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+To analyze traffic and optimize your experience, we serve cookies on this site. By clicking or navigating, you agree to allow our usage of cookies. As the current maintainers of this site, Facebook’s Cookies Policy applies. Learn more, including about available controls: Cookies Policy.
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+ torch_xla.debug.metrics — PyTorch/XLA master documentation
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+ Source code for torch_xla.core.xla_model
+import contextlib
+import io
+import itertools
+import logging
+import sys
+import re
+import threading
+import time
+import warnings
+from typing import Any, Callable, Dict, List, Optional, Set, TextIO, Tuple, TypedDict, Union
+import torch
+import torch.distributed._functional_collectives
+from torch.library import Library
+import torch.nn.functional as F
+import torch.optim as optim
+import torch_xla
+from torch_xla import runtime
+import torch_xla.core.xla_env_vars as xenv
+import torch_xla.debug.metrics_saver as ms
+import torch_xla.utils.utils as xu
+import torch_xla.utils.closures as xc
+from torch_xla.distributed.spmd.xla_sharding import ShardingSpec
+import os
+from torch_xla.experimental.deprecation import deprecated
+import torch_xla._internal.utils as _utils
+
+_DEVICES = xu.LazyProperty(lambda: torch_xla._XLAC._xla_get_devices())
+
+REDUCE_SUM = 'sum'
+REDUCE_MUL = 'mul'
+REDUCE_AND = 'and'
+REDUCE_OR = 'or'
+REDUCE_MIN = 'min'
+REDUCE_MAX = 'max'
+
+_DEVICE_CONTEXTS = dict()
+_DEVICE_CONTEXTS_LOCK = threading.Lock()
+
+XLA_LIB = Library("xla", "DEF")
+
+from . import xla_model as this_module
+
+xrt_world_size = deprecated(this_module, torch_xla.runtime.world_size,
+ 'xrt_world_size() will be removed in release 2.7.')
+get_ordinal = deprecated(
+ this_module, torch_xla.runtime.global_ordinal,
+ 'xla_model.get_ordinal() will be removed in release 2.7.')
+parse_xla_device = deprecated(
+ this_module, _utils.parse_xla_device,
+ 'xla_model.parse_xla_device() will be removed in release 2.7.')
+
+
+class DeviceContext(object):
+
+ def __init__(self, device: Union[str, torch.device]):
+ self.device = device
+
+
+def _get_device_context(
+ device: Optional[Union[str, torch.device]] = None) -> DeviceContext:
+ if device is None:
+ device = torch_xla._XLAC._xla_get_default_device()
+ else:
+ device = str(device)
+ with _DEVICE_CONTEXTS_LOCK:
+ devctx = _DEVICE_CONTEXTS.get(device, None)
+ if devctx is None:
+ devctx = DeviceContext(device)
+ _DEVICE_CONTEXTS[device] = devctx
+ return devctx
+
+
+def is_xla_tensor(tensor: torch.Tensor) -> bool:
+ return tensor.device.type == 'xla'
+
+
+def get_xla_supported_devices(devkind: Optional[str] = None,
+ max_devices: Optional[int] = None) -> List[str]:
+ """Returns a list of supported devices of a given kind.
+
+ Args:
+ devkind (string..., optional): If specified, a device type such as `TPU`,
+ `CUDA`, `CPU`, or name of custom PJRT device.
+ max_devices (int, optional): The maximum number of devices to be returned of
+ that kind.
+
+ Returns:
+ The list of device strings such as ['xla:0', 'xla:1', ...]
+ """
+ # TODO(wcromar): Remove `devkind` after 2.3 release cut. We no longer support
+ # multiple device types.
+ if not devkind:
+ devices = torch_xla._XLAC._xla_get_devices()
+ return [
+ f'xla:{i}'
+ for i, _ in enumerate(devices[:max_devices] if max_devices else devices)
+ ]
+ else:
+ warnings.warn("`devkind` argument is deprecated and will be removed in a "
+ "future release.")
+
+ xla_devices = _DEVICES.value
+ kind_devices = []
+ for i, device in enumerate(xla_devices):
+ if re.match(devkind + r':\d+$', device):
+ kind_devices.append('xla:{}'.format(i))
+ if kind_devices:
+ return kind_devices[:max_devices] if max_devices else kind_devices
+
+
+def get_local_ordinal() -> int:
+ """Retrieves the replication local ordinal of the current thread.
+
+ The local ordinals range from 0 to the number of local devices minus 1.
+
+ Returns:
+ The replication local ordinal of the current thread.
+ """
+ return runtime.local_ordinal()
+
+
+[docs]def is_master_ordinal(local: bool = True) -> bool:
+ """Checks whether the current process is the master ordinal (0).
+
+ Args:
+ local (bool): Whether the local or global master ordinal should be checked.
+ In case of multi-host replication, there is only one global master ordinal
+ (host 0, device 0), while there are NUM_HOSTS local master ordinals.
+ Default: True
+
+ Returns:
+ A boolean indicating whether the current process is the master ordinal.
+ """
+ ordinal = get_local_ordinal() if local else runtime.global_ordinal()
+ return ordinal == 0
+
+
+def master_print(*args: Tuple[Any, ...],
+ fd: TextIO = sys.stdout,
+ local: bool = False,
+ flush: bool = False):
+ if is_master_ordinal(local=local):
+ print(*args, file=fd, flush=flush)
+
+
+[docs]def xla_device(n: Optional[int] = None,
+ devkind: Optional[str] = None) -> torch.device:
+ """Returns a given instance of an XLA device.
+
+ Args:
+ n (int, optional): The specific instance (ordinal) to be returned. If
+ specified, the specific XLA device instance will be returned. Otherwise
+ the first device of `devkind` will be returned.
+ devkind (string..., optional): If specified, device type such as `TPU`,
+ `CUDA`, `CPU`, or custom PJRT device. Deprecated.
+
+ Returns:
+ A `torch.device` with the requested instance.
+ """
+ # When SPMD is enabled, we always return `xla:0` to the user, and
+ # under the hood we use virtual device logic for every xla tensor
+ if xu.check_env_flag('XLA_USE_SPMD'):
+ device = 'xla:0'
+ torch_xla._XLAC._xla_set_default_device(device)
+ return torch.device(device)
+
+ return runtime.xla_device(n, devkind)
+
+
+def _xla_real_device(device: torch.device) -> Any:
+ device_str = str(device)
+ m = re.match(r'xla:(\d+)$', device_str)
+ if not m:
+ raise RuntimeError('Invalid device format: {}'.format(device_str))
+ return _DEVICES.value[int(m.group(1))]
+
+
+def xla_real_devices(devices: Optional[List[torch.device]] = None) -> List[str]:
+ """Returns the real devices' name.
+
+ Args:
+ devices: The list of torch devices such as ['xla:0', 'xla:1'].
+
+ Returns:
+ A list of real devices' name such as ['CUDA:0', 'CUDA:1'].
+ """
+ if not devices:
+ devices = get_xla_supported_devices()
+
+ return [_xla_real_device(device) for device in devices]
+
+
+[docs]def xla_device_hw(device: Union[str, torch.device]) -> str:
+ """Returns the hardware type of the given device.
+
+ Args:
+ device (string or torch.device): The xla device that will be mapped to the
+ real device.
+
+ Returns:
+ A string representation of the hardware type of the given device.
+ """
+ real_device = _xla_real_device(device)
+ return real_device.split(':')[0]
+
+
+def xla_replication_devices(
+ local_devices: Optional[List[torch.device]] = None) -> List[str]:
+ real_devices = xla_real_devices(local_devices)
+ device_types = set()
+ for device in real_devices:
+ xdev = _utils.parse_xla_device(device)
+ device_types.add(xdev[0])
+ if len(device_types) != 1:
+ # No replication if the device set spawns multiple device types.
+ raise RuntimeError(
+ 'Cannot replicate across different device types: devices={}/{}'.format(
+ local_devices, real_devices))
+ device_type = device_types.pop()
+ kind_devices = get_xla_supported_devices()
+ if len(kind_devices) != len(local_devices):
+ # Replication can only happen among all devices of one kind.
+ raise RuntimeError(
+ 'Cannot replicate if number of devices ({}) is different from {}'.
+ format(len(local_devices), len(kind_devices)))
+ replication_devices = []
+ for device in torch_xla._XLAC._xla_get_all_devices():
+ # device is like 'CUDA:0'
+ xdev = _utils.parse_xla_device(device)
+ if not xdev:
+ raise RuntimeError('Invalid device format: {}'.format(device))
+ if xdev[0] == device_type:
+ replication_devices.append(device)
+ sorted_by_ordinal = sorted(
+ replication_devices,
+ key=lambda device: _utils.parse_xla_device(device)[1])
+ return sorted_by_ordinal
+
+
+def unlazy(tensors: List[torch.Tensor]):
+ """Blocks the program until `tensors` are materialized.
+
+ This API is for benchmarking, don't use it in real models.
+
+ Args:
+ tensors: List of `torch.Tensor`s to materialize. For each
+ Tensor `t` in the list, `t.device` must be an `xla` device.
+ """
+ torch_xla._XLAC._xla_sync_multi(tensors, devices=[], wait=True)
+
+
+def set_replication(device: torch.device,
+ devices: Optional[List[torch.device]]):
+ device = str(device)
+ devctx = _get_device_context(device=device)
+ devices = [str(x) for x in devices]
+ if devices:
+ # sample replication_devices: ['CUDA:0', 'CUDA:1', 'CUDA:2', 'CUDA:3']
+ replication_devices = xla_replication_devices(devices)
+ torch_xla._XLAC._xla_set_replication_devices(replication_devices)
+ devctx.device_index = devices.index(device)
+ else:
+ torch_xla._XLAC._xla_set_replication_devices([])
+ devctx.device_index = 0
+ torch_xla._XLAC._set_all_reduce_token(devctx.device, None)
+ torch_xla._XLAC._xla_set_default_device(device)
+
+
+class RateTracker(object):
+
+ def __init__(self, smooth_factor: Optional[float] = None):
+ self._smooth_factor = xu.getenv_as(
+ 'RATE_TRACKER_SMOOTHING', float,
+ 0.4) if smooth_factor is None else smooth_factor
+ self._start_time = time.time()
+ self._partial_time = self._start_time
+ self._partial_count = 0.0
+ self._partial_rate = None
+ self._count = 0.0
+
+ def _update(self, now: float, rate: float):
+ self._partial_count += self._count
+ self._count = 0.0
+ self._partial_time = now
+ self._partial_rate = rate
+
+ def add(self, count: float):
+ self._count += count
+
+ def _smooth(self, current_rate: float) -> float:
+ if self._partial_rate is None:
+ smoothed_rate = current_rate
+ else:
+ smoothed_rate = ((1 - self._smooth_factor) * current_rate +
+ self._smooth_factor * self._partial_rate)
+ return smoothed_rate
+
+ def rate(self):
+ now = time.time()
+ delta = now - self._partial_time
+ report_rate = 0.0
+ if delta > 0:
+ report_rate = self._smooth(self._count / delta)
+ self._update(now, report_rate)
+ return report_rate
+
+ def global_rate(self):
+ delta = time.time() - self._start_time
+ count = self._partial_count + self._count
+ return count / delta if delta > 0 else 0.0
+
+
+class ToXlaTensorArena(object):
+
+ def __init__(self, convert_fn: Callable[[List[torch.Tensor]],
+ List[torch.Tensor]],
+ select_fn: Callable[[torch.Tensor], bool]):
+ self._convert_fn = convert_fn
+ self._select_fn = select_fn
+ self._tensors = []
+
+ def _add(self, tensor: torch.Tensor):
+ self._tensors.append(tensor)
+
+ def _convert(self):
+ self._index = 0
+ if self._tensors:
+ self._converted_tensors = self._convert_fn(self._tensors)
+ else:
+ self._converted_tensors = []
+
+ def _get_converted_tensor(self) -> torch.Tensor:
+ assert self._index < len(self._converted_tensors)
+ new_tensor = self._converted_tensors[self._index]
+ self._index += 1
+ return new_tensor
+
+ def _collect_tensors(self, inputs: Any):
+
+ def collect_fn(value: Any):
+ self._add(value)
+
+ xu.for_each_instance(inputs, lambda x: self._select_fn(x), collect_fn)
+
+ def _replace_tensors(self, inputs: Any):
+
+ def convert_fn(value: Any):
+ return self._get_converted_tensor()
+
+ return xu.for_each_instance_rewrite(inputs, lambda x: self._select_fn(x),
+ convert_fn)
+
+ def transform(self, inputs: Any):
+ self._tensors = []
+ self._collect_tensors(inputs)
+ self._convert()
+ return self._replace_tensors(inputs)
+
+
+def check_view_sharing(obj):
+ tensors = set()
+ aliases = dict()
+
+ def tensor_info(t: torch.Tensor) -> str:
+ return '{}{}'.format(t.dtype, list(t.size()))
+
+ def tensor_id(t: torch.Tensor) -> Tuple[int, str]:
+ if is_xla_tensor(t):
+ return torch_xla._XLAC._xla_get_tensor_id(t), 'xla'
+ return id(t), 'torch'
+
+ def alias_id(t: torch.Tensor) -> Tuple[int, str]:
+ if is_xla_tensor(t):
+ aid = torch_xla._XLAC._xla_get_tensor_view_alias_id(t)
+ return None if aid == 0 else aid, 'xla'
+ return t.storage().data_ptr(), 'torch'
+
+ def check_object(obj):
+ tid = tensor_id(obj)
+ if tid not in tensors:
+ tensors.add(tid)
+ aid = alias_id(obj)
+ if aid[0] is not None:
+ if aid in aliases:
+ oobj = aliases[aid]
+ raise RuntimeError(
+ 'Tensor ID {} ({}) is sharing a view with tensor ID {} ({})'.
+ format(tid, tensor_info(obj), tensor_id(oobj), tensor_info(oobj)))
+ aliases[aid] = obj
+
+ xu.for_each_instance(obj, lambda x: type(x) == torch.Tensor, check_object)
+
+
+def _fetch_gradients(optimizer: optim.Optimizer) -> List[torch.Tensor]:
+ gradients = []
+ for param_group in optimizer.__getstate__()['param_groups']:
+ for group, params in param_group.items():
+ if group == 'params':
+ for p in params:
+ if isinstance(p, torch.Tensor) and p.grad is not None:
+ gradients.append(p.grad.data)
+ return gradients
+
+
+def _get_all_reduce_token() -> Tuple[Any, DeviceContext]:
+ devctx = _get_device_context()
+ token = torch_xla._XLAC._get_all_reduce_token(devctx.device)
+ return token, devctx
+
+
+[docs]def all_reduce(
+ reduce_type: str,
+ inputs: Union[torch.Tensor, List[torch.Tensor]],
+ scale: float = 1.0,
+ groups: Optional[List[List[int]]] = None,
+ pin_layout: bool = True) -> Union[torch.Tensor, List[torch.Tensor]]:
+ """Performs an inplace reduce operation on the input tensor(s).
+
+ Args:
+ reduce_type (string): One of ``xm.REDUCE_SUM``, ``xm.REDUCE_MUL``,
+ ``xm.REDUCE_AND``, ``xm.REDUCE_OR``, ``xm.REDUCE_MIN`` and
+ ``xm.REDUCE_MAX``.
+ inputs: Either a single `torch.Tensor` or a list of `torch.Tensor` to
+ perform the all reduce op to.
+ scale (float): A default scaling value to be applied after the reduce.
+ Default: 1.0
+ groups (list, optional): A list of list, representing the replica groups for
+ the `all_reduce()` operation. Example: `[[0, 1, 2, 3], [4, 5, 6, 7]]`
+ defines two groups, one with the `[0, 1, 2, 3]` replicas and one with
+ the `[4, 5, 6, 7]` replicas. If `None` there will be only one group with
+ all the replicas in it.
+ pin_layout (bool, optional): whether to pin the layout for this communication op.
+ Layout pining can prevent potential data corruption when each process that
+ participate in the communication has slightly different program, but it might
+ cause some xla compilation to fail. Unpin the layout when you see error message
+ like "HloModule has a mix of layout constrained".
+
+ Returns:
+ If a single `torch.Tensor` is passed, the return value is a `torch.Tensor`
+ holding the reduced value (across the replicas). If a list/tuple is passed,
+ this function performs an inplace all-reduce op on the input tensors, and
+ returns the list/tuple itself.
+ """
+ groups = groups or []
+
+ # No-op if there is only one device
+ if runtime.world_size() == 1 and not xu.getenv_as('XLA_ALWAYS_ALLREDUCE',
+ bool, False):
+ if isinstance(inputs, torch.Tensor):
+ return inputs.clone()
+ else:
+ return inputs
+
+ if isinstance(inputs, torch.Tensor):
+ result = None
+ if scale == 1.0 and groups == [] and pin_layout:
+ # TODO(alanwaketan): Support groups.
+ # Only c10d_functional version cc ops are traceable by Dynamo.
+ result = torch.ops._c10d_functional.all_reduce(inputs, reduce_type, "")
+ else:
+ result = torch_xla._XLAC._xla_all_reduce(reduce_type, inputs, scale,
+ groups, pin_layout)
+ results = [result]
+ else:
+ torch_xla._XLAC._xla_all_reduce_inplace(reduce_type, inputs, scale, groups,
+ pin_layout)
+ results = inputs
+ return results[0] if isinstance(inputs, torch.Tensor) else results
+
+
+def _all_gather_using_all_reduce(
+ value: torch.Tensor,
+ dim: int = 0,
+ groups: Optional[List[List[int]]] = None,
+ pin_layout: bool = True) -> Optional[torch.Tensor]:
+ """Performs an all-gather operation using all-reduce along a given dimension.
+
+ Args:
+ value (torch.Tensor): The input tensor.
+ dim (int): The gather dimension.
+ Default: 0
+ groups (list, optional): A list of list, representing the replica groups for
+ the `all_gather()` operation. Example: `[[0, 1, 2, 3], [4, 5, 6, 7]]`
+ defines two groups, one with the `[0, 1, 2, 3]` replicas and one with
+ the `[4, 5, 6, 7]` replicas. If `None` there will be only one group with
+ all the replicas in it.
+ pin_layout (bool, optional): whether to pin the layout for this communication op.
+ Layout pining can prevent potential data corruption when each process that
+ participate in the communication has slightly different program, but it might
+ cause some xla compilation to fail. Unpin the layout when you see error message
+ like "HloModule has a mix of layout constrained".
+
+ Returns:
+ A tensor which has, in the ``dim`` dimension, all the values from the
+ participating replicas.
+ """
+ if dim < 0:
+ dim = value.dim() + dim
+ size = value.size(dim)
+ padding = [0] * (2 * value.dim())
+ ordinal = runtime.global_ordinal()
+ if groups is None:
+ left, right = ordinal, runtime.world_size() - 1 - ordinal
+ else:
+ ordinals = dict()
+ for g in groups:
+ for i, x in enumerate(g):
+ ordinals[x] = (i, len(g) - 1 - i)
+ left, right = ordinals[ordinal]
+ idx = value.dim() - 1 - dim
+ padding[2 * idx] = left * size
+ padding[2 * idx + 1] = right * size
+ return all_reduce(REDUCE_SUM, F.pad(value, padding), groups=groups)
+
+
+[docs]def all_gather(value: torch.Tensor,
+ dim: int = 0,
+ groups: Optional[List[List[int]]] = None,
+ output: Optional[torch.Tensor] = None,
+ pin_layout: bool = True) -> torch.Tensor:
+ """Performs an all-gather operation along a given dimension.
+
+ Args:
+ value (torch.Tensor): The input tensor.
+ dim (int): The gather dimension.
+ Default: 0
+ groups (list, optional): A list of list, representing the replica groups for
+ the `all_gather()` operation. Example: `[[0, 1, 2, 3], [4, 5, 6, 7]]`
+ defines two groups, one with the `[0, 1, 2, 3]` replicas and one with
+ the `[4, 5, 6, 7]` replicas. If `None` there will be only one group with
+ all the replicas in it.
+ output (torch.Tensor): Optional output tensor.
+ pin_layout (bool, optional): whether to pin the layout for this communication op.
+ Layout pining can prevent potential data corruption when each process that
+ participate in the communication has slightly different program, but it might
+ cause some xla compilation to fail. Unpin the layout when you see error message
+ like "HloModule has a mix of layout constrained".
+
+ Returns:
+ A tensor which has, in the ``dim`` dimension, all the values from the
+ participating replicas.
+ """
+ # _all_gather_using_all_reduce does not support list of tensors as input
+ if pin_layout and output == None and isinstance(value, torch.Tensor):
+ # There is not an easy way to pin the all_gather layout, so use all_reduce
+ # based all_gather for this purpose.
+ return _all_gather_using_all_reduce(
+ value, dim=dim, groups=groups, pin_layout=True)
+
+ if dim < 0:
+ dim = value.dim() + dim
+ if groups:
+ shard_count = len(groups[0])
+ assert all(len(group) == shard_count for group in groups), \
+ "Replica groups must have the same number of replicas/shards."
+ else:
+ # All replicas belong to a single group
+ shard_count = runtime.world_size()
+
+ token, devctx = _get_all_reduce_token()
+
+ if isinstance(value, torch.Tensor):
+ if output != None:
+ # Call the out of place version of the all_gather
+ new_token = torch_xla._XLAC._xla_all_gather_out(output, value, token, dim,
+ shard_count, groups or [],
+ pin_layout)
+ torch_xla._XLAC._set_all_reduce_token(devctx.device, new_token)
+ return output
+
+ result = torch_xla._XLAC._xla_all_gather(value, dim, shard_count, groups or
+ [], pin_layout)
+ return result
+
+ # Now the input should be a list of Tensors.
+ elif isinstance(value, list) and all(
+ isinstance(v, torch.Tensor) for v in value):
+ if pin_layout:
+ raise RuntimeError(
+ "For xm.all_gather with list of tensors input, pin_layout=True is not yet supported."
+ )
+ if output != None:
+ if not isinstance(output, list) or any(
+ not isinstance(v, torch.Tensor) for v in output):
+ raise TypeError(
+ f"`output` needs to be a list of Tensors, but given {type(output)}."
+ )
+ if len(output) != len(value):
+ raise ValueError("`output` length doesn't match `input` length: "
+ f"{len(output)} vs {len(input)}.")
+ # Call the out of place version of the reduce_scatter
+ new_token = torch_xla._XLAC._xla_all_gather_coalesced_out(
+ output, value, token, dim, shard_count, groups or [], pin_layout)
+ torch_xla._XLAC._set_all_reduce_token(devctx.device, new_token)
+ return output
+
+ result = torch_xla._XLAC._xla_all_gather_coalesced(value, token, dim,
+ shard_count, groups or
+ [], pin_layout)
+ torch_xla._XLAC._set_all_reduce_token(devctx.device, result[-1])
+ return result[:-1]
+ else:
+ raise TypeError("`value` needs to be a Tensor or a list of Tensors, but "
+ f"given {type(value)}.")
+
+
+class CoalescingBuckets(object):
+
+ def __init__(
+ self,
+ func: Callable[[
+ Union[torch.Tensor,
+ List[torch.Tensor]], Optional[Union[torch.Tensor,
+ List[torch.Tensor]]]
+ ], Union[torch.Tensor, List[torch.Tensor]]],
+ input_list: Any,
+ output_list: Optional[Any] = None,
+ bucket_cap_mb: int = 160):
+ if not isinstance(input_list, list) or any(
+ not isinstance(v, torch.Tensor) for v in input_list):
+ raise TypeError(
+ f"`input_list` needs to be a list of Tensors, but given {type(input_list)}."
+ )
+ if output_list != None:
+ if not isinstance(output_list, list) or any(
+ not isinstance(v, torch.Tensor) for v in output_list):
+ raise TypeError(
+ f"`output_list` needs to be a list of Tensors, but given {type(output_list)}."
+ )
+ if len(output_list) != len(input_list):
+ raise ValueError(
+ "`output_list` length doesn't match `input_list` length: "
+ f"{len(output_list)} vs {len(input_list)}.")
+ self._func = func
+ self._input_list = input_list
+ self._output_list = output_list
+ self._total = 0
+ self._tensor_bucket = []
+ self._output_bucket = [] if output_list else None
+ self._bucket_cap = bucket_cap_mb * 1024 * 1024
+ self._out_tensors = []
+
+ def flush(self):
+ if len(self._tensor_bucket) == 1:
+ # Use non-coalesced CCOp if its just one tensor
+ output = self._output_bucket[0] if self._output_bucket else None
+ self._out_tensors.append(self._func(self._tensor_bucket[0], output))
+ elif len(self._tensor_bucket):
+ self._out_tensors.extend(
+ self._func(self._tensor_bucket, self._output_bucket))
+ self._total = 0
+ self._tensor_bucket = []
+ self._output_bucket = [] if self._output_list else None
+
+ def add(self, tensor: torch.Tensor, idx: int):
+ self._total += tensor.numel() * tensor.element_size()
+ self._tensor_bucket.append(tensor)
+ if self._output_list != None:
+ self._output_bucket.append(self._output_list[idx])
+
+ def __call__(self) -> Union[torch.Tensor, List[torch.Tensor]]:
+ for idx, tensor in enumerate(self._input_list):
+ tensor_bytes = tensor.numel() * tensor.element_size()
+
+ # Aim for target bucket_cap_mb: flush new tensor with bucket if bucket content
+ # is small (1/2 cap) but don't combine if combined total is over 2x cap
+ total_new = self._total + tensor_bytes
+ if tensor_bytes > self._bucket_cap and self._total < 0.5 * self._bucket_cap and total_new <= 2 * self._bucket_cap:
+ self.add(tensor, idx)
+ self.flush()
+ else:
+ # Bucketize till the total spills over
+ if total_new > self._bucket_cap:
+ self.flush()
+ self.add(tensor, idx)
+
+ # Flush the last remaining bucket
+ self.flush()
+
+ assert len(self._out_tensors) == len(self._input_list)
+
+ return self._out_tensors
+
+
+def all_gather_bucketized(
+ input_list: List[torch.Tensor],
+ dim: int = 0,
+ groups: Optional[List[List[int]]] = None,
+ output: Optional[torch.Tensor] = None,
+ pin_layout: bool = False,
+ bucket_cap_mb=160) -> Union[torch.Tensor, List[torch.Tensor]]:
+ """Performs an all-gather operation along a given dimension, with bucketization.
+
+ Args:
+ See all_gather for the args: dim, groups, output, pin_layout
+ input_list: List of input tensors
+ bucket_cap_mb: Number of MegaBytes of the tensor bucket to fill before doing all-gather.
+
+ Returns:
+ A list of tensors each of which has, in the ``dim`` dimension, all the values from the
+ participating replicas.
+ """
+ # sanity checks
+ if pin_layout:
+ raise RuntimeError(
+ "For xm.all_gather_bucketized, pin_layout=True is not yet supported.")
+
+ def _all_gather_coalesced(_input_list, _output_list=None):
+ return all_gather(
+ value=_input_list,
+ dim=dim,
+ groups=groups,
+ output=_output_list,
+ pin_layout=pin_layout)
+
+ buckets = CoalescingBuckets(
+ _all_gather_coalesced, input_list, output, bucket_cap_mb=bucket_cap_mb)
+ return buckets()
+
+
+[docs]def all_to_all(value: torch.Tensor,
+ split_dimension: int,
+ concat_dimension: int,
+ split_count: int,
+ groups: Optional[List[List[int]]] = None,
+ pin_layout: bool = True) -> torch.Tensor:
+ """Performs an XLA `AllToAll()` operation on the input tensor.
+
+ See: https://www.tensorflow.org/xla/operation_semantics#alltoall
+
+ Args:
+ value (torch.Tensor): The input tensor.
+ split_dimension (int): The dimension upon which the split should happen.
+ concat_dimension (int): The dimension upon which the concat should happen.
+ split_count (int): The split count.
+ groups (list, optional): A list of list, representing the replica groups for
+ the `all_reduce()` operation. Example: `[[0, 1, 2, 3], [4, 5, 6, 7]]`
+ defines two groups, one with the `[0, 1, 2, 3]` replicas and one with
+ the `[4, 5, 6, 7]` replicas. If `None` there will be only one group with
+ all the replicas in it.
+ pin_layout (bool, optional): whether to pin the layout for this communication op.
+ Layout pining can prevent potential data corruption when each process that
+ participate in the communication has slightly different program, but it might
+ cause some xla compilation to fail. Unpin the layout when you see error message
+ like "HloModule has a mix of layout constrained".
+
+ Returns:
+ The result `torch.Tensor` of the `all_to_all()` operation.
+ """
+ token, devctx = _get_all_reduce_token()
+ result = torch_xla._XLAC._xla_all_to_all(value, token, split_dimension,
+ concat_dimension, split_count,
+ groups or [], pin_layout)
+ torch_xla._XLAC._set_all_reduce_token(devctx.device, result[1])
+ return result[0]
+
+
+def collective_permute(value: torch.Tensor,
+ pairs: List[List[int]]) -> torch.Tensor:
+ """Performs a XLA `CollectivePermute()` operation on the input tensor.
+
+ WARNING: This function is not very reliable, may produce wrong results under
+ certain inputs. Use it at your own risk.
+
+ See: https://www.tensorflow.org/xla/operation_semantics#collectivepermute
+
+ Args:
+ value (torch.Tensor): The input tensor.
+ pairs (list): A list of (source_replica_id, target_replica_id) pairs,
+ representing the sender and receiver for the `collective_permute()`
+ operation. Example: `[[0, 1], [1, 2], [2, 0]]` defines three pairs. The
+ tensor will be sent from replica 0 to replica 1, replica 1 to replica 2,
+ and replica 2 to replica 0.
+
+ Returns:
+ The result `torch.Tensor` of the `collective_permute()` operation.
+ """
+ token, devctx = _get_all_reduce_token()
+ result = torch_xla._XLAC._xla_collective_permute(value, token, pairs)
+ torch_xla._XLAC._set_all_reduce_token(devctx.device, result[1])
+ return result[0]
+
+
+def collective_broadcast(tensors: List[torch.Tensor],
+ root_ordinal: int = 0,
+ groups: Optional[List[int]] = None,
+ pin_layout: bool = True) -> None:
+ """Broadcast values of `tensors` from root replica to other replicas in-place.
+
+ Args:
+ tensors (list): List of `torch.Tensor`s to broadcast.
+ root_ordinal (int): Ordinal of replica with values to broadcast.
+ groups (list, optional): A list of list, representing the replica groups for
+ the `all_reduce()` operation. Example: `[[0, 1, 2, 3], [4, 5, 6, 7]]`
+ defines two groups, one with the `[0, 1, 2, 3]` replicas and one with
+ the `[4, 5, 6, 7]` replicas. If `None` there will be only one group with
+ all the replicas in it.
+ pin_layout (bool, optional): whether to pin the layout for this communication op.
+ Layout pining can prevent potential data corruption when each process that
+ participate in the communication has slightly different program, but it might
+ cause some xla compilation to fail. Unpin the layout when you see error message
+ like "HloModule has a mix of layout constrained".
+ """
+ with torch.no_grad():
+ # We must produce the exact same graph in each replica to prevent hanging,
+ # so each replica must have the same multiply op with the same parameters.
+ for tensor in tensors:
+ scale = torch.tensor(
+ 1 if runtime.global_ordinal() == root_ordinal else 0,
+ dtype=tensor.dtype)
+ # Transfer scale tensor as device data instead of constant 1 or 0.
+ xscale = send_cpu_data_to_device(scale, tensor.device)
+ tensor.mul_(xscale[0])
+
+ all_reduce(REDUCE_SUM, tensors, groups=groups, pin_layout=pin_layout)
+
+
+def send(value: torch.Tensor, channel_id: int) -> torch.Tensor:
+ """Performs a XLA `Send()` operation on the input tensor.
+
+ See: https://www.tensorflow.org/xla/operation_semantics#send
+
+ Args:
+ value (torch.Tensor): The input tensor.
+ channel_id (int64): opaque id identifying the destination of the send op.
+ """
+ token, devctx = _get_all_reduce_token()
+ # The input will be returned as result.
+ input_as_result, new_token = torch_xla._XLAC._xla_send(
+ value, token, channel_id)
+ torch_xla._XLAC._set_all_reduce_token(devctx.device, new_token)
+ return input_as_result
+
+
+def recv(output: torch.Tensor, channel_id: int) -> torch.Tensor:
+ """Performs a XLA `Recv()` operation on the input tensor.
+
+ See: https://www.tensorflow.org/xla/operation_semantics#recv
+
+ Args:
+ output (torch.Tensor): The output tensor.
+ channel_id (int64): opaque id identifying the source of the recv op.
+ """
+ token, devctx = _get_all_reduce_token()
+ result, new_token = torch_xla._XLAC._xla_recv(output, token, channel_id)
+ torch_xla._XLAC._set_all_reduce_token(devctx.device, new_token)
+ return result
+
+
+def reduce_scatter(reduce_type: str,
+ input: Union[torch.Tensor, List[torch.Tensor]],
+ scale: float,
+ scatter_dim: int,
+ shard_count: int,
+ groups: Optional[List[List[int]]] = None,
+ output: Optional[Union[torch.Tensor,
+ List[torch.Tensor]]] = None,
+ pin_layout: bool = True) -> torch.Tensor:
+ """Performs a XLA `ReduceScatter()` operation on the input tensor.
+
+ See: https://www.tensorflow.org/xla/operation_semantics#reducescatter
+
+ Args:
+ reduce_type (string): One of ``xm.REDUCE_SUM``, ``xm.REDUCE_MUL``,
+ ``xm.REDUCE_AND``, ``xm.REDUCE_OR``, ``xm.REDUCE_MIN`` and
+ ``xm.REDUCE_MAX``.
+ input: (torch.Tensor or a list of torch.Tensor): The input. If it's a list, then
+ it will also be the output.
+ scale (float): A default scaling value to be applied after the reduce.
+ scatter_dim (int): Dimension number to which apply scatter operation.
+ shard_count (int): The number of ways to split up the scatter_dim in.
+ groups (list): A list of list, representing the replica groups for
+ the `reduce_scatter()` operation. Example: `[[0, 1, 2, 3], [4, 5, 6, 7]]`
+ defines two groups, one with the `[0, 1, 2, 3]` replicas and one with
+ the `[4, 5, 6, 7]` replicas. If `None` there will be only one group with
+ all the replicas in it.
+ output: Optional output tensor if `input` is a torch.Tensor, or a list of
+ torch.Tensor if `input` is a list of torch.Tensor.
+ pin_layout (bool, optional): whether to pin the layout for this communication op.
+ Layout pining can prevent potential data corruption when each process that
+ participate in the communication has slightly different program, but it might
+ cause some xla compilation to fail. Unpin the layout when you see error message
+ like "HloModule has a mix of layout constrained".
+
+ Returns:
+ A `torch.Tensor` with all the values reduced across replicas. Each process
+ gets a shard split along the `scatter_dim`. All other dimensions are
+ the same as the input.
+ """
+ token, devctx = _get_all_reduce_token()
+
+ if isinstance(input, torch.Tensor):
+ if output != None:
+ # Call the out of place version of the reduce_scatter
+ new_token = torch_xla._XLAC._xla_reduce_scatter_out(
+ reduce_type, output, input, token, scale, scatter_dim, shard_count,
+ groups or [], pin_layout)
+ torch_xla._XLAC._set_all_reduce_token(devctx.device, new_token)
+ return output
+
+ result = torch_xla._XLAC._xla_reduce_scatter(reduce_type, input, token,
+ scale, scatter_dim,
+ shard_count, groups or [],
+ pin_layout)
+ torch_xla._XLAC._set_all_reduce_token(devctx.device, result[1])
+ return result[0]
+
+ # Now the input should be a list of Tensors.
+ elif isinstance(input, list) and all(
+ isinstance(v, torch.Tensor) for v in input):
+ if output != None:
+ if not isinstance(output, list) or any(
+ not isinstance(v, torch.Tensor) for v in output):
+ raise TypeError(
+ f"`output` needs to be a list of Tensors, but given {type(output)}."
+ )
+ if len(output) != len(input):
+ raise ValueError("`output` length doesn't match `input` length: "
+ f"{len(output)} vs {len(input)}.")
+ # Call the out of place version of the reduce_scatter
+ new_token = torch_xla._XLAC._xla_reduce_scatter_coalesced_out(
+ reduce_type, output, input, token, scale, scatter_dim, shard_count,
+ groups or [], pin_layout)
+ torch_xla._XLAC._set_all_reduce_token(devctx.device, new_token)
+ return output
+
+ result = torch_xla._XLAC._xla_reduce_scatter_coalesced(
+ reduce_type, input, token, scale, scatter_dim, shard_count, groups or
+ [], pin_layout)
+ torch_xla._XLAC._set_all_reduce_token(devctx.device, result[-1])
+ return result[:-1]
+ else:
+ raise TypeError("`input` needs to be a Tensor or a list of Tensors, but "
+ f"given {type(input)}.")
+
+
+def reduce_scatter_bucketized(reduce_type: str,
+ input_list: Union[torch.Tensor,
+ List[torch.Tensor]],
+ scale: float,
+ scatter_dim: int,
+ shard_count: int,
+ groups: Optional[List[List[int]]] = None,
+ output: Optional[Union[
+ torch.Tensor, List[torch.Tensor]]] = None,
+ pin_layout: bool = False,
+ bucket_cap_mb: int = 160) -> CoalescingBuckets:
+ """Performs a XLA `ReduceScatter()` operation on a list of tensors (bucketized).
+
+ See: https://www.tensorflow.org/xla/operation_semantics#reducescatter
+
+ Args:
+ see reduce_scatter for reduce_type, scale, scatter_dim, shard_count, groups, pin_layout
+ input_list: List of input tensors
+ output: Optional list of output torch.Tensor
+ bucket_cap_mb: Number of MegaBytes of the tensor bucket to fill before doing reduce-scatter.
+
+ Returns:
+ A list of `torch.Tensors` with all the values reduced across replicas. Each process
+ gets a shard split along the `scatter_dim`. All other dimensions are
+ the same as the input.
+ """
+
+ def _reduce_scatter_coalesced(
+ _input_list: Union[torch.Tensor, List[torch.Tensor]],
+ _output_list: Optional[Union[torch.Tensor, List[torch.Tensor]]] = None
+ ) -> Union[torch.Tensor, List[torch.Tensor]]:
+ return reduce_scatter(
+ reduce_type=reduce_type,
+ input=_input_list,
+ scale=scale,
+ scatter_dim=scatter_dim,
+ shard_count=shard_count,
+ groups=groups,
+ output=_output_list,
+ pin_layout=pin_layout)
+
+ buckets = CoalescingBuckets(
+ _reduce_scatter_coalesced,
+ input_list,
+ output,
+ bucket_cap_mb=bucket_cap_mb)
+ return buckets()
+
+
+[docs]def add_step_closure(closure: Callable[..., Any],
+ args: Tuple[Any] = (),
+ run_async: bool = False):
+ """Adds a closure to the list of the ones to be run at the end of the step.
+
+ Many times during model training there is the need to print/report (print to
+ console, post to tensorboard, etc...) information which require the content of
+ intermediary tensors to be inspected.
+ Inspecting different tensors content in different points of the model code
+ requires many executions and typically causes performance issues.
+ Adding a step closure will ensure that it will be run after the barrier, when
+ all the live tensors will be already materialized to device data.
+ Live tensors which will include the ones captured by the closure arguments.
+ So using `add_step_closure()` will ensure a single execution will be
+ performed, even when multiple closures are queued, requiring multiple tensors
+ to be inspected.
+ Step closures will be run sequentially in the order they have been queued.
+ Note that even though using this API the execution will be optimized, it is
+ advised to throttle the printing/reporting events once every N steps.
+
+ Args:
+ closure (callable): The function to be called.
+ args (tuple): The arguments to be passed to the closure.
+ run_async: If True, run the closure asynchronously.
+ """
+ devctx = _get_device_context()
+ closures_type = 'async_step_closures' if run_async else 'step_closures'
+ step_closures = getattr(devctx, closures_type, None)
+ if step_closures is None:
+ step_closures = []
+ setattr(devctx, closures_type, step_closures)
+ step_closures.append(lambda a=args: closure(*a))
+
+
+def _run_step_closures() -> DeviceContext:
+ devctx = _get_device_context()
+ async_step_closures = getattr(devctx, 'async_step_closures', None)
+ if async_step_closures is not None:
+ devctx.async_step_closures = []
+ async_closure_handler = getattr(devctx, 'async_closure_handler', None)
+ if async_closure_handler is None:
+ async_closure_handler = xc.AsyncClosureHandler()
+ devctx.async_closure_handler = async_closure_handler
+ async_closure_handler.run_all(async_step_closures)
+
+ step_closures = getattr(devctx, 'step_closures', None)
+ if step_closures is not None:
+ devctx.step_closures = []
+ for closure in step_closures:
+ closure()
+ return devctx
+
+
+def mark_step(wait: bool = False, reset_scope: bool = True):
+ if xu.getenv_as('XLA_EMIT_STEPLOG', bool, False):
+ print(
+ 'torch_xla.core.xla_model::mark_step\n',
+ end='',
+ file=sys.stderr,
+ flush=True)
+ torch_xla._XLAC._xla_step_marker(
+ torch_xla._XLAC._xla_get_default_device(), [],
+ wait=xu.getenv_as('XLA_SYNC_WAIT', bool, wait),
+ reset_scope=reset_scope)
+ # Only emit metrics from the first local device index, to avoid emitting the
+ # same values from different threads.
+ if is_master_ordinal():
+ ms.save_metrics()
+ devctx = _run_step_closures()
+ torch_xla._XLAC._set_all_reduce_token(devctx.device, None)
+
+
+# TODO(lsy323): When `tensors` is empty, the some intermediate tensors will also be
+# dump as outputs. Need further investigation.
+[docs]def get_stablehlo(tensors: Optional[List[torch.Tensor]] = None) -> str:
+ """Get StableHLO for the computation graph in string format.
+
+ If `tensors` is not empty, the graph with `tensors` as outputs will be dump.
+ If `tensors` is empty, the whole computation graph will be dump.
+
+ For inference graph, it is recommended to pass the model outputs to `tensors`.
+ For training graph, it is not straightforward to identify the "outputs". Using empty `tensors` is recommended.
+
+ To enable source line info in StableHLO, please set env var XLA_HLO_DEBUG=1.
+
+ Args:
+ tensors (list[torch.Tensor], optional): Tensors that represent the output/root of the StableHLO graph.
+
+ Returns:
+ StableHLO Module in string format.
+ """
+ if tensors is None:
+ tensors = []
+ return torch_xla._XLAC._get_stablehlo(
+ tensors, torch_xla._XLAC._xla_get_default_device(), [],
+ False).decode('utf-8')
+
+
+# TODO(lsy323): When `tensors` is empty, the some intermediate tensors will also be
+# dump as outputs. Need further investigation.
+[docs]def get_stablehlo_bytecode(tensors: Optional[torch.Tensor] = None) -> bytes:
+ """Get StableHLO for the computation graph in bytecode format.
+
+ If `tensors` is not empty, the graph with `tensors` as outputs will be dump.
+ If `tensors` is empty, the whole computation graph will be dump.
+
+ For inference graph, it is recommended to pass the model outputs to `tensors`.
+ For training graph, it is not straightforward to identify the "outputs". Using empty `tensors` is recommended.
+
+ Args:
+ tensors (list[torch.Tensor], optional): Tensors that represent the output/root of the StableHLO graph.
+
+ Returns:
+ StableHLO Module in bytecode format.
+ """
+ if tensors is None:
+ tensors = []
+ return torch_xla._XLAC._get_stablehlo(
+ tensors, torch_xla._XLAC._xla_get_default_device(), [], True)
+
+
+[docs]def wait_device_ops(devices: List[str] = []):
+ """Waits for all the async operations on the given devices to complete.
+
+ Args:
+ devices (string..., optional): The devices whose async ops need to be waited
+ for. If empty, all the local devices will be waited for.
+ """
+ torch_xla._XLAC._xla_wait_device_ops(devices=devices)
+
+
+def all_reduce_bucketized_gradients(gradients: List[torch.Tensor],
+ scale: float,
+ groups: Optional[List[List[int]]],
+ pin_layout: bool,
+ bucket_cap_mb: int = 0):
+ total = 0
+ tensor_bucket = []
+ bucket_cap = bucket_cap_mb * 1024 * 1024
+
+ for grad in gradients:
+ grad_bytes = grad.numel() * grad.element_size()
+
+ # Bucketize till the total spills over
+ total += grad_bytes
+ if total > bucket_cap and len(tensor_bucket) > 0:
+ all_reduce(
+ REDUCE_SUM,
+ tensor_bucket,
+ scale=scale,
+ groups=groups,
+ pin_layout=pin_layout)
+ total = grad_bytes
+ tensor_bucket = []
+ tensor_bucket.append(grad)
+
+ # Flush the last remaining bucket
+ if len(tensor_bucket):
+ all_reduce(
+ REDUCE_SUM,
+ tensor_bucket,
+ scale=scale,
+ groups=groups,
+ pin_layout=pin_layout)
+
+
+def reduce_gradients(optimizer: optim.Optimizer,
+ groups: Optional[List[List[int]]] = None,
+ pin_layout: bool = True):
+ """Reduces all the gradients handled by an optimizer.
+
+ Args:
+ optimizer (:class:`torch.Optimizer`): The `torch.Optimizer` instance
+ containing the gradients to be reduced.
+ groups (list, optional): A list of list, representing the replica groups for
+ the `all_reduce()` operation. Example: `[[0, 1, 2, 3], [4, 5, 6, 7]]`
+ defines two groups, one with the `[0, 1, 2, 3]` replicas and one with
+ the `[4, 5, 6, 7]` replicas. If `None` there will be only one group with
+ all the replicas in it.
+ pin_layout (bool, optional): whether to pin the layout when reducing gradients.
+ See `xm.all_reduce` for details.
+ """
+ count = runtime.world_size()
+ if count > 1:
+ gradients = _fetch_gradients(optimizer)
+ bucket_cap_mb = int(os.getenv('ALLREDUCE_GRADIENTS_BUCKET_SIZE_MB', 0))
+ # Reverse the gradients list so that we start allreduce from the last layer
+ # onwards. This allows allreduce to trigger as soon as the bucket fills up and
+ # overlap with backward pass.
+ if bucket_cap_mb > 0:
+ gradients = reversed(gradients)
+ all_reduce_bucketized_gradients(
+ gradients,
+ scale=1.0 / count,
+ groups=groups,
+ pin_layout=pin_layout,
+ bucket_cap_mb=bucket_cap_mb)
+ else:
+ all_reduce(
+ REDUCE_SUM,
+ gradients,
+ scale=1.0 / count,
+ groups=groups,
+ pin_layout=pin_layout)
+
+
+[docs]def optimizer_step(optimizer: optim.Optimizer,
+ barrier: bool = False,
+ optimizer_args: Dict = {},
+ groups: Optional[List[List[int]]] = None,
+ pin_layout: bool = True):
+ """Run the provided optimizer step and sync gradidents across all devices.
+
+ Args:
+ optimizer (:class:`torch.Optimizer`): The `torch.Optimizer` instance whose
+ `step()` function needs to be called. The `step()` function will be called
+ with the `optimizer_args` named arguments.
+ barrier (bool, optional): Whether the XLA tensor barrier should be issued in
+ this API. If using the PyTorch XLA `ParallelLoader` or `DataParallel`
+ support, this is not necessary as the barrier will be issued by the XLA
+ data loader iterator `next()` call.
+ Default: False
+ optimizer_args (dict, optional): Named arguments dictionary for the
+ `optimizer.step()` call.
+ groups (list, optional): A list of list, representing the replica groups for
+ the `all_reduce()` operation. Example: `[[0, 1, 2, 3], [4, 5, 6, 7]]`
+ defines two groups, one with the `[0, 1, 2, 3]` replicas and one with
+ the `[4, 5, 6, 7]` replicas. If `None` there will be only one group with
+ all the replicas in it.
+ pin_layout (bool, optional): whether to pin the layout when reducing gradients.
+ See `xm.all_reduce` for details.
+
+ Returns:
+ The same value returned by the `optimizer.step()` call.
+
+ Example:
+
+ >>> import torch_xla.core.xla_model as xm
+ >>> xm.optimizer_step(self.optimizer)
+ """
+ reduce_gradients(optimizer, groups=groups, pin_layout=pin_layout)
+ loss = optimizer.step(**optimizer_args)
+ if barrier:
+ mark_step()
+ return loss
+
+
+[docs]def save(data: Any,
+ file_or_path: Union[str, TextIO],
+ master_only: bool = True,
+ global_master: bool = False):
+ """Saves the input data into a file.
+
+ The saved data is transferred to PyTorch CPU device before being saved, so a
+ following `torch.load()` will load CPU data.
+ Care must be taken when working with views. Instead of saving views it's
+ recommended that you recreate them after the tensors have been loaded and
+ moved to their destination device(s).
+
+ Args:
+ data: The input data to be saved. Any nested combination of Python objects
+ (list, tuples, sets, dicts, ...).
+ file_or_path: The destination for the data saving operation. Either a file
+ path or a Python file object. If `master_only` is ``False`` the path or
+ file objects must point to different destinations as otherwise all the
+ writes from the same host will override each other.
+ master_only (bool, optional): Whether only the master device should save the
+ data. If False, the `file_or_path` argument should be a different file or
+ path for each of the ordinals taking part to the replication, otherwise
+ all the replicas on the same host will be writing to the same location.
+ Default: True
+ global_master (bool, optional): When ``master_only`` is ``True`` this flag
+ controls whether every host's master (if ``global_master`` is ``False``)
+ saves the content, or only the global master (ordinal 0).
+ Default: False
+
+ Example:
+
+ >>> import torch_xla.core.xla_model as xm
+ >>> xm.wait_device_ops() # wait for all pending operations to finish.
+ >>> xm.save(obj_to_save, path_to_save)
+ >>> xm.rendezvous('torch_xla.core.xla_model.save') # multi process context only
+ """
+ should_write_data = not master_only or is_master_ordinal(
+ local=not global_master)
+
+ cpu_data = _maybe_convert_to_cpu(data, convert=should_write_data)
+ if should_write_data:
+ torch.save(cpu_data, file_or_path)
+
+
+def _maybe_convert_to_cpu(data: Any, convert: bool = True) -> ToXlaTensorArena:
+
+ def convert_fn(tensors):
+ torch_xla._XLAC._xla_sync_multi(
+ tensors, devices=[], wait=True, sync_xla_data=True)
+ if not convert:
+ return tensors
+ return torch_xla._XLAC._xla_get_cpu_tensors(tensors)
+
+ def select_fn(v):
+ return type(v) == torch.Tensor and is_xla_tensor(v)
+
+ return ToXlaTensorArena(convert_fn, select_fn).transform(data)
+
+
+def send_cpu_data_to_device(
+ datas: Any,
+ device: Union[str, torch.device],
+ input_sharding: Optional[ShardingSpec] = None) -> ToXlaTensorArena:
+
+ def convert_fn(tensors):
+ devices = [str(device)] * len(tensors)
+ shardings = None
+ if input_sharding:
+ shardings = [input_sharding.xla_spec(t) for t in tensors]
+ xtensors = torch_xla._XLAC._xla_tensors_from_aten(tensors, devices,
+ shardings)
+ return xtensors
+
+ def select_fn(v):
+ return type(v) == torch.Tensor and v.device.type == 'cpu'
+
+ if type(datas) is torch.Tensor:
+ datas = [datas]
+ return ToXlaTensorArena(convert_fn, select_fn).transform(datas)
+
+
+def xla_rendezvous(payload: bytes = b'',
+ ordinals: Optional[List[int]] = None,
+ tag: Optional[str] = None) -> List[bytes]:
+ """Share `payload` with all replicas in `ordinals`.
+
+ `tag` is ignored except for logging.
+
+ Uses XLA collective communication to communicate between replicas, so this
+ will sync the graph (`xm.mark_step`).
+
+ Args:
+ tag: Name of this rendezvous operation.
+ payload: Payload to share with other replicas.
+ ordinals: List of replicas participating in rendezvous.
+ Returns:
+ List of bytes from other replicas.
+ """
+ if ordinals and len(ordinals) != runtime.global_device_count():
+ raise ValueError('Only global rendezvous is supported')
+
+ if not isinstance(payload, bytes):
+ raise TypeError('`payload` must be bytes, not {}'.format(type(payload)))
+
+ # Finish all execution of previous graphs to avoid recompilation
+ mark_step()
+
+ device = xla_device()
+
+ data = torch.tensor(list(payload), dtype=torch.uint8)
+ size = torch.tensor([data.shape[0]], dtype=torch.int, device=device)
+
+ if tag:
+ logging.info(f"Joining rendezvous '{tag}'...")
+
+ sizes = all_gather(size)
+
+ max_size = torch.max(sizes)
+ mark_step()
+
+ # If all payloads are empty, return immediately to avoid more CPU transfers
+ if max_size.item() < 1:
+ return [b'' for _ in range(sizes.size()[0])]
+
+ padded_data = torch.nn.functional.pad(data, (
+ 0,
+ max_size.item() - size.item(),
+ )).to(xla_device())
+ raw_data = all_gather(padded_data)
+ data_list = torch.split(raw_data, max_size)
+
+ payloads = [d[:sz] for d, sz in zip(data_list, sizes.cpu())]
+ mark_step()
+
+ return [bytes(p.cpu().tolist()) for p in payloads]
+
+
+[docs]def rendezvous(tag: str,
+ payload: bytes = b'',
+ replicas: List[int] = []) -> List[bytes]:
+ """Waits for all the mesh clients to reach the named rendezvous.
+
+ Note: PJRT does not support the XRT mesh server, so this is effectively an
+ alias to `xla_rendezvous`.
+
+ Args:
+ tag (string): The name of the rendezvous to join.
+ payload (bytes, optional): The payload to be sent to the rendezvous.
+ replicas (list, int): The replica ordinals taking part of the rendezvous.
+ Empty means all replicas in the mesh.
+ Default: []
+
+ Returns:
+ The payloads exchanged by all the other cores, with the payload of core
+ ordinal `i` at position `i` in the returned tuple.
+
+ Example:
+
+ >>> import torch_xla.core.xla_model as xm
+ >>> xm.rendezvous('example')
+ """
+ return xla_rendezvous(payload, replicas or None, tag=tag)
+
+
+def do_on_ordinals(
+ target: Callable[..., Any],
+ data: Union[Tuple, Any] = (),
+ ordinals: Union[List[int], Set[int], int] = (0,)
+) -> Optional[Any]:
+ """Runs a function only on a given set of ordinals.
+
+ Args:
+ target (callable): The function to be run on `ordinals`.
+ data: Any input data for the `target` function which contains tensors. All
+ the XLA tensors used by the `target` function must be passed in this
+ argument. Every other data used by the function can be captured by the
+ Python interpreter as usual.
+ Default: ()
+ ordinals (list, int): The list/set of ordinals where the `target` function
+ should run.
+ Default: (0,)
+
+ Returns:
+ In the ordinals that ran the `target` function, the function return value,
+ otherwise `None`.
+ """
+ running = runtime.global_ordinal() in ordinals
+ cpu_data = _maybe_convert_to_cpu(data, convert=running)
+ if running:
+ result = target(*cpu_data)
+ else:
+ result = None
+ rendezvous('torch_xla.core.xla_model.do_on_ordinals')
+ return result
+
+
+[docs]def mesh_reduce(tag: str, data,
+ reduce_fn: Callable[..., Any]) -> Union[Any, ToXlaTensorArena]:
+ """Performs an out-of-graph client mesh reduction.
+
+ Args:
+ tag (string): The name of the rendezvous to join.
+ data: The data to be reduced. The `reduce_fn` callable will receive a list
+ with the copies of the same data coming from all the mesh client processes
+ (one per core).
+ reduce_fn (callable): A function which receives a list of `data`-like
+ objects and returns the reduced result.
+
+ Returns:
+ The reduced value.
+
+ Example:
+
+ >>> import torch_xla.core.xla_model as xm
+ >>> import numpy as np
+ >>> accuracy = xm.mesh_reduce('test_accuracy', accuracy, np.mean)
+ """
+ cpu_data = _maybe_convert_to_cpu(data)
+ bio = io.BytesIO()
+ torch.save(cpu_data, bio)
+ xdata = rendezvous(tag, bio.getvalue())
+ xldata = []
+ for xd in xdata:
+ xbio = io.BytesIO(xd)
+ xldata.append(torch.load(xbio))
+ return reduce_fn(xldata) if xldata else cpu_data
+
+
+[docs]def set_rng_state(seed: int, device: Optional[str] = None):
+ """Sets the random number generator state.
+
+ Args:
+ seed (integer): The state to be set.
+ device (string, optional): The device where the RNG state needs to be set.
+ If missing the default device seed will be set.
+ """
+ if device is None:
+ device = torch_xla._XLAC._xla_get_default_device()
+ torch_xla._XLAC._xla_set_rng_seed(seed, str(device) if device else '')
+
+
+[docs]def get_rng_state(device: Optional[str] = None) -> int:
+ """Gets the current running random number generator state.
+
+ Args:
+ device (string, optional): The device whose RNG state needs to be retrieved.
+ If missing the default device seed will be set.
+
+ Returns:
+ The RNG state, as integer.
+ """
+ if device is None:
+ device = torch_xla._XLAC._xla_get_default_device()
+ return torch_xla._XLAC._xla_get_rng_seed(str(device) if device else '')
+
+
+@contextlib.contextmanager
+def fork_rng(device: Optional[str] = None, enabled: bool = True):
+ """
+ Forks the RNG, so that when you return, the RNG is reset to the state that it was previously in.
+ Args:
+ device (string, optional): The device where the RNG state needs to be set. If missing the default device seed will be set.
+ enabled (bool): if ``False``, the RNG is not forked. This is a convenience argument for easily disabling the context manager without having to delete it and unindent your Python code under it.
+ """
+ if not enabled:
+ yield
+ return
+
+ if device is None:
+ device = torch_xla._XLAC._xla_get_default_device()
+ xla_rng_state = get_rng_state(device=device)
+
+ try:
+ yield
+ finally:
+ set_rng_state(xla_rng_state, device=device)
+
+
+class MemoryInfo(TypedDict):
+ bytes_used: str
+ bytes_limit: int
+
+
+[docs]def get_memory_info(device: Optional[torch.device] = None) -> MemoryInfo:
+ """Retrieves the device memory usage.
+
+ Args:
+ device: Optional[torch.device] The device whose memory information are requested.
+ If not passed will use the default device.
+
+ Returns:
+ MemoryInfo dict with memory usage for the given device.
+
+ Example:
+
+ >>> xm.get_memory_info()
+ {'bytes_used': 290816, 'bytes_limit': 34088157184}
+ """
+ if device == None:
+ device = xla_device()
+ return torch_xla._XLAC._xla_memory_info(str(device))
+
+
+def optimization_barrier_(tensors: List[torch.Tensor]):
+ """Blocks xla compiler from moving computations across this barrier. The common
+ use case would be blocking xla common-subexpression elimination pass from undoing
+ the gradient checkpointing.
+
+ Args:
+ tensors (List[torch.Tensor]): List of `torch.Tensor` to add barrier to.
+ """
+ torch_xla._XLAC._xla_optimization_barrier_(tensors)
+
+
+def broadcast_master_param(model: torch.nn.Module) -> None:
+ """
+ Broadcast the model parameters from master process to other processes
+ """
+ parameters_and_buffers = list(
+ itertools.chain(model.parameters(), model.buffers()))
+ collective_broadcast(parameters_and_buffers)
+ mark_step()
+
+
+
+
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+
\ No newline at end of file
diff --git a/release/2.5/_modules/torch_xla/debug/metrics.html b/release/2.5/_modules/torch_xla/debug/metrics.html
new file mode 100644
index 00000000000..97360be23c7
--- /dev/null
+++ b/release/2.5/_modules/torch_xla/debug/metrics.html
@@ -0,0 +1,792 @@
+
+
+
+
+
+
+
+
+
+
+
+
+ 
+
+To analyze traffic and optimize your experience, we serve cookies on this site. By clicking or navigating, you agree to allow our usage of cookies. As the current maintainers of this site, Facebook’s Cookies Policy applies. Learn more, including about available controls: Cookies Policy.
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ torch_xla.distributed.parallel_loader — PyTorch/XLA master documentation
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
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+
+
+
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+
+
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+
+
+
+
+
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+
+
+
+
+
+
+
+
+
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+
+
+
+
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+
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+
+
+
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+
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+
+
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+
+
+
+
+
+
+
+
+
+
+ Source code for torch_xla.debug.metrics
+import torch_xla
+
+
+[docs]def counter_names():
+ """Retrieves all the currently active counter names."""
+ return torch_xla._XLAC._xla_counter_names()
+
+
+[docs]def counter_value(name):
+ """Returns the value of an active counter.
+
+ Args:
+ name (string): The name of the counter whose value needs to be retrieved.
+
+ Returns:
+ The counter value as integer.
+ """
+ return torch_xla._XLAC._xla_counter_value(name)
+
+
+def clear_counters():
+ """Clear the value of all counters.
+ """
+ return torch_xla._XLAC._clear_xla_counters()
+
+
+[docs]def metric_names():
+ """Retrieves all the currently active metric names."""
+ return torch_xla._XLAC._xla_metric_names()
+
+
+[docs]def metric_data(name):
+ """Returns the data of an active metric.
+
+ Args:
+ name (string): The name of the metric whose data needs to be retrieved.
+
+ Returns:
+ The metric data, which is a tuple of (TOTAL_SAMPLES, ACCUMULATOR, SAMPLES).
+ The `TOTAL_SAMPLES` is the total number of samples which have been posted to
+ the metric. A metric retains only a given number of samples (in a circular
+ buffer).
+ The `ACCUMULATOR` is the sum of the samples over `TOTAL_SAMPLES`.
+ The `SAMPLES` is a list of (TIME, VALUE) tuples.
+ """
+ return torch_xla._XLAC._xla_metric_data(name)
+
+
+def clear_metrics():
+ """Clear the value of all metrics.
+ """
+ return torch_xla._XLAC._clear_xla_metrics()
+
+
+def clear_all():
+ """Clear the value of all metrics and all counters.
+ """
+ clear_metrics()
+ clear_counters()
+
+
+[docs]def metrics_report():
+ """Retrieves a string containing the full metrics and counters report."""
+ return torch_xla._XLAC._xla_metrics_report()
+
+
+[docs]def short_metrics_report(counter_names: list = None, metric_names: list = None):
+ """Retrieves a string containing the full metrics and counters report.
+
+ Args:
+ counter_names (list): The list of counter names whose data needs to be printed.
+ metric_names (list): The list of metric names whose data needs to be printed.
+ """
+ if not counter_names:
+ counter_names = ['CachedCompile', 'MarkStep', 'DynamoSyncInputExecuteTime']
+ if not metric_names:
+ metric_names = [
+ 'CompileTime', 'ExecuteTime', 'ExecuteReplicatedTime',
+ 'TransferToDeviceTime', 'TransferFromDeviceTime'
+ ]
+ return torch_xla._XLAC._short_xla_metrics_report(counter_names, metric_names)
+
+
+def executed_fallback_ops():
+ """Retrieves a list of operations that were run in fallback mode."""
+ return torch_xla._XLAC._get_executed_fallback_ops()
+
+
+
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\ No newline at end of file
diff --git a/release/2.5/_modules/torch_xla/distributed/parallel_loader.html b/release/2.5/_modules/torch_xla/distributed/parallel_loader.html
new file mode 100644
index 00000000000..37bc6ba182b
--- /dev/null
+++ b/release/2.5/_modules/torch_xla/distributed/parallel_loader.html
@@ -0,0 +1,973 @@
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+To analyze traffic and optimize your experience, we serve cookies on this site. By clicking or navigating, you agree to allow our usage of cookies. As the current maintainers of this site, Facebook’s Cookies Policy applies. Learn more, including about available controls: Cookies Policy.
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ torch_xla.distributed.spmd.xla_sharding — PyTorch/XLA master documentation
+
+
+
+
+
+
+
+
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+
+
+
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+
+
+
+
+
+
+
+
+
+
+
+
+ Source code for torch_xla.distributed.parallel_loader
+import itertools
+import queue
+import threading
+import torch
+import torch_xla
+import torch_xla.debug.profiler as xp
+import torch_xla.utils.keyd_queue as kq
+import torch_xla.utils.utils as xu
+import torch_xla.core.xla_model as xm
+
+
+class PerDeviceQueue(object):
+
+ def __init__(self, device, loader_prefetch_size, device_prefetch_size):
+ self.device = device
+ self.cpu_loader_queue = kq.Queue(maxsize=loader_prefetch_size)
+ self.queue = kq.Queue(maxsize=device_prefetch_size)
+ self.close_queue_count = itertools.count()
+
+
+class PerDeviceLoader(object):
+
+ def __init__(self, loader, device):
+ self._loader = loader
+ self._device = device
+ self._mark_step_batch_count = loader.batches_per_execution - 1
+ self._batches_yielded = 0
+
+ def __iter__(self):
+ return self
+
+ def __next__(self):
+ return self.next()
+
+ def __len__(self):
+ return self._loader.per_device_samples()
+
+ def next(self):
+ if xp.get_tracer_marked_step():
+ xp.set_tracer_marked_step(False)
+ self._batches_yielded += 1
+ else:
+ if self._mark_step_batch_count <= self._batches_yielded:
+ self._batches_yielded = 0
+ xm.mark_step()
+ else:
+ self._batches_yielded += 1
+
+ item = self._loader.next_item(self._device)
+ if item is None:
+ if not self._loader._exception_queue.empty():
+ raise self._loader._exception_queue.get()
+ xm.mark_step()
+ raise StopIteration
+ return item
+
+
+class ParallelLoader(object):
+ """Wraps an existing PyTorch DataLoader with background data upload.
+
+ Args:
+ cpu_loader (:class:`torch.utils.data.DataLoader`): The PyTorch DataLoader to be
+ wrapped.
+ devices (`torch.device`...): The list of devices where the data has to be
+ sent. The i-th sample returned by the `loader` will be sent to `devices[i
+ % len(devices)]`.
+ batchdim (int, optional): The dimension which is holding the batch size.
+ Default: 0
+ loader_prefetch_size (int, optional): The max capacity of the queue used by
+ the thread which is reading samples from the `loader`, to be processed by
+ the worker threads which upload data to the devices.
+ Default: 16
+ device_prefetch_size (int, optional): The max size of the per-device queues,
+ where the worker threads deposit tensors which have already been sent to
+ devices.
+ Default: 8
+ host_to_device_transfer_threads (int, optional): The number of threads that
+ work in parallel to transfer data from loader queue to device queue.
+ Default: 1
+ input_sharding (ShardingSpec, Dict(str, ShardingSpec), optional): Sharding
+ spec to apply to compatible input tensors after loading.
+ Default: None
+ """
+
+ def __init__(self,
+ cpu_loader,
+ devices,
+ batchdim=0,
+ batches_per_execution=1,
+ loader_prefetch_size=16,
+ device_prefetch_size=8,
+ host_to_device_transfer_threads=1,
+ input_sharding=None):
+ self._cpu_loader = cpu_loader
+ self._devices = [torch.device(x) for x in devices]
+ self._batchdim = batchdim
+ self._batches_per_execution = batches_per_execution
+ self._done = False
+ self._queues = dict()
+ self._exception_queue = queue.Queue()
+ self._input_sharding = input_sharding
+ for device in self._devices:
+ self._queues[device] = PerDeviceQueue(device, loader_prefetch_size,
+ device_prefetch_size)
+ thread = threading.Thread(target=self._loader_worker)
+ thread.daemon = True
+ thread.start()
+ for dqueue in self._queues.values():
+ for i in range(host_to_device_transfer_threads):
+ thread = threading.Thread(
+ target=self._worker,
+ args=(
+ dqueue,
+ host_to_device_transfer_threads,
+ ))
+ thread.daemon = True
+ thread.start()
+
+ def per_device_loader(self, device):
+ """Retrieves the loader iterator object for the given device.
+
+ Args:
+ device (`torch.device`): The device whole loader is being requested.
+
+ Returns:
+ The loader iterator object for the `device`. This is not a
+ `torch.utils.data.DataLoader` interface, but a Python iterator which
+ returns the same tensor data structure as returned by the wrapped
+ `torch.utils.data.DataLoader`, but residing on XLA devices.
+ """
+ return PerDeviceLoader(self, torch.device(device))
+
+ def per_device_samples(self):
+ return len(self._loader) // len(self._devices)
+
+ def next_item(self, device):
+ dqueue = self._queues[device]
+ return dqueue.queue.get()
+
+ def close(self):
+ self._done = True
+ for dqueue in self._queues.values():
+ dqueue.queue.close()
+ dqueue.cpu_loader_queue.close()
+
+ @property
+ def batches_per_execution(self):
+ return self._batches_per_execution
+
+ def _loader_worker(self):
+ queues = list(self._queues.values())
+ data_iter = enumerate(self._cpu_loader)
+ batch = []
+ while not self._done:
+ try:
+ _, data = next(data_iter)
+ except StopIteration:
+ break
+ batch.append(data)
+ if len(batch) == len(self._devices):
+ for queue_no, device_batch in enumerate(batch):
+ queues[queue_no].cpu_loader_queue.put(device_batch)
+ batch = []
+ for dqueue in queues:
+ dqueue.cpu_loader_queue.close_write()
+
+ def _get_batch(self, dqueue):
+ batch = []
+ while len(batch) < dqueue.queue.max_size():
+ item = dqueue.cpu_loader_queue.get()
+ if item is None:
+ break
+ batch.append(item)
+ return batch
+
+ def send_cpu_data_to_device(self, batches, device):
+ """Move batch to device.
+ Args:
+ batch -> List(torch.Tensor), List(Dict(str: torch.Tensor)): Input batch
+ present in the cpu memory
+ device: TPU device where the batch should be moved
+
+ Returns:
+ result -> List(torch.Tensor), Dict(str: torch.Tensor): Returns a dict if the
+ input batch is a dict. Otherwise, returns a list of torch.Tensor.
+ """
+ result = None
+ if isinstance(self._input_sharding, dict):
+ if not isinstance(batches[0], dict):
+ raise ValueError(
+ f"input batch should be a dict when input sharding is a dict.")
+ result = []
+ for batch in batches:
+ xla_batch = {}
+ missing_keys = []
+ for key, tensor in batch.items():
+ assert type(tensor) == torch.Tensor
+ sharding_spec = None
+ if self._input_sharding:
+ if key not in self._input_sharding:
+ missing_keys.append(key)
+ continue
+ sharding_spec = self._input_sharding[key]
+
+ # xla_tensor is a list of tensors.
+ xla_tensor = xm.send_cpu_data_to_device(tensor, device, sharding_spec)
+ xla_batch[key] = xla_tensor[0]
+ if len(missing_keys) != 0:
+ # Returning exception as raising in the dataloading thread doesn't surface the problem in the main thread.
+ raise KeyError(
+ f"Keys: {missing_keys} are missing from input_sharding.")
+ result.append(xla_batch)
+ else:
+ result = xm.send_cpu_data_to_device(batches, device, self._input_sharding)
+ return result
+
+ def _worker(self, dqueue, host_to_device_transfer_threads):
+ device = torch.device(dqueue.device)
+ while True:
+ batch = self._get_batch(dqueue)
+ if not batch:
+ break
+ try:
+ batch = self.send_cpu_data_to_device(batch, device)
+ except Exception as e:
+ # _worker is being run in a daemon thread, raise the error
+ # will not work. Put the error in an error queue instead.
+ self._exception_queue.put(e)
+ break
+ for data in batch:
+ dqueue.queue.put(data)
+ close_queue_count = next(dqueue.close_queue_count)
+ if close_queue_count == host_to_device_transfer_threads - 1:
+ dqueue.queue.close_write()
+
+
+[docs]class MpDeviceLoader(object):
+ """Wraps an existing PyTorch DataLoader with background data upload.
+
+ This class should only be using with multi-processing data parallelism. It will wrap
+ the dataloader passed in with ParallelLoader and return the per_device_loader for the
+ current device.
+
+ Args:
+ loader (:class:`torch.utils.data.DataLoader`): The PyTorch DataLoader to be
+ wrapped.
+ device (`torch.device`...): The device where the data has to be sent.
+ kwargs: Named arguments for the `ParallelLoader` constructor.
+
+ Example:
+
+ >>> device = torch_xla.device()
+ >>> train_device_loader = MpDeviceLoader(train_loader, device)
+ """
+
+ def __init__(self, loader, device, **kwargs):
+ self._loader = loader
+ self._device = device
+ self._parallel_loader_kwargs = kwargs
+
+ def __iter__(self):
+ parallel_loader = ParallelLoader(self._loader, [self._device],
+ **self._parallel_loader_kwargs)
+ return parallel_loader.per_device_loader(self._device)
+
+ def __len__(self):
+ return len(self._loader)
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+To analyze traffic and optimize your experience, we serve cookies on this site. By clicking or navigating, you agree to allow our usage of cookies. As the current maintainers of this site, Facebook’s Cookies Policy applies. Learn more, including about available controls: Cookies Policy.
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+ torch_xla.distributed.xla_multiprocessing — PyTorch/XLA master documentation
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+ Source code for torch_xla.distributed.spmd.xla_sharding
+import os
+from collections import OrderedDict, defaultdict
+from dataclasses import dataclass, field
+import torch
+import torch_xla
+import torch_xla.core.xla_model as xm
+import torch_xla._internal.utils as _utils
+from torch_xla.distributed.spmd import XLAShardedTensor, XLAShard
+import torch_xla.runtime as xr
+
+import numpy as np
+import functools
+import itertools
+from typing import Tuple, Union, List, Sequence, Any, Optional, Set
+from enum import IntEnum
+
+
+[docs]class Mesh:
+ """Describe the logical XLA device topology mesh and the underlying resources.
+
+ Args:
+ device_ids (Union[np.ndarray, List]): A raveled list of devices (IDs) in a custom order. The list is reshaped
+ to an `mesh_shape` array, filling the elements using C-like index order.
+
+ mesh_shape (Tuple[int, ...]): A int tuple describing the logical topology shape
+ of the device mesh, and each element describes the number of devices in
+ the corresponding axis.
+
+ axis_names (Tuple[str, ...]): A sequence of resource axis names to be assigned to the dimensions
+ of the `devices` argument. Its length should match the rank of `devices`.
+
+ Example:
+
+ >>> mesh_shape = (4, 2)
+ >>> num_devices = len(xm.get_xla_supported_devices())
+ >>> device_ids = np.array(range(num_devices))
+ >>> mesh = Mesh(device_ids, mesh_shape, ('x', 'y'))
+ >>> mesh.get_logical_mesh()
+ >>> array([[0, 1],
+ [2, 3],
+ [4, 5],
+ [6, 7]])
+ >>> mesh.shape()
+ OrderedDict([('x', 4), ('y', 2)])
+ """
+
+ device_ids: np.ndarray
+ mesh_shape: Tuple[int, ...]
+ axis_names: Tuple[str, ...]
+
+ def __init__(self,
+ device_ids: Union[np.ndarray, List],
+ mesh_shape: Tuple[int, ...],
+ axis_names: Tuple[str, ...] = None):
+ if not isinstance(device_ids, np.ndarray):
+ device_ids = np.array(device_ids)
+ assert (axis_names is None) or (len(mesh_shape) == len(axis_names))
+ assert axis_names is None or (len(set(axis_names)) == len(axis_names))
+ assert (len(device_ids) == np.prod(mesh_shape))
+ assert len(device_ids) == len(np.unique(device_ids))
+ self.device_ids = device_ids
+ self.mesh_shape = mesh_shape
+ self.axis_names = axis_names
+ assert all(d < self.size() for d in device_ids)
+
+ def size(self):
+ return np.prod(self.mesh_shape)
+
+ def shape(self):
+ if self.axis_names is None:
+ return OrderedDict(
+ (dim, size) for dim, size in enumerate(self.mesh_shape))
+ return OrderedDict(
+ (name, size) for name, size in zip(self.axis_names, self.mesh_shape))
+
+ def get_logical_mesh(self):
+ return self.device_ids.reshape(self.mesh_shape)
+
+ def get_axis_name_idx(self, name: str) -> int:
+ if name not in self.axis_names:
+ return None
+ return self.axis_names.index(name)
+
+ @functools.lru_cache(maxsize=None)
+ def _get_op_sharding_args(self, partition_spec: Tuple):
+ partition_spec = _translate_named_partition_spec(self, partition_spec)
+ flat_specs = np.hstack([d for d in partition_spec])
+ specs = [d for d in flat_specs if d is not None]
+ assert all(d >= 0 and d < len(self.mesh_shape) for d in specs), \
+ f"partition_spec ({partition_spec}) contains out of bound index into mesh_shape."
+ assert len(specs) == len(np.unique(specs)), \
+ f"Each device mesh dimension should appear at most once in partition_spec {partition_spec}."
+
+ tile_assignment = _get_tile_assignment(self, partition_spec)
+ if len(tile_assignment.shape) > len(partition_spec):
+ # Use partial replication for sharding a tensor over a higher-rank mesh
+ sharding_type = ShardingType.PARTIAL
+ else:
+ sharding_type = _get_sharding_type(partition_spec, self.size())
+ replicate_dims = {i for i, d in enumerate(partition_spec) if d is None}
+ group_assignment, replication_groups = _get_group_assignment(
+ sharding_type, tile_assignment, len(partition_spec), replicate_dims)
+
+ tile_assignment = tile_assignment.tolist()
+ sharding_type = int(sharding_type)
+ return tile_assignment, group_assignment, replication_groups, sharding_type
+
+ @functools.lru_cache(maxsize=None)
+ def get_op_sharding(self,
+ partition_spec: Tuple) -> torch_xla._XLAC.OpSharding:
+ """
+ Return the OpSharding for the given partition spec. This is an expensive
+ operation as the mesh grows, so the value is cached for reuse.
+ """
+ # For scalar tensors, it can only be replicated.
+ # We have made sure len(t.shape) == len(partition_spec)
+ # in mark_sharding API.
+ if len(partition_spec) == 0:
+ return torch_xla._XLAC.OpSharding([], [], [], ShardingType.REPLICATED)
+
+ tile_assignment, group_assignment, replication_groups, sharding_type = self._get_op_sharding_args(
+ partition_spec)
+ return torch_xla._XLAC.OpSharding(tile_assignment, group_assignment,
+ replication_groups, sharding_type)
+
+
+_GLOBAL_MESH: Mesh = None
+
+
+[docs]def set_global_mesh(mesh: Mesh):
+ """
+ Set the global mesh that can be used for the current process.
+
+ Args:
+ mesh: (Mesh) Mesh object that will be the global mesh.
+
+ Example:
+
+ >>> import torch_xla.distributed.spmd as xs
+ >>> mesh = xs.get_1d_mesh("data")
+ >>> xs.set_global_mesh(mesh)
+ """
+ global _GLOBAL_MESH
+ _GLOBAL_MESH = mesh
+
+
+[docs]def get_global_mesh() -> Optional[Mesh]:
+ """
+ Get the global mesh for the current process.
+
+ Returns:
+ mesh: (Optional[Mesh]) Mesh object if global mesh is set, otherwise return None.
+
+ Example:
+
+ >>> import torch_xla.distributed.spmd as xs
+ >>> xs.get_global_mesh()
+ """
+ global _GLOBAL_MESH
+ return _GLOBAL_MESH
+
+
+[docs]def get_1d_mesh(axis_name: Optional[str] = None) -> Mesh:
+ """
+ Helper function to return the mesh with all devices in one dimension.
+
+ Args:
+ axis_name: (Optional[str]) optional string to represent the axis name of the mesh
+
+ Returns:
+ Mesh: Mesh object
+
+ Example:
+
+ >>> # This example is assuming 1 TPU v4-8
+ >>> import torch_xla.distributed.spmd as xs
+ >>> mesh = xs.get_1d_mesh("data")
+ >>> print(mesh.mesh_shape)
+ (4,)
+ >>> print(mesh.axis_names)
+ ('data',)
+ """
+ num_devices = xr.global_runtime_device_count()
+ mesh_shape = (num_devices,)
+ device_ids = np.array(range(num_devices))
+ if axis_name == None:
+ return Mesh(device_ids, mesh_shape)
+ else:
+ return Mesh(device_ids, mesh_shape, (axis_name,))
+
+
+# HybridDevice class has been inspired from jax's mesh_utils: https://github.com/google/jax/blob/fc5960f2b8b7a0ef74dbae4e27c5c08ff1564cff/jax/experimental/mesh_utils.py#L4ƒ
+[docs]class HybridMesh(Mesh):
+ """Creates a hybrid device mesh of devices connected with ICI and DCN networks.
+ The shape of logical mesh should be ordered by increasing network-intensity
+ e.g. [replica, data, model] where mdl has the most network communication
+ requirements.
+
+ Args:
+ ici_mesh_shape: shape of the logical mesh for inner connected devices.
+ dcn_mesh_shape: shape of logical mesh for outer connected devices.
+
+ Example:
+
+ >>> # This example is assuming 2 slices of v4-8.
+ >>> ici_mesh_shape = (1, 4, 1) # (data, fsdp, tensor)
+ >>> dcn_mesh_shape = (2, 1, 1)
+ >>> mesh = HybridMesh(ici_mesh_shape, dcn_mesh_shape, ('data','fsdp','tensor'))
+ >>> print(mesh.shape())
+ >>> >> OrderedDict([('data', 2), ('fsdp', 4), ('tensor', 1)])
+ """
+ ici_mesh_shape: Tuple[int, ...]
+ dcn_mesh_shape: Tuple[int, ...]
+
+ def __init__(self,
+ *,
+ ici_mesh_shape: Tuple[int, ...],
+ dcn_mesh_shape: Tuple[int, ...] = None,
+ axis_names: Tuple[str, ...] = None):
+ if dcn_mesh_shape == None:
+ dcn_mesh_shape = tuple([1] * len(ici_mesh_shape))
+ assert len(ici_mesh_shape) == len(dcn_mesh_shape)
+ mesh_shape = tuple([x * y for x, y in zip(ici_mesh_shape, dcn_mesh_shape)])
+ self.device_attributes = xr.global_runtime_device_attributes()
+ self.device_attributes.sort(
+ key=lambda attr: _utils.parse_xla_device(attr['name'])[1])
+
+ if 'slice_index' in self.device_attributes[0] and np.prod(
+ dcn_mesh_shape) == 1:
+ raise ValueError('Provide dcn_mesh_shape to create a mesh for multislice')
+ if 'slice_index' not in self.device_attributes[0] and np.prod(
+ dcn_mesh_shape) > 1:
+ raise ValueError('Invalid dcn_mesh_shape for single slice mesh')
+ self.ici_mesh_shape = ici_mesh_shape
+ self.dcn_mesh_shape = dcn_mesh_shape
+ if np.prod(dcn_mesh_shape) > 1 and 'slice_index' in self.device_attributes[
+ 0]: # multislice
+ mesh = self._create_hybrid_device_mesh(self.ici_mesh_shape,
+ self.dcn_mesh_shape)
+ else:
+ mesh = self._create_device_mesh(self.ici_mesh_shape)
+ device_ids = mesh.flatten()
+ super().__init__(device_ids, mesh_shape, axis_names)
+
+ # This is imported from JAX: https://github.com/google/jax/blob/main/jax/experimental/mesh_utils.py#L172
+ def _get_physical_tpu_mesh(self, devices: Sequence[int]) -> np.ndarray:
+ r"""Rearrange TPU devices in a slice into a physical mesh.
+
+ Args:
+ devices: A list of device logical ordinals in a TPU slice.
+
+ Returns:
+ A np.ndarray of device logical ordinals with shape [global_x, global_y, global_z]. On
+ v2 and v3, global_z is instead cores_per_chip (i.e., 2).
+ """
+ assert xm.xla_device_hw(xm.xla_device()) == 'TPU'
+ # coords is a 3-dims tuple representing the device in physical mesh
+ device_coords = [self.device_attributes[d]['coords'] for d in devices]
+ dims = tuple(d + 1 for d in max(device_coords))
+ out = np.empty(dims, dtype=int)
+ for coords, d in zip(device_coords, devices):
+ out[coords[0], coords[1], coords[2]] = d
+ return out
+
+ # This is imported from JAX: https://github.com/google/jax/blob/main/jax/experimental/mesh_utils.py#L64.
+ def _create_device_mesh_for_nd_torus(
+ self, physical_mesh: np.ndarray,
+ mesh_shape: Sequence[int]) -> Tuple[np.ndarray, List[Tuple[int, ...]]]:
+ """Assigns logical parallelism axes to physical axes of an N-D torus network.
+
+ Given logical parallelism axes with sizes in `mesh_shape` and devices in an
+ N-dimensional torus network represented by `physical_mesh`, maps each logical
+ axis to one or more physical axes. Prefer to map more-performance-sensitive
+ logical axes to larger numbers of physical axes to maximize the bandwidth
+ available to them. Also prefer to assign logical axes to multiple physical
+ axes of the same size (e.g., a 2D square) rather than multiple physical axes
+ of different sizes when possible.
+
+ Note that this routine will never split a physical axis over more than one
+ logical axis (which would reduce total usable bandwidth but may sometimes be
+ desired anyway). As a result, it will error out in cases where this is
+ necessary to produce a valid mapping.
+
+ Let's use a concrete example to explain the concepts and considerations.
+
+ As an example, suppose the logical mesh is [data, model], for data and model
+ parallelism respectively. Also suppose that data parallelism is less
+ performance sensitive than model parallelism. Consider a 3D TPU pod slice of
+ shape 4x4x16, represented by a physical mesh of shape (4, 4, 16).
+
+ A TPU pod slice has equal bandwidth along all axes with wraparound links, but
+ a 2D plane of size 4x4 may have faster XLA collective implementations than a
+ non-square plane or a 1D subgroup. If the mesh_shape is [16, 16], we may want
+ the more performance sensitive `model` axis to be mapped to the 4x4 XY plane.
+
+ Args:
+ physical_mesh: a np.ndarray of devices in the shape of the N-D torus
+ physical topology.
+ mesh_shape: shape of the logical mesh (size of the various logical
+ parallelism axes), with axes ordered by increasing network intensity.
+
+ Returns:
+ An np.ndarray of devices in the shape of the logical mesh (mesh_shape), with
+ each logical parallelism axis mapped to one or more physical mesh axes.
+ The axis assignment (a list of length num_logical_axes, whose elements
+ are tuples representing physical axis indices).
+ """
+ # Remaining physical axes to be assigned to logical axes.
+ assignable_physical_mesh = list(physical_mesh.shape)
+ # Map each logical axis to a subset of physical axes.
+ assignment: List[Tuple[int, ...]] = [() for _ in mesh_shape]
+ # Assign logical axes from highest network intensity to lowest.
+ # `mesh_shape` is assumed to ordered by lowest network intensity first, so
+ # reverse it first.
+ # Assigns devices to 2D or 3D logical mesh.
+ for logical_axis_index, logical_axis_size in reversed(
+ list(enumerate(mesh_shape))):
+ for num_axes in range(3, 0, -1):
+ # map a combination of devices in physical axes to the logical axis.
+ axes = itertools.combinations(assignable_physical_mesh, num_axes)
+ indices = itertools.combinations(
+ range(len(assignable_physical_mesh)), num_axes)
+ for c_axes, c_indices in zip(axes, indices):
+ if np.prod(c_axes) == logical_axis_size:
+ assignment[logical_axis_index] = c_indices
+ # Zero the assigned physical axes.
+ assignable_physical_mesh = [
+ 0 if i in c_indices else v
+ for i, v in enumerate(assignable_physical_mesh)
+ ]
+ break
+ if assignment[logical_axis_index]:
+ # We already found an assignment from one candidate above.
+ break
+ else:
+ # If the num_axes for loop did not break, i.e. none of the candidates work
+ # goto here with this while-else construct.
+ if logical_axis_size > 1:
+ raise NotImplementedError(
+ 'Failed to find assignment for logical_axis_index'
+ f' {logical_axis_index} of size {logical_axis_size} with remaining'
+ f' assignable mesh {assignable_physical_mesh}. The size of each'
+ ' axis in your logical mesh must be equal to the product of'
+ ' some subset of the physical mesh axis sizes. E.g logical mesh (4,'
+ ' 16) is compatible with physical mesh 4x4x4 since 4=4 and 16=4x4.'
+ )
+ # Flatten the assignment
+ transpose: List[int] = []
+ for x in assignment:
+ for y in x:
+ transpose.append(int(y))
+ return physical_mesh.transpose(transpose).reshape(mesh_shape), assignment
+
+ def _create_device_mesh(self,
+ mesh_shape: Sequence[int],
+ devices: Sequence[Any] = None) -> Sequence[int]:
+ """Creates a performant device mesh.
+
+ Args:
+ mesh_shape: shape of logical mesh, ordered by increasing network-intensity
+ e.g. [replica, data, mdl] where mdl has the most network communication
+ requirements.
+ devices: optionally, the devices to construct a mesh for.
+
+ Returns:
+ A np.ndarray of devices with mesh_shape as its shape.
+ """
+
+ if devices is None:
+ devices = np.arange(xr.global_runtime_device_count())
+ if np.prod(mesh_shape) != len(devices):
+ raise ValueError(
+ f'Number of devices {len(devices)} must equal the product '
+ f'of mesh_shape {mesh_shape}')
+ physical_mesh = self._get_physical_tpu_mesh(devices)
+ device_mesh, assignment = self._create_device_mesh_for_nd_torus(
+ physical_mesh, mesh_shape)
+ return device_mesh
+
+ # This is imported from JAX: https://github.com/google/jax/blob/main/jax/experimental/mesh_utils.py#L288.
+ def _create_hybrid_device_mesh(
+ self, ici_mesh_shape: Sequence[int],
+ dcn_mesh_shape: Sequence[int]) -> Sequence[int]:
+ """Creates a device mesh for hybrid (e.g., ICI and DCN) parallelism.
+
+ Args:
+ ici_mesh_shape: shape of the logical mesh for the faster/inner network, ordered
+ by increasing network intensity, e.g. [replica, data, mdl] where mdl has
+ the most network communication requirements.
+ dcn_mesh_shape: shape of the logical mesh for the slower/outer network,
+ in the same order as mesh_shape.
+
+ Returns:
+ A np.ndarray of device logical ordinal with ici_mesh_shape * dcn_mesh_shape as its shape
+ that can be fed into HybridMesh for hybrid parallelism.
+ """
+ granule_dict = defaultdict(list)
+ for d, dev in enumerate(self.device_attributes):
+ granule_dict[dev['slice_index']].append(d)
+ # sorts devices based on slice_index.
+ granules = list(granule_dict[key] for key in sorted(granule_dict.keys()))
+ if np.prod(dcn_mesh_shape) != len(granules):
+ raise ValueError(
+ f'Number of slices {len(granules)} must equal the product of '
+ f'dcn_mesh_shape {dcn_mesh_shape}')
+ # creates a seperate internal mesh for each slice.
+ per_granule_meshes = [
+ self._create_device_mesh(ici_mesh_shape, granule)
+ for granule in granules
+ ]
+ granule_mesh = np.arange(len(granules)).reshape(dcn_mesh_shape)
+ blocks = np.vectorize(
+ lambda i: per_granule_meshes[i], otypes=[object])(
+ granule_mesh)
+ device_mesh = np.block(blocks.tolist())
+ return device_mesh
+
+
+class ShardingType(IntEnum):
+ # ShardingType enum ID maps to OpSharidng.Type (https://shorturl.at/pvAJX)
+ REPLICATED = 0
+ MAXIMAL = 1
+ TUPLE = 2
+ TILED = 3
+ MANUAL = 4
+ PARTIAL = 5
+ UNKNOWN = 6 # implicit replication. TODO(yeounoh) wait for auto-sharding support
+
+
+def _get_sharding_type(partition_spec: Tuple[Union[int, None]],
+ num_devices: int) -> ShardingType:
+ sharding_type = ShardingType.TILED
+ if num_devices == 1:
+ sharding_type = ShardingType.MAXIMAL
+ elif all(d is None for d in partition_spec):
+ sharding_type = ShardingType.REPLICATED
+ elif any(d is None for d in partition_spec):
+ sharding_type = ShardingType.PARTIAL
+ return sharding_type
+
+
+def _get_tile_assignment(
+ mesh: Mesh, partition_spec: Tuple[Union[Tuple[int], int,
+ None]]) -> np.ndarray:
+ """
+ Permute the given mesh to create the tile assignment based on the partition
+ spec. Returns the tiling assignment as a numpy ndarray.
+
+ If the input partition_spec combines multiple logical mesh axes over a single
+ tensor axis, the resulting tiling assignment will combine the specified axes
+ into a single axis.
+ """
+ # Flatten the partition spec and ensure that it is fully specified over the
+ # mesh for permutation.
+ tiled_dims = [x for x in partition_spec if x is not None]
+ permutation = np.hstack(tiled_dims).tolist() if tiled_dims else []
+ missing_axes = sorted(set(range(len(mesh.shape()))) - set(permutation))
+ tile_assignment = mesh.get_logical_mesh().transpose(permutation +
+ missing_axes)
+
+ # For any tuples in the partition_spec, the grouped axes will be adjacent
+ # after the permutation. Combine these dimensions into a single axis.
+ for i, spec in enumerate(tiled_dims):
+ if isinstance(spec, tuple):
+ shape = tile_assignment.shape
+ tile_assignment = tile_assignment.reshape(shape[:i] + (-1,) +
+ shape[i + len(spec):])
+
+ return tile_assignment
+
+
+# Produce group assignment for partial replication. Partial replication tiles
+# groups (a.k.a. sub-groups) where the shards are fully replicated within each
+# sub-group. `replication_groups` is a list of groups as lists, where each group
+# contains the participating device IDs. `group_assignment` describes the group
+# placement and the overall mesh, where each element is the group ID.
+# The tile_assignment should be the result of `_get_tile_assignment` so that all
+# tiled dimensions are in the first axes and replicated dimensions are in the
+# remaining axes.
+def _get_group_assignment(sharding_type: ShardingType,
+ tile_assignment: np.ndarray, tensor_rank: int,
+ replicate_dims: Set[int]) -> Tuple[List, List]:
+ group_assignment = list()
+ replication_groups = list()
+ if sharding_type is ShardingType.PARTIAL:
+ # Shard across groups and replicate within subgroups; replicated dims
+ # will be used to group replication devices.
+ tile_shape = tile_assignment.shape
+ # When creating the tile assignment, the mesh is permuted so that the first
+ # few axes are used for tiling.
+ tile_dims = range(tensor_rank - len(replicate_dims))
+ group_list = [tile_assignment]
+ for d in tile_dims:
+ _group_list = list()
+ for group_members in group_list:
+ _group_list += np.split(group_members, tile_shape[d], d)
+ group_list = _group_list
+ replication_groups = [group.flatten().tolist() for group in group_list]
+
+ mesh_axis = itertools.count()
+ group_tile_shape = [
+ 1 if d in replicate_dims else tile_shape[next(mesh_axis)]
+ for d in range(tensor_rank)
+ ]
+ group_assignment = np.arange(len(replication_groups)).reshape(
+ tuple(group_tile_shape)).tolist()
+ return group_assignment, replication_groups
+
+
+def _translate_named_partition_spec(mesh: Mesh, partition_spec: Tuple):
+ _partition_spec = list()
+ for p in partition_spec:
+ if type(p) is tuple:
+ assert not any(type(x) is tuple
+ for x in p), 'Partition spec cannot contain nested tuples'
+ _partition_spec.append(_translate_named_partition_spec(mesh, p))
+ elif (p is None) or (type(p) is int):
+ _partition_spec.append(p)
+ elif type(p) is str:
+ idx = mesh.get_axis_name_idx(p)
+ if idx is None:
+ raise ValueError(f"Axis name {p} is not defined in the given mesh")
+ _partition_spec.append(idx)
+ else:
+ raise ValueError(
+ f"Spec type {type(p)} is not supported in partition spec")
+ return tuple(_partition_spec)
+
+
+def _mark_manual_sharding(
+ t: Union[torch.Tensor, XLAShardedTensor]) -> XLAShardedTensor:
+ """
+ This API is meant to be paired with the upcoming pause_spmd&resume_spmd APIs.
+ Don't use it alone.
+ """
+ manual_sharding = torch_xla._XLAC.OpSharding([], [], [], ShardingType.MANUAL)
+ torch_xla._XLAC._mark_manual_sharding(
+ unwrap_sharded_tensor(t), manual_sharding)
+ return wrap_as_sharded_tensor(t)
+
+
+def enable_manual_sharding(t: Union[torch.Tensor, XLAShardedTensor],
+ partition_spec: Tuple[Union[Tuple, int, str, None]],
+ *,
+ mesh: Mesh = None) -> XLAShardedTensor:
+ """
+ This API enables manual sharding for the given tensor. Manual sharding disables SPMD sharding proporgation and auto
+ partition for the given tensor and all subsequential tensors that produced by an op that uses the given tensor as
+ input, and therefore allows the user to manually call collectives for the tensor and subsequential tensors. It
+ requires the user to provide the partition spec to shard the tensor before enabling the manual sharding. To be noted,
+ the leaf tensors need to pass to disable_manual_sharding before ending the graph.
+ """
+ mesh = get_global_mesh() if mesh is None else mesh
+ t = mark_sharding(unwrap_sharded_tensor(t), mesh, partition_spec)
+ t = torch_xla._XLAC._spmd_full_to_shard_shape(unwrap_sharded_tensor(t))
+ return wrap_as_sharded_tensor(t)
+
+
+def disable_manual_sharding(t: Union[torch.Tensor, XLAShardedTensor],
+ partition_spec: Tuple[Union[Tuple, int, str, None]],
+ full_shape: torch.Size,
+ *,
+ mesh: Mesh = None) -> XLAShardedTensor:
+ """
+ This API disables manual sharding for the given tensor. The partition_spec and full_shape are used to construct the
+ output tensor as if the input tensor has not been manual sharded.
+ """
+ mesh = get_global_mesh() if mesh is None else mesh
+ t = _mark_manual_sharding(unwrap_sharded_tensor(t))
+ t = torch_xla._XLAC._spmd_shard_to_full_shape(
+ unwrap_sharded_tensor(t), mesh.get_op_sharding(partition_spec),
+ full_shape, t.dtype)
+ return wrap_as_sharded_tensor(t)
+
+
+[docs]def mark_sharding(
+ t: Union[torch.Tensor, XLAShardedTensor], mesh: Mesh,
+ partition_spec: Tuple[Union[Tuple, int, str, None]]) -> XLAShardedTensor:
+ """
+ Annotates the tensor provided with XLA partition spec. Internally,
+ it annotates the corresponding XLATensor as sharded for the XLA SpmdPartitioner pass.
+
+ Args:
+ t (Union[torch.Tensor, XLAShardedTensor]): input tensor to be annotated with partition_spec.
+
+ mesh (Mesh): describes the logical XLA device topology and the underlying device IDs.
+
+ partition_spec (Tuple[Tuple, int, str, None]): A tuple of device_mesh dimension index or
+ `None`. Each index is an int, str if the mesh axis is named, or tuple of int or str.
+ This specifies how each input rank is sharded (index to mesh_shape) or replicated (None).
+ When a tuple is specified, the corresponding input tensor axis will be sharded along all
+ logical axes in the tuple. Note that the order the mesh axes are specified in the tuple
+ will impact the resulting sharding.
+
+ dynamo_custom_op (bool): if set to True, it calls the dynamo custom op variant of mark_sharding
+ to make itself recognizeable and traceable by dynamo.
+
+ Example:
+
+ >>> import torch_xla.runtime as xr
+ >>> import torch_xla.distributed.spmd as xs
+ >>> mesh_shape = (4, 2)
+ >>> num_devices = xr.global_runtime_device_count()
+ >>> device_ids = np.array(range(num_devices))
+ >>> mesh = Mesh(device_ids, mesh_shape, ('x', 'y'))
+ >>> input = torch.randn(8, 32).to(xm.xla_device())
+ >>> xs.mark_sharding(input, mesh, (0, None)) # 4-way data parallel
+ >>> linear = nn.Linear(32, 10).to(xm.xla_device())
+ >>> xs.mark_sharding(linear.weight, mesh, (None, 1)) # 2-way model parallel
+ """
+ num_devices = xr.global_runtime_device_count()
+ assert num_devices > 0, "This requires XLA supported device(s)."
+ assert mesh.size() == num_devices, \
+ f"{mesh.mesh_shape} is not mappable over {num_devices} devices."
+ # We only allow fully specified `partition_spec` to be applicable, as opposed
+ # to filling in the unspecified replicated dims. Fully specified `partiion_spec`
+ # should be of the same rank as `t`. This is to support partial replication
+ # where the group assignment may vary with different input ranks.
+ assert len(t.shape) == len(partition_spec), \
+ f"Partition spec length ({len(partition_spec)}) should be equal to the input rank ({len(t.shape)})."
+
+ op_sharding = mesh.get_op_sharding(partition_spec)
+ annotate_func = torch_xla._XLAC._xla_mark_sharding
+ annotate_func(unwrap_sharded_tensor(t), op_sharding)
+ return wrap_as_sharded_tensor(t)
+
+
+[docs]def clear_sharding(t: Union[torch.Tensor, XLAShardedTensor]) -> torch.Tensor:
+ """
+ Clear sharding annotation from the input tensor and return a `cpu` casted tensor. This
+ is a in place operation but will also return the same torch.Tensor back.
+
+ Args:
+ t (Union[torch.Tensor, XLAShardedTensor]): Tensor that we want to clear the sharding
+
+ Return:
+ t (torch.Tensor): tensor that without sharding.
+
+ Example:
+
+ >>> import torch_xla.distributed.spmd as xs
+ >>> torch_xla.runtime.use_spmd()
+ >>> t1 = torch.randn(8,8).to(torch_xla.device())
+ >>> mesh = xs.get_1d_mesh()
+ >>> xs.mark_sharding(t1, mesh, (0, None))
+ >>> xs.clear_sharding(t1)
+ """
+ torch_xla._XLAC._xla_clear_sharding(unwrap_sharded_tensor(t))
+ if isinstance(t, XLAShardedTensor):
+ return t.global_tensor
+ return t
+
+
+def wrap_as_sharded_tensor(
+ t: Union[torch.Tensor, XLAShardedTensor]) -> XLAShardedTensor:
+ if not isinstance(t, XLAShardedTensor):
+ return XLAShardedTensor(t)
+ return t
+
+
+def unwrap_sharded_tensor(
+ t: Union[torch.Tensor, XLAShardedTensor]) -> torch.Tensor:
+ if isinstance(t, XLAShardedTensor):
+ return t.global_tensor
+ return t
+
+
+def wrap_if_sharded(x: Any) -> Any:
+ """
+ If the input is a sharded tensor, return an XLAShardedTensor wrapping it.
+ Otherwise, returns the input.
+ """
+ if (isinstance(x, torch.Tensor) and not isinstance(x, XLAShardedTensor) and
+ x.device.type == 'xla' and
+ torch_xla._XLAC._get_xla_sharding_type(x) is not None):
+ return XLAShardedTensor(x)
+ return x
+
+
+@dataclass
+class ShardingSpec:
+ mesh: Mesh
+ partition_spec: Tuple[Union[int, None]]
+ minibatch: Optional[bool] = False
+
+ # Derived fields
+ _tile_assignment: List[int] = field(init=False)
+ _group_assignment: List[int] = field(init=False)
+ _replication_groups: List[int] = field(init=False)
+ _sharding_type: ShardingType = field(init=False)
+
+ def __post_init__(self):
+ mesh = self.mesh
+ partition_spec = _translate_named_partition_spec(mesh, self.partition_spec)
+ tile_assignment = _get_tile_assignment(mesh, partition_spec)
+ self._tile_assignment = tile_assignment.tolist()
+ self._sharding_type = _get_sharding_type(partition_spec,
+ xr.global_runtime_device_count())
+ replicate_dims = {i for i, d in enumerate(partition_spec) if d is None}
+ self._group_assignment, self._replication_groups = _get_group_assignment(
+ self._sharding_type, tile_assignment, len(partition_spec),
+ replicate_dims)
+
+ def xla_spec(self, t: torch.Tensor) -> Union['XlaShardingSpec', None]:
+ """
+ Create an XlaShardingSpec for the given tensor. If the tensor is
+ incompatible with the ShardingSpec, returns None.
+ """
+ if not self.can_apply(t):
+ return None
+ return torch_xla._XLAC.XlaShardingSpec(t, self._tile_assignment,
+ self._group_assignment,
+ self._replication_groups,
+ int(self._sharding_type),
+ self.minibatch)
+
+ def can_apply(self, t: torch.Tensor) -> bool:
+ """
+ Test whether the ShardingSpec is compatible with the given torch.Tensor.
+ """
+ return len(t.shape) == len(self.partition_spec)
+
+ def apply(self, t: torch.Tensor):
+ # TODO(yeounoh) use virtual device interface when available.
+ assert (t.device == xm.xla_device())
+ mark_sharding(t, self.mesh, self.partition_spec)
+
+
+class XLAPatchedLinear(torch.autograd.Function):
+ """
+ A patched version of `torch.nn.functional.linear` that uses einsum instead
+ of torch.matmul which will flatten the tensors to 2D and collide the sharded
+ dimensions. The torch.matmul default behavior makes it very hard for XLA compiler
+ to propagate the sharding annotation.
+
+ TODO (alanwaketan): Let's patch it on the dispatcher level.
+ """
+
+ @staticmethod
+ def forward(ctx, input, weight, bias=None):
+ # bias is an optional argument
+ ctx.save_for_backward(input, weight, bias)
+ with torch.no_grad():
+ product = torch.einsum('...n,mn->...m', input, weight)
+ if bias is None:
+ return product
+ return product + bias
+
+ @staticmethod
+ def backward(ctx, grad_output):
+ input, weight, bias = ctx.saved_tensors
+ grad_input = grad_weight = grad_bias = None
+
+ if ctx.needs_input_grad[0]:
+ grad_input = torch.einsum('...m,mn->...n', grad_output, weight)
+ if ctx.needs_input_grad[1]:
+ grad_weight = torch.einsum('...m,...n->mn', grad_output, input)
+ if bias is not None and ctx.needs_input_grad[2]:
+ grad_bias = torch.einsum('...m->m', grad_output)
+
+ return grad_input, grad_weight, grad_bias
+
+
+def xla_patched_nn_linear_forward(m, input):
+ return XLAPatchedLinear.apply(input, m.weight, m.bias)
+
+
+def apply_backward_optimization_barrier(m: torch.nn.Module):
+ """
+ Register a full backward hook that apply an optimization barrier to the given module.
+ This will prevent the XLA compiler from fusing the module's backward pass with others.
+ It's useful to prevent gigantic buffers being allocated to synchronize the gradients.
+ """
+
+ def optimization_barrier(module, grad_input, grad_output):
+ from torch_xla.utils.checkpoint import CheckpointFunction
+ gradients = []
+ for param in module.parameters():
+ if param.grad != None:
+ gradients.append(param.grad)
+ xm.optimization_barrier_(
+ CheckpointFunction._extract_tensors_from_list(gradients +
+ list(grad_input)))
+
+ m.register_full_backward_hook(optimization_barrier)
+
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diff --git a/release/2.5/_modules/torch_xla/distributed/xla_multiprocessing.html b/release/2.5/_modules/torch_xla/distributed/xla_multiprocessing.html
new file mode 100644
index 00000000000..5e1cd5f551e
--- /dev/null
+++ b/release/2.5/_modules/torch_xla/distributed/xla_multiprocessing.html
@@ -0,0 +1,825 @@
+
+
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+
+
+
+
+
+
+
+
+
+ 
+
+To analyze traffic and optimize your experience, we serve cookies on this site. By clicking or navigating, you agree to allow our usage of cookies. As the current maintainers of this site, Facebook’s Cookies Policy applies. Learn more, including about available controls: Cookies Policy.
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ torch_xla.experimental.eager — PyTorch/XLA master documentation
+
+
+
+
+
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+
+ Source code for torch_xla.distributed.xla_multiprocessing
+import torch.multiprocessing
+from torch_xla import runtime as xr
+from torch_xla._internal import pjrt
+
+
+[docs]def spawn(fn,
+ args=(),
+ nprocs=None,
+ join=True,
+ daemon=False,
+ start_method='spawn'):
+ """Enables multi processing based replication.
+
+ Args:
+ fn (callable): The function to be called for each device which takes part of
+ the replication. The function will be called with a first argument being
+ the global index of the process within the replication, followed by the
+ arguments passed in `args`.
+ args (tuple): The arguments for `fn`.
+ Default: Empty tuple
+ nprocs (int): The number of processes/devices for the replication. At the
+ moment, if specified, can be either 1 or the maximum number of devices.
+ join (bool): Whether the call should block waiting for the completion of the
+ processes which have being spawned.
+ Default: True
+ daemon (bool): Whether the processes being spawned should have the `daemon`
+ flag set (see Python multi-processing API).
+ Default: False
+ start_method (string): The Python `multiprocessing` process creation method.
+ Default: `spawn`
+
+ Returns:
+ The same object returned by the `torch.multiprocessing.spawn` API. If
+ `nprocs` is 1 the `fn` function will be called directly, and the API will
+ return None.
+ """
+ return pjrt.spawn(fn, nprocs, start_method, args)
+
+
+class MpModelWrapper(object):
+ """Wraps a model to minimize host memory usage when `fork` method is used.
+
+ This class should be used together with the `spawn(..., start_method='fork')`
+ API to minimize the use of host memory.
+ Instead of creating models on each multiprocessing process, hence replicating
+ the model's initial host memory, the model is created once at global scope,
+ and then moved into each device inside the `spawn()` target function.
+ Example::
+
+ WRAPPED_MODEL = xmp.MpModelWrapper(MyNetwork())
+
+ def _mp_fn(index, ...):
+ device = xm.xla_device()
+ model = WRAPPED_MODEL.to(device)
+ ...
+
+ torch_xla.launch(_mp_fn, ..., start_method='fork')
+
+ This method has two advantages. First it uses only one copy of the memory
+ pages to host the original model weights, and second it serializes the move
+ of the wrapped model into each device, by lowering the load onto the system
+ memory during the process.
+ """
+
+ def __init__(self, model):
+ """Creates a new `MpModelWrapper` object.
+
+ Args:
+ model (torch.nn.Module): The model to be wrapped. Should be on PyTorch CPU
+ device (which is the default when creating new models).
+ """
+ self._model = model
+ self._lock = torch.multiprocessing.Lock()
+
+ def to(self, device):
+ """Retrieves the model moved onto the specified device.
+
+ Args:
+ device (torch.device): The device where the model should be moved onto.
+ Returns:
+ The model on the specified device.
+ """
+ with self._lock:
+ self._model.to(device)
+ return self._model
+
+
+class MpSerialExecutor(object):
+ """Utility to run a function in a serialized fashion among multi-core processes.
+
+ Example::
+
+ # At global scope.
+ SERIAL_EXEC = xmp.MpSerialExecutor()
+
+ def load_dataset(path):
+ return maybe_download_and_load(path)
+
+ def _mp_fn(index, ...):
+ # Avoid all cores downloading the same data with the serial executor.
+ dataset = SERIAL_EXEC.run(lambda: load_dataset('/tmp/mnist-data'))
+ ...
+
+ torch_xla.launch(_mp_fn, ...)
+ """
+
+ def __init__(self):
+ self._lock = torch.multiprocessing.Lock()
+
+ def run(self, fn):
+ """Runs the provided function serialized WRT each per-core process.
+
+ Args:
+ fn (callable): The function to run in a serialized fashion.
+ Returns:
+ The `fn` return value.
+ """
+ with self._lock:
+ return fn()
+
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diff --git a/release/2.5/_modules/torch_xla/experimental/eager.html b/release/2.5/_modules/torch_xla/experimental/eager.html
new file mode 100644
index 00000000000..93583db3b15
--- /dev/null
+++ b/release/2.5/_modules/torch_xla/experimental/eager.html
@@ -0,0 +1,746 @@
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+To analyze traffic and optimize your experience, we serve cookies on this site. By clicking or navigating, you agree to allow our usage of cookies. As the current maintainers of this site, Facebook’s Cookies Policy applies. Learn more, including about available controls: Cookies Policy.
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ torch_xla.runtime — PyTorch/XLA master documentation
+
+
+
+
+
+
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+
+ Source code for torch_xla.experimental.eager
+import functools
+from contextlib import contextmanager
+
+import torch_xla
+import logging
+
+
+[docs]def eager_mode(enable: bool):
+ """Configure torch_xla's default executation mode.
+
+ Under eager mode only functions that was `torch_xla.compile`d will be
+ traced and compiled. Other torch ops will be executed eagerly.
+ """
+ torch_xla._XLAC._set_use_eager_mode(enable)
+
+
+def is_eager_mode() -> bool:
+ """Return True if torch_xla is currently under eager mode
+ """
+ return torch_xla._XLAC._get_use_eager_mode()
+
+
+@contextmanager
+def eager_mode_context(enable: bool):
+ """Context manager to enable/disable the eager mode.
+ """
+ saved_eager_mode = is_eager_mode()
+ eager_mode(enable)
+ try:
+ yield saved_eager_mode
+ finally:
+ eager_mode(saved_eager_mode)
+
+
+def compile(func):
+ # can's use deprecated wrapper at import time due to circular dependency
+ logging.warning(
+ 'torch_xla.experimental.compile is deprecated. Use torch_xla.compile instead.'
+ )
+ return torch_xla.compile(func)
+
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diff --git a/release/2.5/_modules/torch_xla/runtime.html b/release/2.5/_modules/torch_xla/runtime.html
new file mode 100644
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+To analyze traffic and optimize your experience, we serve cookies on this site. By clicking or navigating, you agree to allow our usage of cookies. As the current maintainers of this site, Facebook’s Cookies Policy applies. Learn more, including about available controls: Cookies Policy.
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+ torch_xla.torch_xla — PyTorch/XLA master documentation
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+ Source code for torch_xla.runtime
+import functools
+import logging
+import os
+import warnings
+from typing import Dict, List, Optional, TypeVar
+
+import torch
+import torch.cuda
+import torch_xla
+import torch_xla.core.xla_env_vars as xenv
+import torch_xla.core.xla_model as xm
+import torch_xla.utils.utils as xu
+import torch_xla._internal.utils as _utils
+import torch_xla._internal.tpu as tpu
+from torch_xla.experimental import plugins
+from torch_xla import runtime
+
+R = TypeVar('R')
+FN = TypeVar('FN')
+
+# Note [Dynamo WORLD_SIEZ and ORDINAL]
+# Belows are workaround to cache the ordinal and world_size such that
+# Dynamo won't do graph breaks when runtime.world_size() and runtime.global_ordinal() are called.
+_WORLD_SIZE = None
+_ORDINAL = None
+
+
+def _init_world_size_ordinal():
+ global _WORLD_SIZE, _ORDINAL
+
+ # Dynamo doesn't support XRT or multithreaded runtime. See Note [V3-8 Threading]
+ if runtime.addressable_device_count() > 1:
+ return
+
+ if _WORLD_SIZE is None:
+ _WORLD_SIZE = runtime.world_size()
+ _ORDINAL = runtime.global_ordinal()
+
+
+def set_device_type(pjrt_device: str) -> None:
+ """Sets the current PjRt device type.
+
+ Must be run before using any XLA devices.
+
+ Args:
+ pjrt_device: 'TPU' or 'CPU'
+ """
+ if torch_xla._XLAC._xla_runtime_is_initialized() and os.environ.get(
+ xenv.PJRT_DEVICE) != pjrt_device:
+ raise RuntimeError(
+ "Can't change device type after XLA runtime is initialized")
+
+ os.environ[xenv.PJRT_DEVICE] = pjrt_device
+
+
+def _maybe_select_default_device():
+ if xu.getenv_as(xenv.PJRT_SELECT_DEFAULT_DEVICE, str,
+ '1') == '0' or xenv.PJRT_DEVICE in os.environ:
+ return
+
+ # Check for libtpu _and_ the TPU device
+ if torch_xla._found_libtpu and tpu.num_available_chips() > 0:
+ logging.warning('libtpu.so and TPU device found. Setting PJRT_DEVICE=TPU.')
+ os.environ[xenv.PJRT_DEVICE] = 'TPU'
+ elif xu.getenv_as(xenv.GPU_NUM_DEVICES, int, 0) > 0:
+ logging.warning('GPU_NUM_DEVICES is set. Setting PJRT_DEVICE=CUDA')
+ os.environ[xenv.PJRT_DEVICE] = 'CUDA'
+ elif torch.cuda.is_available() and torch.cuda.device_count() > 0:
+ num_devices_str = str(torch.cuda.device_count())
+ logging.warning(
+ 'Found CUDA without GPU_NUM_DEVICES. Defaulting to PJRT_DEVICE=CUDA with GPU_NUM_DEVICES='
+ + num_devices_str)
+ os.environ[xenv.PJRT_DEVICE] = 'CUDA'
+ os.environ[xenv.GPU_NUM_DEVICES] = num_devices_str
+ elif torch_xla._found_libneuronxla:
+ logging.warning('Found libneuronpjrt.so. Setting PJRT_DEVICE=NEURON.')
+ os.environ[xenv.PJRT_DEVICE] = 'NEURON'
+ else:
+ logging.warning('Defaulting to PJRT_DEVICE=CPU')
+ os.environ[xenv.PJRT_DEVICE] = 'CPU'
+
+
+[docs]def device_type() -> Optional[str]:
+ """Returns the current PjRt device type.
+
+ Selects a default device if none has been configured
+
+ Returns:
+ A string representation of the device.
+ """
+ pjrt_device = xu.getenv_as(xenv.PJRT_DEVICE, str)
+ return pjrt_device.split('_')[0] if pjrt_device else pjrt_device
+
+
+def is_bf16_supported():
+ """Returns whether torch.bfloat16 is supported on this environment.
+ """
+ try:
+ torch.tensor([1.], dtype=torch.bfloat16, device=xm.xla_device())
+ return True
+ except Exception as e:
+ return False
+
+
+def xla_device(n: Optional[int] = None,
+ devkind: Optional[str] = None) -> torch.device:
+ """Returns an XLA device.
+
+ Args:
+ n: Index of XLA device within visibible devices. If not set, use local
+ ordinal (default 0) to select an addressable device.
+ devkind: Type of device to return. Should match `device_type()`.
+
+ Returns:
+ A `torch.device` representing an XLA device.
+ """
+ if n is None:
+ return torch.device(torch_xla._XLAC._xla_get_default_device())
+
+ devices = xm.get_xla_supported_devices(devkind=devkind)
+ if n > len(devices):
+ raise IndexError('Device index {} out of range in {}'.format(n, devices))
+
+ device = devices[n]
+ torch_xla._XLAC._xla_set_default_device(device)
+ return torch.device(device)
+
+
+[docs]def local_process_count() -> int:
+ """Returns the number of processes running on this host."""
+ return xu.getenv_as(xenv.PJRT_LOCAL_PROCESS_COUNT, int, defval=1)
+
+
+[docs]def global_device_count() -> int:
+ """Returns the total number of devices across all processes/hosts."""
+ return len(torch_xla._XLAC._xla_get_all_devices())
+
+
+[docs]def world_size() -> int:
+ """Returns the total number of processes participating in the job."""
+ global _WORLD_SIZE
+ if _WORLD_SIZE is not None:
+ return _WORLD_SIZE
+ if torch_xla._XLAC._xla_get_replication_devices_count() == 0:
+ _WORLD_SIZE = 1
+ else:
+ _WORLD_SIZE = global_device_count()
+ return _WORLD_SIZE
+
+
+[docs]def local_device_count() -> int:
+ """Returns the total number of devices on this host.
+
+ Assumes each process has the same number of addressable devices.
+ """
+ return local_process_count() * addressable_device_count()
+
+
+[docs]def addressable_device_count() -> int:
+ """Returns the number of devices visible to this process."""
+ return torch_xla._XLAC._xla_num_devices()
+
+
+[docs]def global_ordinal() -> int:
+ """Returns global ordinal of this thread within all processes.
+
+ Global ordinal is in range [0, global_device_count). Global ordinals are not
+ guaranteed to have any predictable relationship to the TPU worker ID nor are
+ they guaranteed to be contiguous on each host."""
+ global _ORDINAL
+ if _ORDINAL is not None:
+ return _ORDINAL
+ return torch_xla._XLAC._xla_get_default_device_ordinal()
+
+
+[docs]def local_ordinal() -> int:
+ """Returns local ordinal of this thread within this host.
+
+ Local ordinal is in range [0, local_device_count)."""
+ local_rank = xu.getenv_as(xenv.PJRT_LOCAL_PROCESS_RANK, int, 0)
+ devices_per_process = addressable_device_count()
+ return local_rank * devices_per_process + xla_device().index
+
+
+def process_index() -> int:
+ return torch_xla._XLAC._xla_get_process_index()
+
+
+def process_count() -> int:
+ return torch_xla._XLAC._xla_get_num_processes()
+
+
+def host_index() -> int:
+ if plugins.using_dynamic_plugins():
+ return plugins.default().host_index()
+ elif device_type() == 'TPU':
+ return tpu.worker_id()
+
+ # TODO: Update this when we support multi-host GPU
+ return 0
+
+
+# API below will be used to query physcial device attribute.
+def runtime_device_attributes(device: str) -> Dict[str, object]:
+ return torch_xla._XLAC._xla_get_device_attributes(device)
+
+
+def global_runtime_device_attributes() -> List[Dict[str, object]]:
+ return torch_xla._XLAC._xla_get_all_device_attributes()
+
+
+[docs]@functools.lru_cache()
+def global_runtime_device_count() -> int:
+ """Returns the total number of runtime devices across all processes/hosts, especially useful for SPMD."""
+ return len(torch_xla._XLAC._xla_get_all_runtime_devices())
+
+
+def addressable_runtime_device_count() -> int:
+ """Returns the number of devices visible to this process."""
+ return torch_xla._XLAC._xla_num_runtime_devices()
+
+
+# TODO(yeounoh) introduce SPMD configuration.
+[docs]def use_spmd(auto: Optional[bool] = False):
+ """API to enable SPMD mode. This is a recommended way to enable SPMD.
+
+ This forces SPMD mode if some tensors are already initialized on non-SPMD
+ devices. This means that those tensors would be replicated across the devices.
+
+ Args:
+ auto (bool): Whether to enable the auto-sharding. Read
+ https://github.com/pytorch/xla/blob/master/docs/spmd_advanced.md#auto-sharding
+ for more detail
+ """
+ if os.environ.get("XLA_USE_SPMD") is not None:
+ warnings.warn("XLA_USE_SPMD is being deprecated. "
+ "Use torch_xla.runtime.use_spmd() "
+ "without setting XLA_USE_SPMD env-var.")
+
+ if torch_xla._XLAC._xla_get_spmd_config_is_locked(
+ ) and not xu.check_env_flag("XLA_USE_SPMD"):
+ warnings.warn(
+ "Replicating tensors already initialized on non-virtual XLA device for SPMD "
+ "to force SPMD mode. This is one-time overhead to setup, and to minimize such, "
+ "please set SPMD mode before initializting tensors "
+ "(i.e., call use_spmd() in the beginning of the program).")
+ torch_xla._XLAC._xla_force_spmd_device()
+ xm.wait_device_ops()
+
+ # TODO(yeounoh) we can drop envvar in the future
+ os.environ["XLA_USE_SPMD"] = "1"
+ if auto:
+ torch_xla._XLAC._xla_set_auto_sharding()
+ os.environ["XLA_AUTO_SPMD"] = "1"
+
+ if device_type() == 'NEURON':
+ # In case of Neuron, reset the initialization environment to accommodate SPMD.
+ try:
+ from torch_neuronx.initialization import initialize
+
+ initialize()
+ except ImportError:
+ pass
+
+
+[docs]def is_spmd():
+ """Returns if SPMD is set for execution."""
+ # TODO(yeounoh) replace this when we fully deprecate the flag.
+ return xu.check_env_flag('XLA_USE_SPMD')
+
+
+[docs]def get_master_ip() -> str:
+ """Retrieve the master worker IP for the runtime. This calls into
+ backend-specific discovery APIs.
+
+ Returns:
+ master worker's IP address as a string."""
+ if device_type() == 'TPU':
+ return tpu.discover_master_worker_ip()
+ raise RuntimeError(f'IP discovery not supported for device: {device_type()}')
+
+
+[docs]def initialize_cache(path: str, readonly: bool = False):
+ """Initializes the persistent compilation cache. This API must be called
+ before any computations have been performed.
+
+ Args:
+ path (str): The path at which to store the persistent cache.
+ readonly (bool): Whether or not this worker should have write access to the cache.
+ """
+ assert not torch_xla._XLAC._xla_computation_cache_is_initialized(
+ ), "Computation cache has already been initialized"
+
+ # TODO(jonbolin): Consider moving away from environment variables to control
+ # the cache.
+ os.environ['XLA_PERSISTENT_CACHE_PATH'] = path
+ os.environ['XLA_PERSISTENT_CACHE_READ_ONLY'] = '1' if readonly else '0'
+
+
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+
\ No newline at end of file
diff --git a/release/2.5/_modules/torch_xla/torch_xla.html b/release/2.5/_modules/torch_xla/torch_xla.html
new file mode 100644
index 00000000000..7875958cc0e
--- /dev/null
+++ b/release/2.5/_modules/torch_xla/torch_xla.html
@@ -0,0 +1,939 @@
+
+
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+
+
+
+
+ 
+
+To analyze traffic and optimize your experience, we serve cookies on this site. By clicking or navigating, you agree to allow our usage of cookies. As the current maintainers of this site, Facebook’s Cookies Policy applies. Learn more, including about available controls: Cookies Policy.
+
+
+
+
+
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+
+
+
+
+
+
+
+x = y + 2
+if x[0] == 2 :
+ z = y +1
+else:
+ z = y - 1
+```
+
+Note you'll evaluate x using a subgraph when you hit control flow, but there might be previous variable included in the branch computation as well (like` y` is just one node smaller than x, but it wasn't materizalized when you evaluate `x`). So you're actually evaluating 1 small graph and two big graphs for this example. And with more control flow involved, y could get updated in multiple branches which still produces different combo of large graphs.
+
diff --git a/release/2.5/_sources/quantized_ops.rst.txt b/release/2.5/_sources/quantized_ops.rst.txt
new file mode 100644
index 00000000000..1ebe49105a3
--- /dev/null
+++ b/release/2.5/_sources/quantized_ops.rst.txt
@@ -0,0 +1 @@
+.. mdinclude:: ../quantized_ops.md
\ No newline at end of file
diff --git a/release/2.5/_sources/runtime.rst.txt b/release/2.5/_sources/runtime.rst.txt
new file mode 100644
index 00000000000..3aca8f3dfe1
--- /dev/null
+++ b/release/2.5/_sources/runtime.rst.txt
@@ -0,0 +1 @@
+.. mdinclude:: ../pjrt.md
\ No newline at end of file
diff --git a/release/2.5/_sources/spmd.rst.txt b/release/2.5/_sources/spmd.rst.txt
new file mode 100644
index 00000000000..6765a5d24a6
--- /dev/null
+++ b/release/2.5/_sources/spmd.rst.txt
@@ -0,0 +1,4 @@
+.. mdinclude:: ../spmd_basic.md
+.. mdinclude:: ../fsdpv2.md
+.. mdinclude:: ../spmd_advanced.md
+.. mdinclude:: ../spmd_distributed_checkpoint.md
\ No newline at end of file
diff --git a/release/2.5/_sources/torch_compile.rst.txt b/release/2.5/_sources/torch_compile.rst.txt
new file mode 100644
index 00000000000..505163227f0
--- /dev/null
+++ b/release/2.5/_sources/torch_compile.rst.txt
@@ -0,0 +1 @@
+.. mdinclude:: ../dynamo.md
\ No newline at end of file
diff --git a/release/2.5/_static/_sphinx_javascript_frameworks_compat.js b/release/2.5/_static/_sphinx_javascript_frameworks_compat.js
new file mode 100644
index 00000000000..8549469dc29
--- /dev/null
+++ b/release/2.5/_static/_sphinx_javascript_frameworks_compat.js
@@ -0,0 +1,134 @@
+/*
+ * _sphinx_javascript_frameworks_compat.js
+ * ~~~~~~~~~~
+ *
+ * Compatability shim for jQuery and underscores.js.
+ *
+ * WILL BE REMOVED IN Sphinx 6.0
+ * xref RemovedInSphinx60Warning
+ *
+ */
+
+/**
+ * select a different prefix for underscore
+ */
+$u = _.noConflict();
+
+
+/**
+ * small helper function to urldecode strings
+ *
+ * See https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/decodeURIComponent#Decoding_query_parameters_from_a_URL
+ */
+jQuery.urldecode = function(x) {
+ if (!x) {
+ return x
+ }
+ return decodeURIComponent(x.replace(/\+/g, ' '));
+};
+
+/**
+ * small helper function to urlencode strings
+ */
+jQuery.urlencode = encodeURIComponent;
+
+/**
+ * This function returns the parsed url parameters of the
+ * current request. Multiple values per key are supported,
+ * it will always return arrays of strings for the value parts.
+ */
+jQuery.getQueryParameters = function(s) {
+ if (typeof s === 'undefined')
+ s = document.location.search;
+ var parts = s.substr(s.indexOf('?') + 1).split('&');
+ var result = {};
+ for (var i = 0; i < parts.length; i++) {
+ var tmp = parts[i].split('=', 2);
+ var key = jQuery.urldecode(tmp[0]);
+ var value = jQuery.urldecode(tmp[1]);
+ if (key in result)
+ result[key].push(value);
+ else
+ result[key] = [value];
+ }
+ return result;
+};
+
+/**
+ * highlight a given string on a jquery object by wrapping it in
+ * span elements with the given class name.
+ */
+jQuery.fn.highlightText = function(text, className) {
+ function highlight(node, addItems) {
+ if (node.nodeType === 3) {
+ var val = node.nodeValue;
+ var pos = val.toLowerCase().indexOf(text);
+ if (pos >= 0 &&
+ !jQuery(node.parentNode).hasClass(className) &&
+ !jQuery(node.parentNode).hasClass("nohighlight")) {
+ var span;
+ var isInSVG = jQuery(node).closest("body, svg, foreignObject").is("svg");
+ if (isInSVG) {
+ span = document.createElementNS("http://www.w3.org/2000/svg", "tspan");
+ } else {
+ span = document.createElement("span");
+ span.className = className;
+ }
+ span.appendChild(document.createTextNode(val.substr(pos, text.length)));
+ node.parentNode.insertBefore(span, node.parentNode.insertBefore(
+ document.createTextNode(val.substr(pos + text.length)),
+ node.nextSibling));
+ node.nodeValue = val.substr(0, pos);
+ if (isInSVG) {
+ var rect = document.createElementNS("http://www.w3.org/2000/svg", "rect");
+ var bbox = node.parentElement.getBBox();
+ rect.x.baseVal.value = bbox.x;
+ rect.y.baseVal.value = bbox.y;
+ rect.width.baseVal.value = bbox.width;
+ rect.height.baseVal.value = bbox.height;
+ rect.setAttribute('class', className);
+ addItems.push({
+ "parent": node.parentNode,
+ "target": rect});
+ }
+ }
+ }
+ else if (!jQuery(node).is("button, select, textarea")) {
+ jQuery.each(node.childNodes, function() {
+ highlight(this, addItems);
+ });
+ }
+ }
+ var addItems = [];
+ var result = this.each(function() {
+ highlight(this, addItems);
+ });
+ for (var i = 0; i < addItems.length; ++i) {
+ jQuery(addItems[i].parent).before(addItems[i].target);
+ }
+ return result;
+};
+
+/*
+ * backward compatibility for jQuery.browser
+ * This will be supported until firefox bug is fixed.
+ */
+if (!jQuery.browser) {
+ jQuery.uaMatch = function(ua) {
+ ua = ua.toLowerCase();
+
+ var match = /(chrome)[ \/]([\w.]+)/.exec(ua) ||
+ /(webkit)[ \/]([\w.]+)/.exec(ua) ||
+ /(opera)(?:.*version|)[ \/]([\w.]+)/.exec(ua) ||
+ /(msie) ([\w.]+)/.exec(ua) ||
+ ua.indexOf("compatible") < 0 && /(mozilla)(?:.*? rv:([\w.]+)|)/.exec(ua) ||
+ [];
+
+ return {
+ browser: match[ 1 ] || "",
+ version: match[ 2 ] || "0"
+ };
+ };
+ jQuery.browser = {};
+ jQuery.browser[jQuery.uaMatch(navigator.userAgent).browser] = true;
+}
diff --git a/release/2.5/_static/basic.css b/release/2.5/_static/basic.css
new file mode 100644
index 00000000000..eeb0519a69b
--- /dev/null
+++ b/release/2.5/_static/basic.css
@@ -0,0 +1,899 @@
+/*
+ * basic.css
+ * ~~~~~~~~~
+ *
+ * Sphinx stylesheet -- basic theme.
+ *
+ * :copyright: Copyright 2007-2022 by the Sphinx team, see AUTHORS.
+ * :license: BSD, see LICENSE for details.
+ *
+ */
+
+/* -- main layout ----------------------------------------------------------- */
+
+div.clearer {
+ clear: both;
+}
+
+div.section::after {
+ display: block;
+ content: '';
+ clear: left;
+}
+
+/* -- relbar ---------------------------------------------------------------- */
+
+div.related {
+ width: 100%;
+ font-size: 90%;
+}
+
+div.related h3 {
+ display: none;
+}
+
+div.related ul {
+ margin: 0;
+ padding: 0 0 0 10px;
+ list-style: none;
+}
+
+div.related li {
+ display: inline;
+}
+
+div.related li.right {
+ float: right;
+ margin-right: 5px;
+}
+
+/* -- sidebar --------------------------------------------------------------- */
+
+div.sphinxsidebarwrapper {
+ padding: 10px 5px 0 10px;
+}
+
+div.sphinxsidebar {
+ float: left;
+ width: 230px;
+ margin-left: -100%;
+ font-size: 90%;
+ word-wrap: break-word;
+ overflow-wrap : break-word;
+}
+
+div.sphinxsidebar ul {
+ list-style: none;
+}
+
+div.sphinxsidebar ul ul,
+div.sphinxsidebar ul.want-points {
+ margin-left: 20px;
+ list-style: square;
+}
+
+div.sphinxsidebar ul ul {
+ margin-top: 0;
+ margin-bottom: 0;
+}
+
+div.sphinxsidebar form {
+ margin-top: 10px;
+}
+
+div.sphinxsidebar input {
+ border: 1px solid #98dbcc;
+ font-family: sans-serif;
+ font-size: 1em;
+}
+
+div.sphinxsidebar #searchbox form.search {
+ overflow: hidden;
+}
+
+div.sphinxsidebar #searchbox input[type="text"] {
+ float: left;
+ width: 80%;
+ padding: 0.25em;
+ box-sizing: border-box;
+}
+
+div.sphinxsidebar #searchbox input[type="submit"] {
+ float: left;
+ width: 20%;
+ border-left: none;
+ padding: 0.25em;
+ box-sizing: border-box;
+}
+
+
+img {
+ border: 0;
+ max-width: 100%;
+}
+
+/* -- search page ----------------------------------------------------------- */
+
+ul.search {
+ margin: 10px 0 0 20px;
+ padding: 0;
+}
+
+ul.search li {
+ padding: 5px 0 5px 20px;
+ background-image: url(file.png);
+ background-repeat: no-repeat;
+ background-position: 0 7px;
+}
+
+ul.search li a {
+ font-weight: bold;
+}
+
+ul.search li p.context {
+ color: #888;
+ margin: 2px 0 0 30px;
+ text-align: left;
+}
+
+ul.keywordmatches li.goodmatch a {
+ font-weight: bold;
+}
+
+/* -- index page ------------------------------------------------------------ */
+
+table.contentstable {
+ width: 90%;
+ margin-left: auto;
+ margin-right: auto;
+}
+
+table.contentstable p.biglink {
+ line-height: 150%;
+}
+
+a.biglink {
+ font-size: 1.3em;
+}
+
+span.linkdescr {
+ font-style: italic;
+ padding-top: 5px;
+ font-size: 90%;
+}
+
+/* -- general index --------------------------------------------------------- */
+
+table.indextable {
+ width: 100%;
+}
+
+table.indextable td {
+ text-align: left;
+ vertical-align: top;
+}
+
+table.indextable ul {
+ margin-top: 0;
+ margin-bottom: 0;
+ list-style-type: none;
+}
+
+table.indextable > tbody > tr > td > ul {
+ padding-left: 0em;
+}
+
+table.indextable tr.pcap {
+ height: 10px;
+}
+
+table.indextable tr.cap {
+ margin-top: 10px;
+ background-color: #f2f2f2;
+}
+
+img.toggler {
+ margin-right: 3px;
+ margin-top: 3px;
+ cursor: pointer;
+}
+
+div.modindex-jumpbox {
+ border-top: 1px solid #ddd;
+ border-bottom: 1px solid #ddd;
+ margin: 1em 0 1em 0;
+ padding: 0.4em;
+}
+
+div.genindex-jumpbox {
+ border-top: 1px solid #ddd;
+ border-bottom: 1px solid #ddd;
+ margin: 1em 0 1em 0;
+ padding: 0.4em;
+}
+
+/* -- domain module index --------------------------------------------------- */
+
+table.modindextable td {
+ padding: 2px;
+ border-collapse: collapse;
+}
+
+/* -- general body styles --------------------------------------------------- */
+
+div.body {
+ min-width: 360px;
+ max-width: 800px;
+}
+
+div.body p, div.body dd, div.body li, div.body blockquote {
+ -moz-hyphens: auto;
+ -ms-hyphens: auto;
+ -webkit-hyphens: auto;
+ hyphens: auto;
+}
+
+a.headerlink {
+ visibility: hidden;
+}
+a.brackets:before,
+span.brackets > a:before{
+ content: "[";
+}
+
+a.brackets:after,
+span.brackets > a:after {
+ content: "]";
+}
+
+
+h1:hover > a.headerlink,
+h2:hover > a.headerlink,
+h3:hover > a.headerlink,
+h4:hover > a.headerlink,
+h5:hover > a.headerlink,
+h6:hover > a.headerlink,
+dt:hover > a.headerlink,
+caption:hover > a.headerlink,
+p.caption:hover > a.headerlink,
+div.code-block-caption:hover > a.headerlink {
+ visibility: visible;
+}
+
+div.body p.caption {
+ text-align: inherit;
+}
+
+div.body td {
+ text-align: left;
+}
+
+.first {
+ margin-top: 0 !important;
+}
+
+p.rubric {
+ margin-top: 30px;
+ font-weight: bold;
+}
+
+img.align-left, figure.align-left, .figure.align-left, object.align-left {
+ clear: left;
+ float: left;
+ margin-right: 1em;
+}
+
+img.align-right, figure.align-right, .figure.align-right, object.align-right {
+ clear: right;
+ float: right;
+ margin-left: 1em;
+}
+
+img.align-center, figure.align-center, .figure.align-center, object.align-center {
+ display: block;
+ margin-left: auto;
+ margin-right: auto;
+}
+
+img.align-default, figure.align-default, .figure.align-default {
+ display: block;
+ margin-left: auto;
+ margin-right: auto;
+}
+
+.align-left {
+ text-align: left;
+}
+
+.align-center {
+ text-align: center;
+}
+
+.align-default {
+ text-align: center;
+}
+
+.align-right {
+ text-align: right;
+}
+
+/* -- sidebars -------------------------------------------------------------- */
+
+div.sidebar,
+aside.sidebar {
+ margin: 0 0 0.5em 1em;
+ border: 1px solid #ddb;
+ padding: 7px;
+ background-color: #ffe;
+ width: 40%;
+ float: right;
+ clear: right;
+ overflow-x: auto;
+}
+
+p.sidebar-title {
+ font-weight: bold;
+}
+div.admonition, div.topic, blockquote {
+ clear: left;
+}
+
+/* -- topics ---------------------------------------------------------------- */
+div.topic {
+ border: 1px solid #ccc;
+ padding: 7px;
+ margin: 10px 0 10px 0;
+}
+
+p.topic-title {
+ font-size: 1.1em;
+ font-weight: bold;
+ margin-top: 10px;
+}
+
+/* -- admonitions ----------------------------------------------------------- */
+
+div.admonition {
+ margin-top: 10px;
+ margin-bottom: 10px;
+ padding: 7px;
+}
+
+div.admonition dt {
+ font-weight: bold;
+}
+
+p.admonition-title {
+ margin: 0px 10px 5px 0px;
+ font-weight: bold;
+}
+
+div.body p.centered {
+ text-align: center;
+ margin-top: 25px;
+}
+
+/* -- content of sidebars/topics/admonitions -------------------------------- */
+
+div.sidebar > :last-child,
+aside.sidebar > :last-child,
+div.topic > :last-child,
+div.admonition > :last-child {
+ margin-bottom: 0;
+}
+
+div.sidebar::after,
+aside.sidebar::after,
+div.topic::after,
+div.admonition::after,
+blockquote::after {
+ display: block;
+ content: '';
+ clear: both;
+}
+
+/* -- tables ---------------------------------------------------------------- */
+
+table.docutils {
+ margin-top: 10px;
+ margin-bottom: 10px;
+ border: 0;
+ border-collapse: collapse;
+}
+
+table.align-center {
+ margin-left: auto;
+ margin-right: auto;
+}
+
+table.align-default {
+ margin-left: auto;
+ margin-right: auto;
+}
+
+table caption span.caption-number {
+ font-style: italic;
+}
+
+table caption span.caption-text {
+}
+
+table.docutils td, table.docutils th {
+ padding: 1px 8px 1px 5px;
+ border-top: 0;
+ border-left: 0;
+ border-right: 0;
+ border-bottom: 1px solid #aaa;
+}
+
+th {
+ text-align: left;
+ padding-right: 5px;
+}
+
+table.citation {
+ border-left: solid 1px gray;
+ margin-left: 1px;
+}
+
+table.citation td {
+ border-bottom: none;
+}
+
+th > :first-child,
+td > :first-child {
+ margin-top: 0px;
+}
+
+th > :last-child,
+td > :last-child {
+ margin-bottom: 0px;
+}
+
+/* -- figures --------------------------------------------------------------- */
+
+div.figure, figure {
+ margin: 0.5em;
+ padding: 0.5em;
+}
+
+div.figure p.caption, figcaption {
+ padding: 0.3em;
+}
+
+div.figure p.caption span.caption-number,
+figcaption span.caption-number {
+ font-style: italic;
+}
+
+div.figure p.caption span.caption-text,
+figcaption span.caption-text {
+}
+
+/* -- field list styles ----------------------------------------------------- */
+
+table.field-list td, table.field-list th {
+ border: 0 !important;
+}
+
+.field-list ul {
+ margin: 0;
+ padding-left: 1em;
+}
+
+.field-list p {
+ margin: 0;
+}
+
+.field-name {
+ -moz-hyphens: manual;
+ -ms-hyphens: manual;
+ -webkit-hyphens: manual;
+ hyphens: manual;
+}
+
+/* -- hlist styles ---------------------------------------------------------- */
+
+table.hlist {
+ margin: 1em 0;
+}
+
+table.hlist td {
+ vertical-align: top;
+}
+
+/* -- object description styles --------------------------------------------- */
+
+.sig {
+ font-family: 'Consolas', 'Menlo', 'DejaVu Sans Mono', 'Bitstream Vera Sans Mono', monospace;
+}
+
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+ background-color: transparent;
+ font-weight: bold;
+}
+
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+ font-size: 1.1em;
+}
+
+code.descname {
+ font-size: 1.2em;
+}
+
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+ background-color: transparent;
+}
+
+.optional {
+ font-size: 1.3em;
+}
+
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+ font-size: larger;
+}
+
+.sig-param.n {
+ font-style: italic;
+}
+
+/* C++ specific styling */
+
+.sig-inline.c-texpr,
+.sig-inline.cpp-texpr {
+ font-family: unset;
+}
+
+.sig.c .k, .sig.c .kt,
+.sig.cpp .k, .sig.cpp .kt {
+ color: #0033B3;
+}
+
+.sig.c .m,
+.sig.cpp .m {
+ color: #1750EB;
+}
+
+.sig.c .s, .sig.c .sc,
+.sig.cpp .s, .sig.cpp .sc {
+ color: #067D17;
+}
+
+
+/* -- other body styles ----------------------------------------------------- */
+
+ol.arabic {
+ list-style: decimal;
+}
+
+ol.loweralpha {
+ list-style: lower-alpha;
+}
+
+ol.upperalpha {
+ list-style: upper-alpha;
+}
+
+ol.lowerroman {
+ list-style: lower-roman;
+}
+
+ol.upperroman {
+ list-style: upper-roman;
+}
+
+:not(li) > ol > li:first-child > :first-child,
+:not(li) > ul > li:first-child > :first-child {
+ margin-top: 0px;
+}
+
+:not(li) > ol > li:last-child > :last-child,
+:not(li) > ul > li:last-child > :last-child {
+ margin-bottom: 0px;
+}
+
+ol.simple ol p,
+ol.simple ul p,
+ul.simple ol p,
+ul.simple ul p {
+ margin-top: 0;
+}
+
+ol.simple > li:not(:first-child) > p,
+ul.simple > li:not(:first-child) > p {
+ margin-top: 0;
+}
+
+ol.simple p,
+ul.simple p {
+ margin-bottom: 0;
+}
+dl.footnote > dt,
+dl.citation > dt {
+ float: left;
+ margin-right: 0.5em;
+}
+
+dl.footnote > dd,
+dl.citation > dd {
+ margin-bottom: 0em;
+}
+
+dl.footnote > dd:after,
+dl.citation > dd:after {
+ content: "";
+ clear: both;
+}
+
+dl.field-list {
+ display: grid;
+ grid-template-columns: fit-content(30%) auto;
+}
+
+dl.field-list > dt {
+ font-weight: bold;
+ word-break: break-word;
+ padding-left: 0.5em;
+ padding-right: 5px;
+}
+dl.field-list > dt:after {
+ content: ":";
+}
+
+
+dl.field-list > dd {
+ padding-left: 0.5em;
+ margin-top: 0em;
+ margin-left: 0em;
+ margin-bottom: 0em;
+}
+
+dl {
+ margin-bottom: 15px;
+}
+
+dd > :first-child {
+ margin-top: 0px;
+}
+
+dd ul, dd table {
+ margin-bottom: 10px;
+}
+
+dd {
+ margin-top: 3px;
+ margin-bottom: 10px;
+ margin-left: 30px;
+}
+
+dl > dd:last-child,
+dl > dd:last-child > :last-child {
+ margin-bottom: 0;
+}
+
+dt:target, span.highlighted {
+ background-color: #fbe54e;
+}
+
+rect.highlighted {
+ fill: #fbe54e;
+}
+
+dl.glossary dt {
+ font-weight: bold;
+ font-size: 1.1em;
+}
+
+.versionmodified {
+ font-style: italic;
+}
+
+.system-message {
+ background-color: #fda;
+ padding: 5px;
+ border: 3px solid red;
+}
+
+.footnote:target {
+ background-color: #ffa;
+}
+
+.line-block {
+ display: block;
+ margin-top: 1em;
+ margin-bottom: 1em;
+}
+
+.line-block .line-block {
+ margin-top: 0;
+ margin-bottom: 0;
+ margin-left: 1.5em;
+}
+
+.guilabel, .menuselection {
+ font-family: sans-serif;
+}
+
+.accelerator {
+ text-decoration: underline;
+}
+
+.classifier {
+ font-style: oblique;
+}
+
+.classifier:before {
+ font-style: normal;
+ margin: 0 0.5em;
+ content: ":";
+ display: inline-block;
+}
+
+abbr, acronym {
+ border-bottom: dotted 1px;
+ cursor: help;
+}
+
+/* -- code displays --------------------------------------------------------- */
+
+pre {
+ overflow: auto;
+ overflow-y: hidden; /* fixes display issues on Chrome browsers */
+}
+
+pre, div[class*="highlight-"] {
+ clear: both;
+}
+
+span.pre {
+ -moz-hyphens: none;
+ -ms-hyphens: none;
+ -webkit-hyphens: none;
+ hyphens: none;
+ white-space: nowrap;
+}
+
+div[class*="highlight-"] {
+ margin: 1em 0;
+}
+
+td.linenos pre {
+ border: 0;
+ background-color: transparent;
+ color: #aaa;
+}
+
+table.highlighttable {
+ display: block;
+}
+
+table.highlighttable tbody {
+ display: block;
+}
+
+table.highlighttable tr {
+ display: flex;
+}
+
+table.highlighttable td {
+ margin: 0;
+ padding: 0;
+}
+
+table.highlighttable td.linenos {
+ padding-right: 0.5em;
+}
+
+table.highlighttable td.code {
+ flex: 1;
+ overflow: hidden;
+}
+
+.highlight .hll {
+ display: block;
+}
+
+div.highlight pre,
+table.highlighttable pre {
+ margin: 0;
+}
+
+div.code-block-caption + div {
+ margin-top: 0;
+}
+
+div.code-block-caption {
+ margin-top: 1em;
+ padding: 2px 5px;
+ font-size: small;
+}
+
+div.code-block-caption code {
+ background-color: transparent;
+}
+
+table.highlighttable td.linenos,
+span.linenos,
+div.highlight span.gp { /* gp: Generic.Prompt */
+ user-select: none;
+ -webkit-user-select: text; /* Safari fallback only */
+ -webkit-user-select: none; /* Chrome/Safari */
+ -moz-user-select: none; /* Firefox */
+ -ms-user-select: none; /* IE10+ */
+}
+
+div.code-block-caption span.caption-number {
+ padding: 0.1em 0.3em;
+ font-style: italic;
+}
+
+div.code-block-caption span.caption-text {
+}
+
+div.literal-block-wrapper {
+ margin: 1em 0;
+}
+
+code.xref, a code {
+ background-color: transparent;
+ font-weight: bold;
+}
+
+h1 code, h2 code, h3 code, h4 code, h5 code, h6 code {
+ background-color: transparent;
+}
+
+.viewcode-link {
+ float: right;
+}
+
+.viewcode-back {
+ float: right;
+ font-family: sans-serif;
+}
+
+div.viewcode-block:target {
+ margin: -1px -10px;
+ padding: 0 10px;
+}
+
+/* -- math display ---------------------------------------------------------- */
+
+img.math {
+ vertical-align: middle;
+}
+
+div.body div.math p {
+ text-align: center;
+}
+
+span.eqno {
+ float: right;
+}
+
+span.eqno a.headerlink {
+ position: absolute;
+ z-index: 1;
+}
+
+div.math:hover a.headerlink {
+ visibility: visible;
+}
+
+/* -- printout stylesheet --------------------------------------------------- */
+
+@media print {
+ div.document,
+ div.documentwrapper,
+ div.bodywrapper {
+ margin: 0 !important;
+ width: 100%;
+ }
+
+ div.sphinxsidebar,
+ div.related,
+ div.footer,
+ #top-link {
+ display: none;
+ }
+}
\ No newline at end of file
diff --git a/release/2.5/_static/css/pytorch_theme.css b/release/2.5/_static/css/pytorch_theme.css
new file mode 100644
index 00000000000..0e54497643c
--- /dev/null
+++ b/release/2.5/_static/css/pytorch_theme.css
@@ -0,0 +1,118 @@
+body {
+ font-family: "Lato","proxima-nova","Helvetica Neue",Arial,sans-serif;
+}
+
+/* Default header fonts are ugly */
+h1, h2, .rst-content .toctree-wrapper p.caption, h3, h4, h5, h6, legend, p.caption {
+ font-family: "Lato","proxima-nova","Helvetica Neue",Arial,sans-serif;
+}
+
+/* Use white for docs background */
+.wy-side-nav-search {
+ background-color: #fff;
+}
+
+.wy-nav-content-wrap, .wy-menu li.current > a {
+ background-color: #fff;
+}
+
+@media screen and (min-width: 1400px) {
+ .wy-nav-content-wrap {
+ background-color: rgba(0, 0, 0, 0.0470588);
+ }
+
+ .wy-nav-content {
+ background-color: #fff;
+ }
+}
+
+/* Fixes for mobile */
+.wy-nav-top {
+ background-color: #fff;
+ background-image: url('../img/pytorch-logo-dark.svg');
+ background-repeat: no-repeat;
+ background-position: center;
+ padding: 0;
+ margin: 0.4045em 0.809em;
+ color: #333;
+}
+
+.wy-nav-top > a {
+ display: none;
+}
+
+@media screen and (max-width: 768px) {
+ .wy-side-nav-search>a img.logo {
+ height: 60px;
+ }
+}
+
+/* This is needed to ensure that logo above search scales properly */
+.wy-side-nav-search a {
+ display: block;
+}
+
+/* This ensures that multiple constructors will remain in separate lines. */
+.rst-content dl:not(.docutils) dt {
+ display: table;
+}
+
+/* Use our red for literals (it's very similar to the original color) */
+.rst-content tt.literal, .rst-content tt.literal, .rst-content code.literal {
+ color: #F05732;
+}
+
+.rst-content tt.xref, a .rst-content tt, .rst-content tt.xref,
+.rst-content code.xref, a .rst-content tt, a .rst-content code {
+ color: #404040;
+}
+
+/* Change link colors (except for the menu) */
+
+a {
+ color: #F05732;
+}
+
+a:hover {
+ color: #F05732;
+}
+
+
+a:visited {
+ color: #D44D2C;
+}
+
+.wy-menu a {
+ color: #b3b3b3;
+}
+
+.wy-menu a:hover {
+ color: #b3b3b3;
+}
+
+/* Default footer text is quite big */
+footer {
+ font-size: 80%;
+}
+
+footer .rst-footer-buttons {
+ font-size: 125%; /* revert footer settings - 1/80% = 125% */
+}
+
+footer p {
+ font-size: 100%;
+}
+
+/* For hidden headers that appear in TOC tree */
+/* see http://stackoverflow.com/a/32363545/3343043 */
+.rst-content .hidden-section {
+ display: none;
+}
+
+nav .hidden-section {
+ display: inherit;
+}
+
+.wy-side-nav-search>div.version {
+ color: #000;
+}
diff --git a/release/2.5/_static/css/theme.css b/release/2.5/_static/css/theme.css
new file mode 100644
index 00000000000..c04db2d2c84
--- /dev/null
+++ b/release/2.5/_static/css/theme.css
@@ -0,0 +1,12594 @@
+@charset "UTF-8";
+/*!
+ * Bootstrap v4.0.0 (https://getbootstrap.com)
+ * Copyright 2011-2018 The Bootstrap Authors
+ * Copyright 2011-2018 Twitter, Inc.
+ * Licensed under MIT (https://github.com/twbs/bootstrap/blob/master/LICENSE)
+ */
+:root {
+ --blue: #007bff;
+ --indigo: #6610f2;
+ --purple: #6f42c1;
+ --pink: #e83e8c;
+ --red: #dc3545;
+ --orange: #fd7e14;
+ --yellow: #ffc107;
+ --green: #28a745;
+ --teal: #20c997;
+ --cyan: #17a2b8;
+ --white: #fff;
+ --gray: #6c757d;
+ --gray-dark: #343a40;
+ --primary: #007bff;
+ --secondary: #6c757d;
+ --success: #28a745;
+ --info: #17a2b8;
+ --warning: #ffc107;
+ --danger: #dc3545;
+ --light: #f8f9fa;
+ --dark: #343a40;
+ --breakpoint-xs: 0;
+ --breakpoint-sm: 576px;
+ --breakpoint-md: 768px;
+ --breakpoint-lg: 992px;
+ --breakpoint-xl: 1200px;
+ --font-family-sans-serif: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, "Helvetica Neue", Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";
+ --font-family-monospace: SFMono-Regular, Menlo, Monaco, Consolas, "Liberation Mono", "Courier New", monospace;
+}
+
+*,
+*::before,
+*::after {
+ -webkit-box-sizing: border-box;
+ box-sizing: border-box;
+}
+
+html {
+ font-family: sans-serif;
+ line-height: 1.15;
+ -webkit-text-size-adjust: 100%;
+ -ms-text-size-adjust: 100%;
+ -ms-overflow-style: scrollbar;
+ -webkit-tap-highlight-color: rgba(0, 0, 0, 0);
+}
+
+@-ms-viewport {
+ width: device-width;
+}
+article, aside, dialog, figcaption, figure, footer, header, hgroup, main, nav, section {
+ display: block;
+}
+
+body {
+ margin: 0;
+ font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, "Helvetica Neue", Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";
+ font-size: 1rem;
+ font-weight: 400;
+ line-height: 1.5;
+ color: #212529;
+ text-align: left;
+ background-color: #fff;
+}
+
+[tabindex="-1"]:focus {
+ outline: 0 !important;
+}
+
+hr {
+ -webkit-box-sizing: content-box;
+ box-sizing: content-box;
+ height: 0;
+ overflow: visible;
+}
+
+h1, h2, h3, h4, h5, h6 {
+ margin-top: 0;
+ margin-bottom: 0.5rem;
+}
+
+p {
+ margin-top: 0;
+ margin-bottom: 1rem;
+}
+
+abbr[title],
+abbr[data-original-title] {
+ text-decoration: underline;
+ -webkit-text-decoration: underline dotted;
+ text-decoration: underline dotted;
+ cursor: help;
+ border-bottom: 0;
+}
+
+address {
+ margin-bottom: 1rem;
+ font-style: normal;
+ line-height: inherit;
+}
+
+ol,
+ul,
+dl {
+ margin-top: 0;
+ margin-bottom: 1rem;
+}
+
+ol ol,
+ul ul,
+ol ul,
+ul ol {
+ margin-bottom: 0;
+}
+
+dt {
+ font-weight: 700;
+}
+
+dd {
+ margin-bottom: .5rem;
+ margin-left: 0;
+}
+
+blockquote {
+ margin: 0 0 1rem;
+}
+
+dfn {
+ font-style: italic;
+}
+
+b,
+strong {
+ font-weight: bolder;
+}
+
+small {
+ font-size: 80%;
+}
+
+sub,
+sup {
+ position: relative;
+ font-size: 75%;
+ line-height: 0;
+ vertical-align: baseline;
+}
+
+sub {
+ bottom: -.25em;
+}
+
+sup {
+ top: -.5em;
+}
+
+a {
+ color: #007bff;
+ text-decoration: none;
+ background-color: transparent;
+ -webkit-text-decoration-skip: objects;
+}
+a:hover {
+ color: #0056b3;
+ text-decoration: underline;
+}
+
+a:not([href]):not([tabindex]) {
+ color: inherit;
+ text-decoration: none;
+}
+a:not([href]):not([tabindex]):hover, a:not([href]):not([tabindex]):focus {
+ color: inherit;
+ text-decoration: none;
+}
+a:not([href]):not([tabindex]):focus {
+ outline: 0;
+}
+
+pre,
+code,
+kbd,
+samp {
+ font-family: monospace, monospace;
+ font-size: 1em;
+}
+
+pre {
+ margin-top: 0;
+ margin-bottom: 1rem;
+ overflow: auto;
+ -ms-overflow-style: scrollbar;
+}
+
+figure {
+ margin: 0 0 1rem;
+}
+
+img {
+ vertical-align: middle;
+ border-style: none;
+}
+
+svg:not(:root) {
+ overflow: hidden;
+}
+
+table {
+ border-collapse: collapse;
+}
+
+caption {
+ padding-top: 0.75rem;
+ padding-bottom: 0.75rem;
+ color: #6c757d;
+ text-align: left;
+ caption-side: bottom;
+}
+
+th {
+ text-align: inherit;
+}
+
+label {
+ display: inline-block;
+ margin-bottom: .5rem;
+}
+
+button {
+ border-radius: 0;
+}
+
+button:focus {
+ outline: 1px dotted;
+ outline: 5px auto -webkit-focus-ring-color;
+}
+
+input,
+button,
+select,
+optgroup,
+textarea {
+ margin: 0;
+ font-family: inherit;
+ font-size: inherit;
+ line-height: inherit;
+}
+
+button,
+input {
+ overflow: visible;
+}
+
+button,
+select {
+ text-transform: none;
+}
+
+button,
+html [type="button"],
+[type="reset"],
+[type="submit"] {
+ -webkit-appearance: button;
+}
+
+button::-moz-focus-inner,
+[type="button"]::-moz-focus-inner,
+[type="reset"]::-moz-focus-inner,
+[type="submit"]::-moz-focus-inner {
+ padding: 0;
+ border-style: none;
+}
+
+input[type="radio"],
+input[type="checkbox"] {
+ -webkit-box-sizing: border-box;
+ box-sizing: border-box;
+ padding: 0;
+}
+
+input[type="date"],
+input[type="time"],
+input[type="datetime-local"],
+input[type="month"] {
+ -webkit-appearance: listbox;
+}
+
+textarea {
+ overflow: auto;
+ resize: vertical;
+}
+
+fieldset {
+ min-width: 0;
+ padding: 0;
+ margin: 0;
+ border: 0;
+}
+
+legend {
+ display: block;
+ width: 100%;
+ max-width: 100%;
+ padding: 0;
+ margin-bottom: .5rem;
+ font-size: 1.5rem;
+ line-height: inherit;
+ color: inherit;
+ white-space: normal;
+}
+
+progress {
+ vertical-align: baseline;
+}
+
+[type="number"]::-webkit-inner-spin-button,
+[type="number"]::-webkit-outer-spin-button {
+ height: auto;
+}
+
+[type="search"] {
+ outline-offset: -2px;
+ -webkit-appearance: none;
+}
+
+[type="search"]::-webkit-search-cancel-button,
+[type="search"]::-webkit-search-decoration {
+ -webkit-appearance: none;
+}
+
+::-webkit-file-upload-button {
+ font: inherit;
+ -webkit-appearance: button;
+}
+
+output {
+ display: inline-block;
+}
+
+summary {
+ display: list-item;
+ cursor: pointer;
+}
+
+template {
+ display: none;
+}
+
+[hidden] {
+ display: none !important;
+}
+
+h1, h2, h3, h4, h5, h6,
+.h1, .h2, .h3, .h4, .h5, .h6 {
+ margin-bottom: 0.5rem;
+ font-family: inherit;
+ font-weight: 500;
+ line-height: 1.2;
+ color: inherit;
+}
+
+h1, .h1 {
+ font-size: 2.5rem;
+}
+
+h2, .h2 {
+ font-size: 2rem;
+}
+
+h3, .h3 {
+ font-size: 1.75rem;
+}
+
+h4, .h4 {
+ font-size: 1.5rem;
+}
+
+h5, .h5 {
+ font-size: 1.25rem;
+}
+
+h6, .h6 {
+ font-size: 1rem;
+}
+
+.lead {
+ font-size: 1.25rem;
+ font-weight: 300;
+}
+
+.display-1 {
+ font-size: 6rem;
+ font-weight: 300;
+ line-height: 1.2;
+}
+
+.display-2 {
+ font-size: 5.5rem;
+ font-weight: 300;
+ line-height: 1.2;
+}
+
+.display-3 {
+ font-size: 4.5rem;
+ font-weight: 300;
+ line-height: 1.2;
+}
+
+.display-4 {
+ font-size: 3.5rem;
+ font-weight: 300;
+ line-height: 1.2;
+}
+
+hr {
+ margin-top: 1rem;
+ margin-bottom: 1rem;
+ border: 0;
+ border-top: 1px solid rgba(0, 0, 0, 0.1);
+}
+
+small,
+.small {
+ font-size: 80%;
+ font-weight: 400;
+}
+
+mark,
+.mark {
+ padding: 0.2em;
+ background-color: #fcf8e3;
+}
+
+.list-unstyled {
+ padding-left: 0;
+ list-style: none;
+}
+
+.list-inline {
+ padding-left: 0;
+ list-style: none;
+}
+
+.list-inline-item {
+ display: inline-block;
+}
+.list-inline-item:not(:last-child) {
+ margin-right: 0.5rem;
+}
+
+.initialism {
+ font-size: 90%;
+ text-transform: uppercase;
+}
+
+.blockquote {
+ margin-bottom: 1rem;
+ font-size: 1.25rem;
+}
+
+.blockquote-footer {
+ display: block;
+ font-size: 80%;
+ color: #6c757d;
+}
+.blockquote-footer::before {
+ content: "\2014 \00A0";
+}
+
+.img-fluid {
+ max-width: 100%;
+ height: auto;
+}
+
+.img-thumbnail {
+ padding: 0.25rem;
+ background-color: #fff;
+ border: 1px solid #dee2e6;
+ border-radius: 0.25rem;
+ max-width: 100%;
+ height: auto;
+}
+
+.figure {
+ display: inline-block;
+}
+
+.figure-img {
+ margin-bottom: 0.5rem;
+ line-height: 1;
+}
+
+.figure-caption {
+ font-size: 90%;
+ color: #6c757d;
+}
+
+code,
+kbd,
+pre,
+samp {
+ font-family: SFMono-Regular, Menlo, Monaco, Consolas, "Liberation Mono", "Courier New", monospace;
+}
+
+code {
+ font-size: 87.5%;
+ color: #e83e8c;
+ word-break: break-word;
+}
+a > code {
+ color: inherit;
+}
+
+kbd {
+ padding: 0.2rem 0.4rem;
+ font-size: 87.5%;
+ color: #fff;
+ background-color: #212529;
+ border-radius: 0.2rem;
+}
+kbd kbd {
+ padding: 0;
+ font-size: 100%;
+ font-weight: 700;
+}
+
+pre {
+ display: block;
+ font-size: 87.5%;
+ color: #212529;
+}
+pre code {
+ font-size: inherit;
+ color: inherit;
+ word-break: normal;
+}
+
+.pre-scrollable {
+ max-height: 340px;
+ overflow-y: scroll;
+}
+
+.container {
+ width: 100%;
+ padding-right: 15px;
+ padding-left: 15px;
+ margin-right: auto;
+ margin-left: auto;
+}
+@media (min-width: 576px) {
+ .container {
+ max-width: 540px;
+ }
+}
+@media (min-width: 768px) {
+ .container {
+ max-width: 720px;
+ }
+}
+@media (min-width: 992px) {
+ .container {
+ max-width: 960px;
+ }
+}
+@media (min-width: 1200px) {
+ .container {
+ max-width: 1140px;
+ }
+}
+
+.container-fluid {
+ width: 100%;
+ padding-right: 15px;
+ padding-left: 15px;
+ margin-right: auto;
+ margin-left: auto;
+}
+
+.row {
+ display: -webkit-box;
+ display: -ms-flexbox;
+ display: flex;
+ -ms-flex-wrap: wrap;
+ flex-wrap: wrap;
+ margin-right: -15px;
+ margin-left: -15px;
+}
+
+.no-gutters {
+ margin-right: 0;
+ margin-left: 0;
+}
+.no-gutters > .col,
+.no-gutters > [class*="col-"] {
+ padding-right: 0;
+ padding-left: 0;
+}
+
+.col-1, .col-2, .col-3, .col-4, .col-5, .col-6, .col-7, .col-8, .col-9, .col-10, .col-11, .col-12, .col,
+.col-auto, .col-sm-1, .col-sm-2, .col-sm-3, .col-sm-4, .col-sm-5, .col-sm-6, .col-sm-7, .col-sm-8, .col-sm-9, .col-sm-10, .col-sm-11, .col-sm-12, .col-sm,
+.col-sm-auto, .col-md-1, .col-md-2, .col-md-3, .col-md-4, .col-md-5, .col-md-6, .col-md-7, .col-md-8, .col-md-9, .col-md-10, .col-md-11, .col-md-12, .col-md,
+.col-md-auto, .col-lg-1, .col-lg-2, .col-lg-3, .col-lg-4, .col-lg-5, .col-lg-6, .col-lg-7, .col-lg-8, .col-lg-9, .col-lg-10, .col-lg-11, .col-lg-12, .col-lg,
+.col-lg-auto, .col-xl-1, .col-xl-2, .col-xl-3, .col-xl-4, .col-xl-5, .col-xl-6, .col-xl-7, .col-xl-8, .col-xl-9, .col-xl-10, .col-xl-11, .col-xl-12, .col-xl,
+.col-xl-auto {
+ position: relative;
+ width: 100%;
+ min-height: 1px;
+ padding-right: 15px;
+ padding-left: 15px;
+}
+
+.col {
+ -ms-flex-preferred-size: 0;
+ flex-basis: 0;
+ -webkit-box-flex: 1;
+ -ms-flex-positive: 1;
+ flex-grow: 1;
+ max-width: 100%;
+}
+
+.col-auto {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 auto;
+ flex: 0 0 auto;
+ width: auto;
+ max-width: none;
+}
+
+.col-1 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 8.3333333333%;
+ flex: 0 0 8.3333333333%;
+ max-width: 8.3333333333%;
+}
+
+.col-2 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 16.6666666667%;
+ flex: 0 0 16.6666666667%;
+ max-width: 16.6666666667%;
+}
+
+.col-3 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 25%;
+ flex: 0 0 25%;
+ max-width: 25%;
+}
+
+.col-4 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 33.3333333333%;
+ flex: 0 0 33.3333333333%;
+ max-width: 33.3333333333%;
+}
+
+.col-5 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 41.6666666667%;
+ flex: 0 0 41.6666666667%;
+ max-width: 41.6666666667%;
+}
+
+.col-6 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 50%;
+ flex: 0 0 50%;
+ max-width: 50%;
+}
+
+.col-7 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 58.3333333333%;
+ flex: 0 0 58.3333333333%;
+ max-width: 58.3333333333%;
+}
+
+.col-8 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 66.6666666667%;
+ flex: 0 0 66.6666666667%;
+ max-width: 66.6666666667%;
+}
+
+.col-9 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 75%;
+ flex: 0 0 75%;
+ max-width: 75%;
+}
+
+.col-10 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 83.3333333333%;
+ flex: 0 0 83.3333333333%;
+ max-width: 83.3333333333%;
+}
+
+.col-11 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 91.6666666667%;
+ flex: 0 0 91.6666666667%;
+ max-width: 91.6666666667%;
+}
+
+.col-12 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 100%;
+ flex: 0 0 100%;
+ max-width: 100%;
+}
+
+.order-first {
+ -webkit-box-ordinal-group: 0;
+ -ms-flex-order: -1;
+ order: -1;
+}
+
+.order-last {
+ -webkit-box-ordinal-group: 14;
+ -ms-flex-order: 13;
+ order: 13;
+}
+
+.order-0 {
+ -webkit-box-ordinal-group: 1;
+ -ms-flex-order: 0;
+ order: 0;
+}
+
+.order-1 {
+ -webkit-box-ordinal-group: 2;
+ -ms-flex-order: 1;
+ order: 1;
+}
+
+.order-2 {
+ -webkit-box-ordinal-group: 3;
+ -ms-flex-order: 2;
+ order: 2;
+}
+
+.order-3 {
+ -webkit-box-ordinal-group: 4;
+ -ms-flex-order: 3;
+ order: 3;
+}
+
+.order-4 {
+ -webkit-box-ordinal-group: 5;
+ -ms-flex-order: 4;
+ order: 4;
+}
+
+.order-5 {
+ -webkit-box-ordinal-group: 6;
+ -ms-flex-order: 5;
+ order: 5;
+}
+
+.order-6 {
+ -webkit-box-ordinal-group: 7;
+ -ms-flex-order: 6;
+ order: 6;
+}
+
+.order-7 {
+ -webkit-box-ordinal-group: 8;
+ -ms-flex-order: 7;
+ order: 7;
+}
+
+.order-8 {
+ -webkit-box-ordinal-group: 9;
+ -ms-flex-order: 8;
+ order: 8;
+}
+
+.order-9 {
+ -webkit-box-ordinal-group: 10;
+ -ms-flex-order: 9;
+ order: 9;
+}
+
+.order-10 {
+ -webkit-box-ordinal-group: 11;
+ -ms-flex-order: 10;
+ order: 10;
+}
+
+.order-11 {
+ -webkit-box-ordinal-group: 12;
+ -ms-flex-order: 11;
+ order: 11;
+}
+
+.order-12 {
+ -webkit-box-ordinal-group: 13;
+ -ms-flex-order: 12;
+ order: 12;
+}
+
+.offset-1 {
+ margin-left: 8.3333333333%;
+}
+
+.offset-2 {
+ margin-left: 16.6666666667%;
+}
+
+.offset-3 {
+ margin-left: 25%;
+}
+
+.offset-4 {
+ margin-left: 33.3333333333%;
+}
+
+.offset-5 {
+ margin-left: 41.6666666667%;
+}
+
+.offset-6 {
+ margin-left: 50%;
+}
+
+.offset-7 {
+ margin-left: 58.3333333333%;
+}
+
+.offset-8 {
+ margin-left: 66.6666666667%;
+}
+
+.offset-9 {
+ margin-left: 75%;
+}
+
+.offset-10 {
+ margin-left: 83.3333333333%;
+}
+
+.offset-11 {
+ margin-left: 91.6666666667%;
+}
+
+@media (min-width: 576px) {
+ .col-sm {
+ -ms-flex-preferred-size: 0;
+ flex-basis: 0;
+ -webkit-box-flex: 1;
+ -ms-flex-positive: 1;
+ flex-grow: 1;
+ max-width: 100%;
+ }
+
+ .col-sm-auto {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 auto;
+ flex: 0 0 auto;
+ width: auto;
+ max-width: none;
+ }
+
+ .col-sm-1 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 8.3333333333%;
+ flex: 0 0 8.3333333333%;
+ max-width: 8.3333333333%;
+ }
+
+ .col-sm-2 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 16.6666666667%;
+ flex: 0 0 16.6666666667%;
+ max-width: 16.6666666667%;
+ }
+
+ .col-sm-3 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 25%;
+ flex: 0 0 25%;
+ max-width: 25%;
+ }
+
+ .col-sm-4 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 33.3333333333%;
+ flex: 0 0 33.3333333333%;
+ max-width: 33.3333333333%;
+ }
+
+ .col-sm-5 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 41.6666666667%;
+ flex: 0 0 41.6666666667%;
+ max-width: 41.6666666667%;
+ }
+
+ .col-sm-6 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 50%;
+ flex: 0 0 50%;
+ max-width: 50%;
+ }
+
+ .col-sm-7 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 58.3333333333%;
+ flex: 0 0 58.3333333333%;
+ max-width: 58.3333333333%;
+ }
+
+ .col-sm-8 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 66.6666666667%;
+ flex: 0 0 66.6666666667%;
+ max-width: 66.6666666667%;
+ }
+
+ .col-sm-9 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 75%;
+ flex: 0 0 75%;
+ max-width: 75%;
+ }
+
+ .col-sm-10 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 83.3333333333%;
+ flex: 0 0 83.3333333333%;
+ max-width: 83.3333333333%;
+ }
+
+ .col-sm-11 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 91.6666666667%;
+ flex: 0 0 91.6666666667%;
+ max-width: 91.6666666667%;
+ }
+
+ .col-sm-12 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 100%;
+ flex: 0 0 100%;
+ max-width: 100%;
+ }
+
+ .order-sm-first {
+ -webkit-box-ordinal-group: 0;
+ -ms-flex-order: -1;
+ order: -1;
+ }
+
+ .order-sm-last {
+ -webkit-box-ordinal-group: 14;
+ -ms-flex-order: 13;
+ order: 13;
+ }
+
+ .order-sm-0 {
+ -webkit-box-ordinal-group: 1;
+ -ms-flex-order: 0;
+ order: 0;
+ }
+
+ .order-sm-1 {
+ -webkit-box-ordinal-group: 2;
+ -ms-flex-order: 1;
+ order: 1;
+ }
+
+ .order-sm-2 {
+ -webkit-box-ordinal-group: 3;
+ -ms-flex-order: 2;
+ order: 2;
+ }
+
+ .order-sm-3 {
+ -webkit-box-ordinal-group: 4;
+ -ms-flex-order: 3;
+ order: 3;
+ }
+
+ .order-sm-4 {
+ -webkit-box-ordinal-group: 5;
+ -ms-flex-order: 4;
+ order: 4;
+ }
+
+ .order-sm-5 {
+ -webkit-box-ordinal-group: 6;
+ -ms-flex-order: 5;
+ order: 5;
+ }
+
+ .order-sm-6 {
+ -webkit-box-ordinal-group: 7;
+ -ms-flex-order: 6;
+ order: 6;
+ }
+
+ .order-sm-7 {
+ -webkit-box-ordinal-group: 8;
+ -ms-flex-order: 7;
+ order: 7;
+ }
+
+ .order-sm-8 {
+ -webkit-box-ordinal-group: 9;
+ -ms-flex-order: 8;
+ order: 8;
+ }
+
+ .order-sm-9 {
+ -webkit-box-ordinal-group: 10;
+ -ms-flex-order: 9;
+ order: 9;
+ }
+
+ .order-sm-10 {
+ -webkit-box-ordinal-group: 11;
+ -ms-flex-order: 10;
+ order: 10;
+ }
+
+ .order-sm-11 {
+ -webkit-box-ordinal-group: 12;
+ -ms-flex-order: 11;
+ order: 11;
+ }
+
+ .order-sm-12 {
+ -webkit-box-ordinal-group: 13;
+ -ms-flex-order: 12;
+ order: 12;
+ }
+
+ .offset-sm-0 {
+ margin-left: 0;
+ }
+
+ .offset-sm-1 {
+ margin-left: 8.3333333333%;
+ }
+
+ .offset-sm-2 {
+ margin-left: 16.6666666667%;
+ }
+
+ .offset-sm-3 {
+ margin-left: 25%;
+ }
+
+ .offset-sm-4 {
+ margin-left: 33.3333333333%;
+ }
+
+ .offset-sm-5 {
+ margin-left: 41.6666666667%;
+ }
+
+ .offset-sm-6 {
+ margin-left: 50%;
+ }
+
+ .offset-sm-7 {
+ margin-left: 58.3333333333%;
+ }
+
+ .offset-sm-8 {
+ margin-left: 66.6666666667%;
+ }
+
+ .offset-sm-9 {
+ margin-left: 75%;
+ }
+
+ .offset-sm-10 {
+ margin-left: 83.3333333333%;
+ }
+
+ .offset-sm-11 {
+ margin-left: 91.6666666667%;
+ }
+}
+@media (min-width: 768px) {
+ .col-md {
+ -ms-flex-preferred-size: 0;
+ flex-basis: 0;
+ -webkit-box-flex: 1;
+ -ms-flex-positive: 1;
+ flex-grow: 1;
+ max-width: 100%;
+ }
+
+ .col-md-auto {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 auto;
+ flex: 0 0 auto;
+ width: auto;
+ max-width: none;
+ }
+
+ .col-md-1 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 8.3333333333%;
+ flex: 0 0 8.3333333333%;
+ max-width: 8.3333333333%;
+ }
+
+ .col-md-2 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 16.6666666667%;
+ flex: 0 0 16.6666666667%;
+ max-width: 16.6666666667%;
+ }
+
+ .col-md-3 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 25%;
+ flex: 0 0 25%;
+ max-width: 25%;
+ }
+
+ .col-md-4 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 33.3333333333%;
+ flex: 0 0 33.3333333333%;
+ max-width: 33.3333333333%;
+ }
+
+ .col-md-5 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 41.6666666667%;
+ flex: 0 0 41.6666666667%;
+ max-width: 41.6666666667%;
+ }
+
+ .col-md-6 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 50%;
+ flex: 0 0 50%;
+ max-width: 50%;
+ }
+
+ .col-md-7 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 58.3333333333%;
+ flex: 0 0 58.3333333333%;
+ max-width: 58.3333333333%;
+ }
+
+ .col-md-8 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 66.6666666667%;
+ flex: 0 0 66.6666666667%;
+ max-width: 66.6666666667%;
+ }
+
+ .col-md-9 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 75%;
+ flex: 0 0 75%;
+ max-width: 75%;
+ }
+
+ .col-md-10 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 83.3333333333%;
+ flex: 0 0 83.3333333333%;
+ max-width: 83.3333333333%;
+ }
+
+ .col-md-11 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 91.6666666667%;
+ flex: 0 0 91.6666666667%;
+ max-width: 91.6666666667%;
+ }
+
+ .col-md-12 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 100%;
+ flex: 0 0 100%;
+ max-width: 100%;
+ }
+
+ .order-md-first {
+ -webkit-box-ordinal-group: 0;
+ -ms-flex-order: -1;
+ order: -1;
+ }
+
+ .order-md-last {
+ -webkit-box-ordinal-group: 14;
+ -ms-flex-order: 13;
+ order: 13;
+ }
+
+ .order-md-0 {
+ -webkit-box-ordinal-group: 1;
+ -ms-flex-order: 0;
+ order: 0;
+ }
+
+ .order-md-1 {
+ -webkit-box-ordinal-group: 2;
+ -ms-flex-order: 1;
+ order: 1;
+ }
+
+ .order-md-2 {
+ -webkit-box-ordinal-group: 3;
+ -ms-flex-order: 2;
+ order: 2;
+ }
+
+ .order-md-3 {
+ -webkit-box-ordinal-group: 4;
+ -ms-flex-order: 3;
+ order: 3;
+ }
+
+ .order-md-4 {
+ -webkit-box-ordinal-group: 5;
+ -ms-flex-order: 4;
+ order: 4;
+ }
+
+ .order-md-5 {
+ -webkit-box-ordinal-group: 6;
+ -ms-flex-order: 5;
+ order: 5;
+ }
+
+ .order-md-6 {
+ -webkit-box-ordinal-group: 7;
+ -ms-flex-order: 6;
+ order: 6;
+ }
+
+ .order-md-7 {
+ -webkit-box-ordinal-group: 8;
+ -ms-flex-order: 7;
+ order: 7;
+ }
+
+ .order-md-8 {
+ -webkit-box-ordinal-group: 9;
+ -ms-flex-order: 8;
+ order: 8;
+ }
+
+ .order-md-9 {
+ -webkit-box-ordinal-group: 10;
+ -ms-flex-order: 9;
+ order: 9;
+ }
+
+ .order-md-10 {
+ -webkit-box-ordinal-group: 11;
+ -ms-flex-order: 10;
+ order: 10;
+ }
+
+ .order-md-11 {
+ -webkit-box-ordinal-group: 12;
+ -ms-flex-order: 11;
+ order: 11;
+ }
+
+ .order-md-12 {
+ -webkit-box-ordinal-group: 13;
+ -ms-flex-order: 12;
+ order: 12;
+ }
+
+ .offset-md-0 {
+ margin-left: 0;
+ }
+
+ .offset-md-1 {
+ margin-left: 8.3333333333%;
+ }
+
+ .offset-md-2 {
+ margin-left: 16.6666666667%;
+ }
+
+ .offset-md-3 {
+ margin-left: 25%;
+ }
+
+ .offset-md-4 {
+ margin-left: 33.3333333333%;
+ }
+
+ .offset-md-5 {
+ margin-left: 41.6666666667%;
+ }
+
+ .offset-md-6 {
+ margin-left: 50%;
+ }
+
+ .offset-md-7 {
+ margin-left: 58.3333333333%;
+ }
+
+ .offset-md-8 {
+ margin-left: 66.6666666667%;
+ }
+
+ .offset-md-9 {
+ margin-left: 75%;
+ }
+
+ .offset-md-10 {
+ margin-left: 83.3333333333%;
+ }
+
+ .offset-md-11 {
+ margin-left: 91.6666666667%;
+ }
+}
+@media (min-width: 992px) {
+ .col-lg {
+ -ms-flex-preferred-size: 0;
+ flex-basis: 0;
+ -webkit-box-flex: 1;
+ -ms-flex-positive: 1;
+ flex-grow: 1;
+ max-width: 100%;
+ }
+
+ .col-lg-auto {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 auto;
+ flex: 0 0 auto;
+ width: auto;
+ max-width: none;
+ }
+
+ .col-lg-1 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 8.3333333333%;
+ flex: 0 0 8.3333333333%;
+ max-width: 8.3333333333%;
+ }
+
+ .col-lg-2 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 16.6666666667%;
+ flex: 0 0 16.6666666667%;
+ max-width: 16.6666666667%;
+ }
+
+ .col-lg-3 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 25%;
+ flex: 0 0 25%;
+ max-width: 25%;
+ }
+
+ .col-lg-4 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 33.3333333333%;
+ flex: 0 0 33.3333333333%;
+ max-width: 33.3333333333%;
+ }
+
+ .col-lg-5 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 41.6666666667%;
+ flex: 0 0 41.6666666667%;
+ max-width: 41.6666666667%;
+ }
+
+ .col-lg-6 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 50%;
+ flex: 0 0 50%;
+ max-width: 50%;
+ }
+
+ .col-lg-7 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 58.3333333333%;
+ flex: 0 0 58.3333333333%;
+ max-width: 58.3333333333%;
+ }
+
+ .col-lg-8 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 66.6666666667%;
+ flex: 0 0 66.6666666667%;
+ max-width: 66.6666666667%;
+ }
+
+ .col-lg-9 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 75%;
+ flex: 0 0 75%;
+ max-width: 75%;
+ }
+
+ .col-lg-10 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 83.3333333333%;
+ flex: 0 0 83.3333333333%;
+ max-width: 83.3333333333%;
+ }
+
+ .col-lg-11 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 91.6666666667%;
+ flex: 0 0 91.6666666667%;
+ max-width: 91.6666666667%;
+ }
+
+ .col-lg-12 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 100%;
+ flex: 0 0 100%;
+ max-width: 100%;
+ }
+
+ .order-lg-first {
+ -webkit-box-ordinal-group: 0;
+ -ms-flex-order: -1;
+ order: -1;
+ }
+
+ .order-lg-last {
+ -webkit-box-ordinal-group: 14;
+ -ms-flex-order: 13;
+ order: 13;
+ }
+
+ .order-lg-0 {
+ -webkit-box-ordinal-group: 1;
+ -ms-flex-order: 0;
+ order: 0;
+ }
+
+ .order-lg-1 {
+ -webkit-box-ordinal-group: 2;
+ -ms-flex-order: 1;
+ order: 1;
+ }
+
+ .order-lg-2 {
+ -webkit-box-ordinal-group: 3;
+ -ms-flex-order: 2;
+ order: 2;
+ }
+
+ .order-lg-3 {
+ -webkit-box-ordinal-group: 4;
+ -ms-flex-order: 3;
+ order: 3;
+ }
+
+ .order-lg-4 {
+ -webkit-box-ordinal-group: 5;
+ -ms-flex-order: 4;
+ order: 4;
+ }
+
+ .order-lg-5 {
+ -webkit-box-ordinal-group: 6;
+ -ms-flex-order: 5;
+ order: 5;
+ }
+
+ .order-lg-6 {
+ -webkit-box-ordinal-group: 7;
+ -ms-flex-order: 6;
+ order: 6;
+ }
+
+ .order-lg-7 {
+ -webkit-box-ordinal-group: 8;
+ -ms-flex-order: 7;
+ order: 7;
+ }
+
+ .order-lg-8 {
+ -webkit-box-ordinal-group: 9;
+ -ms-flex-order: 8;
+ order: 8;
+ }
+
+ .order-lg-9 {
+ -webkit-box-ordinal-group: 10;
+ -ms-flex-order: 9;
+ order: 9;
+ }
+
+ .order-lg-10 {
+ -webkit-box-ordinal-group: 11;
+ -ms-flex-order: 10;
+ order: 10;
+ }
+
+ .order-lg-11 {
+ -webkit-box-ordinal-group: 12;
+ -ms-flex-order: 11;
+ order: 11;
+ }
+
+ .order-lg-12 {
+ -webkit-box-ordinal-group: 13;
+ -ms-flex-order: 12;
+ order: 12;
+ }
+
+ .offset-lg-0 {
+ margin-left: 0;
+ }
+
+ .offset-lg-1 {
+ margin-left: 8.3333333333%;
+ }
+
+ .offset-lg-2 {
+ margin-left: 16.6666666667%;
+ }
+
+ .offset-lg-3 {
+ margin-left: 25%;
+ }
+
+ .offset-lg-4 {
+ margin-left: 33.3333333333%;
+ }
+
+ .offset-lg-5 {
+ margin-left: 41.6666666667%;
+ }
+
+ .offset-lg-6 {
+ margin-left: 50%;
+ }
+
+ .offset-lg-7 {
+ margin-left: 58.3333333333%;
+ }
+
+ .offset-lg-8 {
+ margin-left: 66.6666666667%;
+ }
+
+ .offset-lg-9 {
+ margin-left: 75%;
+ }
+
+ .offset-lg-10 {
+ margin-left: 83.3333333333%;
+ }
+
+ .offset-lg-11 {
+ margin-left: 91.6666666667%;
+ }
+}
+@media (min-width: 1200px) {
+ .col-xl {
+ -ms-flex-preferred-size: 0;
+ flex-basis: 0;
+ -webkit-box-flex: 1;
+ -ms-flex-positive: 1;
+ flex-grow: 1;
+ max-width: 100%;
+ }
+
+ .col-xl-auto {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 auto;
+ flex: 0 0 auto;
+ width: auto;
+ max-width: none;
+ }
+
+ .col-xl-1 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 8.3333333333%;
+ flex: 0 0 8.3333333333%;
+ max-width: 8.3333333333%;
+ }
+
+ .col-xl-2 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 16.6666666667%;
+ flex: 0 0 16.6666666667%;
+ max-width: 16.6666666667%;
+ }
+
+ .col-xl-3 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 25%;
+ flex: 0 0 25%;
+ max-width: 25%;
+ }
+
+ .col-xl-4 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 33.3333333333%;
+ flex: 0 0 33.3333333333%;
+ max-width: 33.3333333333%;
+ }
+
+ .col-xl-5 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 41.6666666667%;
+ flex: 0 0 41.6666666667%;
+ max-width: 41.6666666667%;
+ }
+
+ .col-xl-6 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 50%;
+ flex: 0 0 50%;
+ max-width: 50%;
+ }
+
+ .col-xl-7 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 58.3333333333%;
+ flex: 0 0 58.3333333333%;
+ max-width: 58.3333333333%;
+ }
+
+ .col-xl-8 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 66.6666666667%;
+ flex: 0 0 66.6666666667%;
+ max-width: 66.6666666667%;
+ }
+
+ .col-xl-9 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 75%;
+ flex: 0 0 75%;
+ max-width: 75%;
+ }
+
+ .col-xl-10 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 83.3333333333%;
+ flex: 0 0 83.3333333333%;
+ max-width: 83.3333333333%;
+ }
+
+ .col-xl-11 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 91.6666666667%;
+ flex: 0 0 91.6666666667%;
+ max-width: 91.6666666667%;
+ }
+
+ .col-xl-12 {
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 100%;
+ flex: 0 0 100%;
+ max-width: 100%;
+ }
+
+ .order-xl-first {
+ -webkit-box-ordinal-group: 0;
+ -ms-flex-order: -1;
+ order: -1;
+ }
+
+ .order-xl-last {
+ -webkit-box-ordinal-group: 14;
+ -ms-flex-order: 13;
+ order: 13;
+ }
+
+ .order-xl-0 {
+ -webkit-box-ordinal-group: 1;
+ -ms-flex-order: 0;
+ order: 0;
+ }
+
+ .order-xl-1 {
+ -webkit-box-ordinal-group: 2;
+ -ms-flex-order: 1;
+ order: 1;
+ }
+
+ .order-xl-2 {
+ -webkit-box-ordinal-group: 3;
+ -ms-flex-order: 2;
+ order: 2;
+ }
+
+ .order-xl-3 {
+ -webkit-box-ordinal-group: 4;
+ -ms-flex-order: 3;
+ order: 3;
+ }
+
+ .order-xl-4 {
+ -webkit-box-ordinal-group: 5;
+ -ms-flex-order: 4;
+ order: 4;
+ }
+
+ .order-xl-5 {
+ -webkit-box-ordinal-group: 6;
+ -ms-flex-order: 5;
+ order: 5;
+ }
+
+ .order-xl-6 {
+ -webkit-box-ordinal-group: 7;
+ -ms-flex-order: 6;
+ order: 6;
+ }
+
+ .order-xl-7 {
+ -webkit-box-ordinal-group: 8;
+ -ms-flex-order: 7;
+ order: 7;
+ }
+
+ .order-xl-8 {
+ -webkit-box-ordinal-group: 9;
+ -ms-flex-order: 8;
+ order: 8;
+ }
+
+ .order-xl-9 {
+ -webkit-box-ordinal-group: 10;
+ -ms-flex-order: 9;
+ order: 9;
+ }
+
+ .order-xl-10 {
+ -webkit-box-ordinal-group: 11;
+ -ms-flex-order: 10;
+ order: 10;
+ }
+
+ .order-xl-11 {
+ -webkit-box-ordinal-group: 12;
+ -ms-flex-order: 11;
+ order: 11;
+ }
+
+ .order-xl-12 {
+ -webkit-box-ordinal-group: 13;
+ -ms-flex-order: 12;
+ order: 12;
+ }
+
+ .offset-xl-0 {
+ margin-left: 0;
+ }
+
+ .offset-xl-1 {
+ margin-left: 8.3333333333%;
+ }
+
+ .offset-xl-2 {
+ margin-left: 16.6666666667%;
+ }
+
+ .offset-xl-3 {
+ margin-left: 25%;
+ }
+
+ .offset-xl-4 {
+ margin-left: 33.3333333333%;
+ }
+
+ .offset-xl-5 {
+ margin-left: 41.6666666667%;
+ }
+
+ .offset-xl-6 {
+ margin-left: 50%;
+ }
+
+ .offset-xl-7 {
+ margin-left: 58.3333333333%;
+ }
+
+ .offset-xl-8 {
+ margin-left: 66.6666666667%;
+ }
+
+ .offset-xl-9 {
+ margin-left: 75%;
+ }
+
+ .offset-xl-10 {
+ margin-left: 83.3333333333%;
+ }
+
+ .offset-xl-11 {
+ margin-left: 91.6666666667%;
+ }
+}
+.table {
+ width: 100%;
+ max-width: 100%;
+ margin-bottom: 1rem;
+ background-color: transparent;
+}
+.table th,
+.table td {
+ padding: 0.75rem;
+ vertical-align: top;
+ border-top: 1px solid #dee2e6;
+}
+.table thead th {
+ vertical-align: bottom;
+ border-bottom: 2px solid #dee2e6;
+}
+.table tbody + tbody {
+ border-top: 2px solid #dee2e6;
+}
+.table .table {
+ background-color: #fff;
+}
+
+.table-sm th,
+.table-sm td {
+ padding: 0.3rem;
+}
+
+.table-bordered {
+ border: 1px solid #dee2e6;
+}
+.table-bordered th,
+.table-bordered td {
+ border: 1px solid #dee2e6;
+}
+.table-bordered thead th,
+.table-bordered thead td {
+ border-bottom-width: 2px;
+}
+
+.table-striped tbody tr:nth-of-type(odd) {
+ background-color: rgba(0, 0, 0, 0.05);
+}
+
+.table-hover tbody tr:hover {
+ background-color: rgba(0, 0, 0, 0.075);
+}
+
+.table-primary,
+.table-primary > th,
+.table-primary > td {
+ background-color: #b8daff;
+}
+
+.table-hover .table-primary:hover {
+ background-color: #9fcdff;
+}
+.table-hover .table-primary:hover > td,
+.table-hover .table-primary:hover > th {
+ background-color: #9fcdff;
+}
+
+.table-secondary,
+.table-secondary > th,
+.table-secondary > td {
+ background-color: #d6d8db;
+}
+
+.table-hover .table-secondary:hover {
+ background-color: #c8cbcf;
+}
+.table-hover .table-secondary:hover > td,
+.table-hover .table-secondary:hover > th {
+ background-color: #c8cbcf;
+}
+
+.table-success,
+.table-success > th,
+.table-success > td {
+ background-color: #c3e6cb;
+}
+
+.table-hover .table-success:hover {
+ background-color: #b1dfbb;
+}
+.table-hover .table-success:hover > td,
+.table-hover .table-success:hover > th {
+ background-color: #b1dfbb;
+}
+
+.table-info,
+.table-info > th,
+.table-info > td {
+ background-color: #bee5eb;
+}
+
+.table-hover .table-info:hover {
+ background-color: #abdde5;
+}
+.table-hover .table-info:hover > td,
+.table-hover .table-info:hover > th {
+ background-color: #abdde5;
+}
+
+.table-warning,
+.table-warning > th,
+.table-warning > td {
+ background-color: #ffeeba;
+}
+
+.table-hover .table-warning:hover {
+ background-color: #ffe8a1;
+}
+.table-hover .table-warning:hover > td,
+.table-hover .table-warning:hover > th {
+ background-color: #ffe8a1;
+}
+
+.table-danger,
+.table-danger > th,
+.table-danger > td {
+ background-color: #f5c6cb;
+}
+
+.table-hover .table-danger:hover {
+ background-color: #f1b0b7;
+}
+.table-hover .table-danger:hover > td,
+.table-hover .table-danger:hover > th {
+ background-color: #f1b0b7;
+}
+
+.table-light,
+.table-light > th,
+.table-light > td {
+ background-color: #fdfdfe;
+}
+
+.table-hover .table-light:hover {
+ background-color: #ececf6;
+}
+.table-hover .table-light:hover > td,
+.table-hover .table-light:hover > th {
+ background-color: #ececf6;
+}
+
+.table-dark,
+.table-dark > th,
+.table-dark > td {
+ background-color: #c6c8ca;
+}
+
+.table-hover .table-dark:hover {
+ background-color: #b9bbbe;
+}
+.table-hover .table-dark:hover > td,
+.table-hover .table-dark:hover > th {
+ background-color: #b9bbbe;
+}
+
+.table-active,
+.table-active > th,
+.table-active > td {
+ background-color: rgba(0, 0, 0, 0.075);
+}
+
+.table-hover .table-active:hover {
+ background-color: rgba(0, 0, 0, 0.075);
+}
+.table-hover .table-active:hover > td,
+.table-hover .table-active:hover > th {
+ background-color: rgba(0, 0, 0, 0.075);
+}
+
+.table .thead-dark th {
+ color: #fff;
+ background-color: #212529;
+ border-color: #32383e;
+}
+.table .thead-light th {
+ color: #495057;
+ background-color: #e9ecef;
+ border-color: #dee2e6;
+}
+
+.table-dark {
+ color: #fff;
+ background-color: #212529;
+}
+.table-dark th,
+.table-dark td,
+.table-dark thead th {
+ border-color: #32383e;
+}
+.table-dark.table-bordered {
+ border: 0;
+}
+.table-dark.table-striped tbody tr:nth-of-type(odd) {
+ background-color: rgba(255, 255, 255, 0.05);
+}
+.table-dark.table-hover tbody tr:hover {
+ background-color: rgba(255, 255, 255, 0.075);
+}
+
+@media (max-width: 575.98px) {
+ .table-responsive-sm {
+ display: block;
+ width: 100%;
+ overflow-x: auto;
+ -webkit-overflow-scrolling: touch;
+ -ms-overflow-style: -ms-autohiding-scrollbar;
+ }
+ .table-responsive-sm > .table-bordered {
+ border: 0;
+ }
+}
+@media (max-width: 767.98px) {
+ .table-responsive-md {
+ display: block;
+ width: 100%;
+ overflow-x: auto;
+ -webkit-overflow-scrolling: touch;
+ -ms-overflow-style: -ms-autohiding-scrollbar;
+ }
+ .table-responsive-md > .table-bordered {
+ border: 0;
+ }
+}
+@media (max-width: 991.98px) {
+ .table-responsive-lg {
+ display: block;
+ width: 100%;
+ overflow-x: auto;
+ -webkit-overflow-scrolling: touch;
+ -ms-overflow-style: -ms-autohiding-scrollbar;
+ }
+ .table-responsive-lg > .table-bordered {
+ border: 0;
+ }
+}
+@media (max-width: 1199.98px) {
+ .table-responsive-xl {
+ display: block;
+ width: 100%;
+ overflow-x: auto;
+ -webkit-overflow-scrolling: touch;
+ -ms-overflow-style: -ms-autohiding-scrollbar;
+ }
+ .table-responsive-xl > .table-bordered {
+ border: 0;
+ }
+}
+.table-responsive {
+ display: block;
+ width: 100%;
+ overflow-x: auto;
+ -webkit-overflow-scrolling: touch;
+ -ms-overflow-style: -ms-autohiding-scrollbar;
+}
+.table-responsive > .table-bordered {
+ border: 0;
+}
+
+.form-control {
+ display: block;
+ width: 100%;
+ padding: 0.375rem 0.75rem;
+ font-size: 1rem;
+ line-height: 1.5;
+ color: #495057;
+ background-color: #fff;
+ background-clip: padding-box;
+ border: 1px solid #ced4da;
+ border-radius: 0.25rem;
+ -webkit-transition: border-color 0.15s ease-in-out, -webkit-box-shadow 0.15s ease-in-out;
+ transition: border-color 0.15s ease-in-out, -webkit-box-shadow 0.15s ease-in-out;
+ transition: border-color 0.15s ease-in-out, box-shadow 0.15s ease-in-out;
+ transition: border-color 0.15s ease-in-out, box-shadow 0.15s ease-in-out, -webkit-box-shadow 0.15s ease-in-out;
+}
+.form-control::-ms-expand {
+ background-color: transparent;
+ border: 0;
+}
+.form-control:focus {
+ color: #495057;
+ background-color: #fff;
+ border-color: #80bdff;
+ outline: 0;
+ -webkit-box-shadow: 0 0 0 0.2rem rgba(0, 123, 255, 0.25);
+ box-shadow: 0 0 0 0.2rem rgba(0, 123, 255, 0.25);
+}
+.form-control::-webkit-input-placeholder {
+ color: #6c757d;
+ opacity: 1;
+}
+.form-control::-moz-placeholder {
+ color: #6c757d;
+ opacity: 1;
+}
+.form-control:-ms-input-placeholder {
+ color: #6c757d;
+ opacity: 1;
+}
+.form-control::-ms-input-placeholder {
+ color: #6c757d;
+ opacity: 1;
+}
+.form-control::placeholder {
+ color: #6c757d;
+ opacity: 1;
+}
+.form-control:disabled, .form-control[readonly] {
+ background-color: #e9ecef;
+ opacity: 1;
+}
+
+select.form-control:not([size]):not([multiple]) {
+ height: calc(2.25rem + 2px);
+}
+select.form-control:focus::-ms-value {
+ color: #495057;
+ background-color: #fff;
+}
+
+.form-control-file,
+.form-control-range {
+ display: block;
+ width: 100%;
+}
+
+.col-form-label {
+ padding-top: calc(0.375rem + 1px);
+ padding-bottom: calc(0.375rem + 1px);
+ margin-bottom: 0;
+ font-size: inherit;
+ line-height: 1.5;
+}
+
+.col-form-label-lg {
+ padding-top: calc(0.5rem + 1px);
+ padding-bottom: calc(0.5rem + 1px);
+ font-size: 1.25rem;
+ line-height: 1.5;
+}
+
+.col-form-label-sm {
+ padding-top: calc(0.25rem + 1px);
+ padding-bottom: calc(0.25rem + 1px);
+ font-size: 0.875rem;
+ line-height: 1.5;
+}
+
+.form-control-plaintext {
+ display: block;
+ width: 100%;
+ padding-top: 0.375rem;
+ padding-bottom: 0.375rem;
+ margin-bottom: 0;
+ line-height: 1.5;
+ background-color: transparent;
+ border: solid transparent;
+ border-width: 1px 0;
+}
+.form-control-plaintext.form-control-sm, .input-group-sm > .form-control-plaintext.form-control,
+.input-group-sm > .input-group-prepend > .form-control-plaintext.input-group-text,
+.input-group-sm > .input-group-append > .form-control-plaintext.input-group-text,
+.input-group-sm > .input-group-prepend > .form-control-plaintext.btn,
+.input-group-sm > .input-group-append > .form-control-plaintext.btn, .form-control-plaintext.form-control-lg, .input-group-lg > .form-control-plaintext.form-control,
+.input-group-lg > .input-group-prepend > .form-control-plaintext.input-group-text,
+.input-group-lg > .input-group-append > .form-control-plaintext.input-group-text,
+.input-group-lg > .input-group-prepend > .form-control-plaintext.btn,
+.input-group-lg > .input-group-append > .form-control-plaintext.btn {
+ padding-right: 0;
+ padding-left: 0;
+}
+
+.form-control-sm, .input-group-sm > .form-control,
+.input-group-sm > .input-group-prepend > .input-group-text,
+.input-group-sm > .input-group-append > .input-group-text,
+.input-group-sm > .input-group-prepend > .btn,
+.input-group-sm > .input-group-append > .btn {
+ padding: 0.25rem 0.5rem;
+ font-size: 0.875rem;
+ line-height: 1.5;
+ border-radius: 0.2rem;
+}
+
+select.form-control-sm:not([size]):not([multiple]), .input-group-sm > select.form-control:not([size]):not([multiple]),
+.input-group-sm > .input-group-prepend > select.input-group-text:not([size]):not([multiple]),
+.input-group-sm > .input-group-append > select.input-group-text:not([size]):not([multiple]),
+.input-group-sm > .input-group-prepend > select.btn:not([size]):not([multiple]),
+.input-group-sm > .input-group-append > select.btn:not([size]):not([multiple]) {
+ height: calc(1.8125rem + 2px);
+}
+
+.form-control-lg, .input-group-lg > .form-control,
+.input-group-lg > .input-group-prepend > .input-group-text,
+.input-group-lg > .input-group-append > .input-group-text,
+.input-group-lg > .input-group-prepend > .btn,
+.input-group-lg > .input-group-append > .btn {
+ padding: 0.5rem 1rem;
+ font-size: 1.25rem;
+ line-height: 1.5;
+ border-radius: 0.3rem;
+}
+
+select.form-control-lg:not([size]):not([multiple]), .input-group-lg > select.form-control:not([size]):not([multiple]),
+.input-group-lg > .input-group-prepend > select.input-group-text:not([size]):not([multiple]),
+.input-group-lg > .input-group-append > select.input-group-text:not([size]):not([multiple]),
+.input-group-lg > .input-group-prepend > select.btn:not([size]):not([multiple]),
+.input-group-lg > .input-group-append > select.btn:not([size]):not([multiple]) {
+ height: calc(2.875rem + 2px);
+}
+
+.form-group {
+ margin-bottom: 1rem;
+}
+
+.form-text {
+ display: block;
+ margin-top: 0.25rem;
+}
+
+.form-row {
+ display: -webkit-box;
+ display: -ms-flexbox;
+ display: flex;
+ -ms-flex-wrap: wrap;
+ flex-wrap: wrap;
+ margin-right: -5px;
+ margin-left: -5px;
+}
+.form-row > .col,
+.form-row > [class*="col-"] {
+ padding-right: 5px;
+ padding-left: 5px;
+}
+
+.form-check {
+ position: relative;
+ display: block;
+ padding-left: 1.25rem;
+}
+
+.form-check-input {
+ position: absolute;
+ margin-top: 0.3rem;
+ margin-left: -1.25rem;
+}
+.form-check-input:disabled ~ .form-check-label {
+ color: #6c757d;
+}
+
+.form-check-label {
+ margin-bottom: 0;
+}
+
+.form-check-inline {
+ display: -webkit-inline-box;
+ display: -ms-inline-flexbox;
+ display: inline-flex;
+ -webkit-box-align: center;
+ -ms-flex-align: center;
+ align-items: center;
+ padding-left: 0;
+ margin-right: 0.75rem;
+}
+.form-check-inline .form-check-input {
+ position: static;
+ margin-top: 0;
+ margin-right: 0.3125rem;
+ margin-left: 0;
+}
+
+.valid-feedback {
+ display: none;
+ width: 100%;
+ margin-top: 0.25rem;
+ font-size: 80%;
+ color: #28a745;
+}
+
+.valid-tooltip {
+ position: absolute;
+ top: 100%;
+ z-index: 5;
+ display: none;
+ max-width: 100%;
+ padding: .5rem;
+ margin-top: .1rem;
+ font-size: .875rem;
+ line-height: 1;
+ color: #fff;
+ background-color: rgba(40, 167, 69, 0.8);
+ border-radius: .2rem;
+}
+
+.was-validated .form-control:valid, .form-control.is-valid,
+.was-validated .custom-select:valid,
+.custom-select.is-valid {
+ border-color: #28a745;
+}
+.was-validated .form-control:valid:focus, .form-control.is-valid:focus,
+.was-validated .custom-select:valid:focus,
+.custom-select.is-valid:focus {
+ border-color: #28a745;
+ -webkit-box-shadow: 0 0 0 0.2rem rgba(40, 167, 69, 0.25);
+ box-shadow: 0 0 0 0.2rem rgba(40, 167, 69, 0.25);
+}
+.was-validated .form-control:valid ~ .valid-feedback,
+.was-validated .form-control:valid ~ .valid-tooltip, .form-control.is-valid ~ .valid-feedback,
+.form-control.is-valid ~ .valid-tooltip,
+.was-validated .custom-select:valid ~ .valid-feedback,
+.was-validated .custom-select:valid ~ .valid-tooltip,
+.custom-select.is-valid ~ .valid-feedback,
+.custom-select.is-valid ~ .valid-tooltip {
+ display: block;
+}
+
+.was-validated .form-check-input:valid ~ .form-check-label, .form-check-input.is-valid ~ .form-check-label {
+ color: #28a745;
+}
+.was-validated .form-check-input:valid ~ .valid-feedback,
+.was-validated .form-check-input:valid ~ .valid-tooltip, .form-check-input.is-valid ~ .valid-feedback,
+.form-check-input.is-valid ~ .valid-tooltip {
+ display: block;
+}
+
+.was-validated .custom-control-input:valid ~ .custom-control-label, .custom-control-input.is-valid ~ .custom-control-label {
+ color: #28a745;
+}
+.was-validated .custom-control-input:valid ~ .custom-control-label::before, .custom-control-input.is-valid ~ .custom-control-label::before {
+ background-color: #71dd8a;
+}
+.was-validated .custom-control-input:valid ~ .valid-feedback,
+.was-validated .custom-control-input:valid ~ .valid-tooltip, .custom-control-input.is-valid ~ .valid-feedback,
+.custom-control-input.is-valid ~ .valid-tooltip {
+ display: block;
+}
+.was-validated .custom-control-input:valid:checked ~ .custom-control-label::before, .custom-control-input.is-valid:checked ~ .custom-control-label::before {
+ background-color: #34ce57;
+}
+.was-validated .custom-control-input:valid:focus ~ .custom-control-label::before, .custom-control-input.is-valid:focus ~ .custom-control-label::before {
+ -webkit-box-shadow: 0 0 0 1px #fff, 0 0 0 0.2rem rgba(40, 167, 69, 0.25);
+ box-shadow: 0 0 0 1px #fff, 0 0 0 0.2rem rgba(40, 167, 69, 0.25);
+}
+
+.was-validated .custom-file-input:valid ~ .custom-file-label, .custom-file-input.is-valid ~ .custom-file-label {
+ border-color: #28a745;
+}
+.was-validated .custom-file-input:valid ~ .custom-file-label::before, .custom-file-input.is-valid ~ .custom-file-label::before {
+ border-color: inherit;
+}
+.was-validated .custom-file-input:valid ~ .valid-feedback,
+.was-validated .custom-file-input:valid ~ .valid-tooltip, .custom-file-input.is-valid ~ .valid-feedback,
+.custom-file-input.is-valid ~ .valid-tooltip {
+ display: block;
+}
+.was-validated .custom-file-input:valid:focus ~ .custom-file-label, .custom-file-input.is-valid:focus ~ .custom-file-label {
+ -webkit-box-shadow: 0 0 0 0.2rem rgba(40, 167, 69, 0.25);
+ box-shadow: 0 0 0 0.2rem rgba(40, 167, 69, 0.25);
+}
+
+.invalid-feedback {
+ display: none;
+ width: 100%;
+ margin-top: 0.25rem;
+ font-size: 80%;
+ color: #dc3545;
+}
+
+.invalid-tooltip {
+ position: absolute;
+ top: 100%;
+ z-index: 5;
+ display: none;
+ max-width: 100%;
+ padding: .5rem;
+ margin-top: .1rem;
+ font-size: .875rem;
+ line-height: 1;
+ color: #fff;
+ background-color: rgba(220, 53, 69, 0.8);
+ border-radius: .2rem;
+}
+
+.was-validated .form-control:invalid, .form-control.is-invalid,
+.was-validated .custom-select:invalid,
+.custom-select.is-invalid {
+ border-color: #dc3545;
+}
+.was-validated .form-control:invalid:focus, .form-control.is-invalid:focus,
+.was-validated .custom-select:invalid:focus,
+.custom-select.is-invalid:focus {
+ border-color: #dc3545;
+ -webkit-box-shadow: 0 0 0 0.2rem rgba(220, 53, 69, 0.25);
+ box-shadow: 0 0 0 0.2rem rgba(220, 53, 69, 0.25);
+}
+.was-validated .form-control:invalid ~ .invalid-feedback,
+.was-validated .form-control:invalid ~ .invalid-tooltip, .form-control.is-invalid ~ .invalid-feedback,
+.form-control.is-invalid ~ .invalid-tooltip,
+.was-validated .custom-select:invalid ~ .invalid-feedback,
+.was-validated .custom-select:invalid ~ .invalid-tooltip,
+.custom-select.is-invalid ~ .invalid-feedback,
+.custom-select.is-invalid ~ .invalid-tooltip {
+ display: block;
+}
+
+.was-validated .form-check-input:invalid ~ .form-check-label, .form-check-input.is-invalid ~ .form-check-label {
+ color: #dc3545;
+}
+.was-validated .form-check-input:invalid ~ .invalid-feedback,
+.was-validated .form-check-input:invalid ~ .invalid-tooltip, .form-check-input.is-invalid ~ .invalid-feedback,
+.form-check-input.is-invalid ~ .invalid-tooltip {
+ display: block;
+}
+
+.was-validated .custom-control-input:invalid ~ .custom-control-label, .custom-control-input.is-invalid ~ .custom-control-label {
+ color: #dc3545;
+}
+.was-validated .custom-control-input:invalid ~ .custom-control-label::before, .custom-control-input.is-invalid ~ .custom-control-label::before {
+ background-color: #efa2a9;
+}
+.was-validated .custom-control-input:invalid ~ .invalid-feedback,
+.was-validated .custom-control-input:invalid ~ .invalid-tooltip, .custom-control-input.is-invalid ~ .invalid-feedback,
+.custom-control-input.is-invalid ~ .invalid-tooltip {
+ display: block;
+}
+.was-validated .custom-control-input:invalid:checked ~ .custom-control-label::before, .custom-control-input.is-invalid:checked ~ .custom-control-label::before {
+ background-color: #e4606d;
+}
+.was-validated .custom-control-input:invalid:focus ~ .custom-control-label::before, .custom-control-input.is-invalid:focus ~ .custom-control-label::before {
+ -webkit-box-shadow: 0 0 0 1px #fff, 0 0 0 0.2rem rgba(220, 53, 69, 0.25);
+ box-shadow: 0 0 0 1px #fff, 0 0 0 0.2rem rgba(220, 53, 69, 0.25);
+}
+
+.was-validated .custom-file-input:invalid ~ .custom-file-label, .custom-file-input.is-invalid ~ .custom-file-label {
+ border-color: #dc3545;
+}
+.was-validated .custom-file-input:invalid ~ .custom-file-label::before, .custom-file-input.is-invalid ~ .custom-file-label::before {
+ border-color: inherit;
+}
+.was-validated .custom-file-input:invalid ~ .invalid-feedback,
+.was-validated .custom-file-input:invalid ~ .invalid-tooltip, .custom-file-input.is-invalid ~ .invalid-feedback,
+.custom-file-input.is-invalid ~ .invalid-tooltip {
+ display: block;
+}
+.was-validated .custom-file-input:invalid:focus ~ .custom-file-label, .custom-file-input.is-invalid:focus ~ .custom-file-label {
+ -webkit-box-shadow: 0 0 0 0.2rem rgba(220, 53, 69, 0.25);
+ box-shadow: 0 0 0 0.2rem rgba(220, 53, 69, 0.25);
+}
+
+.form-inline {
+ display: -webkit-box;
+ display: -ms-flexbox;
+ display: flex;
+ -webkit-box-orient: horizontal;
+ -webkit-box-direction: normal;
+ -ms-flex-flow: row wrap;
+ flex-flow: row wrap;
+ -webkit-box-align: center;
+ -ms-flex-align: center;
+ align-items: center;
+}
+.form-inline .form-check {
+ width: 100%;
+}
+@media (min-width: 576px) {
+ .form-inline label {
+ display: -webkit-box;
+ display: -ms-flexbox;
+ display: flex;
+ -webkit-box-align: center;
+ -ms-flex-align: center;
+ align-items: center;
+ -webkit-box-pack: center;
+ -ms-flex-pack: center;
+ justify-content: center;
+ margin-bottom: 0;
+ }
+ .form-inline .form-group {
+ display: -webkit-box;
+ display: -ms-flexbox;
+ display: flex;
+ -webkit-box-flex: 0;
+ -ms-flex: 0 0 auto;
+ flex: 0 0 auto;
+ -webkit-box-orient: horizontal;
+ -webkit-box-direction: normal;
+ -ms-flex-flow: row wrap;
+ flex-flow: row wrap;
+ -webkit-box-align: center;
+ -ms-flex-align: center;
+ align-items: center;
+ margin-bottom: 0;
+ }
+ .form-inline .form-control {
+ display: inline-block;
+ width: auto;
+ vertical-align: middle;
+ }
+ .form-inline .form-control-plaintext {
+ display: inline-block;
+ }
+ .form-inline .input-group {
+ width: auto;
+ }
+ .form-inline .form-check {
+ display: -webkit-box;
+ display: -ms-flexbox;
+ display: flex;
+ -webkit-box-align: center;
+ -ms-flex-align: center;
+ align-items: center;
+ -webkit-box-pack: center;
+ -ms-flex-pack: center;
+ justify-content: center;
+ width: auto;
+ padding-left: 0;
+ }
+ .form-inline .form-check-input {
+ position: relative;
+ margin-top: 0;
+ margin-right: 0.25rem;
+ margin-left: 0;
+ }
+ .form-inline .custom-control {
+ -webkit-box-align: center;
+ -ms-flex-align: center;
+ align-items: center;
+ -webkit-box-pack: center;
+ -ms-flex-pack: center;
+ justify-content: center;
+ }
+ .form-inline .custom-control-label {
+ margin-bottom: 0;
+ }
+}
+
+.btn {
+ display: inline-block;
+ font-weight: 400;
+ text-align: center;
+ white-space: nowrap;
+ vertical-align: middle;
+ -webkit-user-select: none;
+ -moz-user-select: none;
+ -ms-user-select: none;
+ user-select: none;
+ border: 1px solid transparent;
+ padding: 0.375rem 0.75rem;
+ font-size: 1rem;
+ line-height: 1.5;
+ border-radius: 0.25rem;
+ -webkit-transition: color 0.15s ease-in-out, background-color 0.15s ease-in-out, border-color 0.15s ease-in-out, -webkit-box-shadow 0.15s ease-in-out;
+ transition: color 0.15s ease-in-out, background-color 0.15s ease-in-out, border-color 0.15s ease-in-out, -webkit-box-shadow 0.15s ease-in-out;
+ transition: color 0.15s ease-in-out, background-color 0.15s ease-in-out, border-color 0.15s ease-in-out, box-shadow 0.15s ease-in-out;
+ transition: color 0.15s ease-in-out, background-color 0.15s ease-in-out, border-color 0.15s ease-in-out, box-shadow 0.15s ease-in-out, -webkit-box-shadow 0.15s ease-in-out;
+}
+.btn:hover, .btn:focus {
+ text-decoration: none;
+}
+.btn:focus, .btn.focus {
+ outline: 0;
+ -webkit-box-shadow: 0 0 0 0.2rem rgba(0, 123, 255, 0.25);
+ box-shadow: 0 0 0 0.2rem rgba(0, 123, 255, 0.25);
+}
+.btn.disabled, .btn:disabled {
+ opacity: 0.65;
+}
+.btn:not(:disabled):not(.disabled) {
+ cursor: pointer;
+}
+.btn:not(:disabled):not(.disabled):active, .btn:not(:disabled):not(.disabled).active {
+ background-image: none;
+}
+
+a.btn.disabled,
+fieldset:disabled a.btn {
+ pointer-events: none;
+}
+
+.btn-primary {
+ color: #fff;
+ background-color: #007bff;
+ border-color: #007bff;
+}
+.btn-primary:hover {
+ color: #fff;
+ background-color: #0069d9;
+ border-color: #0062cc;
+}
+.btn-primary:focus, .btn-primary.focus {
+ -webkit-box-shadow: 0 0 0 0.2rem rgba(0, 123, 255, 0.5);
+ box-shadow: 0 0 0 0.2rem rgba(0, 123, 255, 0.5);
+}
+.btn-primary.disabled, .btn-primary:disabled {
+ color: #fff;
+ background-color: #007bff;
+ border-color: #007bff;
+}
+.btn-primary:not(:disabled):not(.disabled):active, .btn-primary:not(:disabled):not(.disabled).active, .show > .btn-primary.dropdown-toggle {
+ color: #fff;
+ background-color: #0062cc;
+ border-color: #005cbf;
+}
+.btn-primary:not(:disabled):not(.disabled):active:focus, .btn-primary:not(:disabled):not(.disabled).active:focus, .show > .btn-primary.dropdown-toggle:focus {
+ -webkit-box-shadow: 0 0 0 0.2rem rgba(0, 123, 255, 0.5);
+ box-shadow: 0 0 0 0.2rem rgba(0, 123, 255, 0.5);
+}
+
+.btn-secondary {
+ color: #fff;
+ background-color: #6c757d;
+ border-color: #6c757d;
+}
+.btn-secondary:hover {
+ color: #fff;
+ background-color: #5a6268;
+ border-color: #545b62;
+}
+.btn-secondary:focus, .btn-secondary.focus {
+ -webkit-box-shadow: 0 0 0 0.2rem rgba(108, 117, 125, 0.5);
+ box-shadow: 0 0 0 0.2rem rgba(108, 117, 125, 0.5);
+}
+.btn-secondary.disabled, .btn-secondary:disabled {
+ color: #fff;
+ background-color: #6c757d;
+ border-color: #6c757d;
+}
+.btn-secondary:not(:disabled):not(.disabled):active, .btn-secondary:not(:disabled):not(.disabled).active, .show > .btn-secondary.dropdown-toggle {
+ color: #fff;
+ background-color: #545b62;
+ border-color: #4e555b;
+}
+.btn-secondary:not(:disabled):not(.disabled):active:focus, .btn-secondary:not(:disabled):not(.disabled).active:focus, .show > .btn-secondary.dropdown-toggle:focus {
+ -webkit-box-shadow: 0 0 0 0.2rem rgba(108, 117, 125, 0.5);
+ box-shadow: 0 0 0 0.2rem rgba(108, 117, 125, 0.5);
+}
+
+.btn-success {
+ color: #fff;
+ background-color: #28a745;
+ border-color: #28a745;
+}
+.btn-success:hover {
+ color: #fff;
+ background-color: #218838;
+ border-color: #1e7e34;
+}
+.btn-success:focus, .btn-success.focus {
+ -webkit-box-shadow: 0 0 0 0.2rem rgba(40, 167, 69, 0.5);
+ box-shadow: 0 0 0 0.2rem rgba(40, 167, 69, 0.5);
+}
+.btn-success.disabled, .btn-success:disabled {
+ color: #fff;
+ background-color: #28a745;
+ border-color: #28a745;
+}
+.btn-success:not(:disabled):not(.disabled):active, .btn-success:not(:disabled):not(.disabled).active, .show > .btn-success.dropdown-toggle {
+ color: #fff;
+ background-color: #1e7e34;
+ border-color: #1c7430;
+}
+.btn-success:not(:disabled):not(.disabled):active:focus, .btn-success:not(:disabled):not(.disabled).active:focus, .show > .btn-success.dropdown-toggle:focus {
+ -webkit-box-shadow: 0 0 0 0.2rem rgba(40, 167, 69, 0.5);
+ box-shadow: 0 0 0 0.2rem rgba(40, 167, 69, 0.5);
+}
+
+.btn-info {
+ color: #fff;
+ background-color: #17a2b8;
+ border-color: #17a2b8;
+}
+.btn-info:hover {
+ color: #fff;
+ background-color: #138496;
+ border-color: #117a8b;
+}
+.btn-info:focus, .btn-info.focus {
+ -webkit-box-shadow: 0 0 0 0.2rem rgba(23, 162, 184, 0.5);
+ box-shadow: 0 0 0 0.2rem rgba(23, 162, 184, 0.5);
+}
+.btn-info.disabled, .btn-info:disabled {
+ color: #fff;
+ background-color: #17a2b8;
+ border-color: #17a2b8;
+}
+.btn-info:not(:disabled):not(.disabled):active, .btn-info:not(:disabled):not(.disabled).active, .show > .btn-info.dropdown-toggle {
+ color: #fff;
+ background-color: #117a8b;
+ border-color: #10707f;
+}
+.btn-info:not(:disabled):not(.disabled):active:focus, .btn-info:not(:disabled):not(.disabled).active:focus, .show > .btn-info.dropdown-toggle:focus {
+ -webkit-box-shadow: 0 0 0 0.2rem rgba(23, 162, 184, 0.5);
+ box-shadow: 0 0 0 0.2rem rgba(23, 162, 184, 0.5);
+}
+
+.btn-warning {
+ color: #212529;
+ background-color: #ffc107;
+ border-color: #ffc107;
+}
+.btn-warning:hover {
+ color: #212529;
+ background-color: #e0a800;
+ border-color: #d39e00;
+}
+.btn-warning:focus, .btn-warning.focus {
+ -webkit-box-shadow: 0 0 0 0.2rem rgba(255, 193, 7, 0.5);
+ box-shadow: 0 0 0 0.2rem rgba(255, 193, 7, 0.5);
+}
+.btn-warning.disabled, .btn-warning:disabled {
+ color: #212529;
+ background-color: #ffc107;
+ border-color: #ffc107;
+}
+.btn-warning:not(:disabled):not(.disabled):active, .btn-warning:not(:disabled):not(.disabled).active, .show > .btn-warning.dropdown-toggle {
+ color: #212529;
+ background-color: #d39e00;
+ border-color: #c69500;
+}
+.btn-warning:not(:disabled):not(.disabled):active:focus, .btn-warning:not(:disabled):not(.disabled).active:focus, .show > .btn-warning.dropdown-toggle:focus {
+ -webkit-box-shadow: 0 0 0 0.2rem rgba(255, 193, 7, 0.5);
+ box-shadow: 0 0 0 0.2rem rgba(255, 193, 7, 0.5);
+}
+
+.btn-danger {
+ color: #fff;
+ background-color: #dc3545;
+ border-color: #dc3545;
+}
+.btn-danger:hover {
+ color: #fff;
+ background-color: #c82333;
+ border-color: #bd2130;
+}
+.btn-danger:focus, .btn-danger.focus {
+ -webkit-box-shadow: 0 0 0 0.2rem rgba(220, 53, 69, 0.5);
+ box-shadow: 0 0 0 0.2rem rgba(220, 53, 69, 0.5);
+}
+.btn-danger.disabled, .btn-danger:disabled {
+ color: #fff;
+ background-color: #dc3545;
+ border-color: #dc3545;
+}
+.btn-danger:not(:disabled):not(.disabled):active, .btn-danger:not(:disabled):not(.disabled).active, .show > .btn-danger.dropdown-toggle {
+ color: #fff;
+ background-color: #bd2130;
+ border-color: #b21f2d;
+}
+.btn-danger:not(:disabled):not(.disabled):active:focus, .btn-danger:not(:disabled):not(.disabled).active:focus, .show > .btn-danger.dropdown-toggle:focus {
+ -webkit-box-shadow: 0 0 0 0.2rem rgba(220, 53, 69, 0.5);
+ box-shadow: 0 0 0 0.2rem rgba(220, 53, 69, 0.5);
+}
+
+.btn-light {
+ color: #212529;
+ background-color: #f8f9fa;
+ border-color: #f8f9fa;
+}
+.btn-light:hover {
+ color: #212529;
+ background-color: #e2e6ea;
+ border-color: #dae0e5;
+}
+.btn-light:focus, .btn-light.focus {
+ -webkit-box-shadow: 0 0 0 0.2rem rgba(248, 249, 250, 0.5);
+ box-shadow: 0 0 0 0.2rem rgba(248, 249, 250, 0.5);
+}
+.btn-light.disabled, .btn-light:disabled {
+ color: #212529;
+ background-color: #f8f9fa;
+ border-color: #f8f9fa;
+}
+.btn-light:not(:disabled):not(.disabled):active, .btn-light:not(:disabled):not(.disabled).active, .show > .btn-light.dropdown-toggle {
+ color: #212529;
+ background-color: #dae0e5;
+ border-color: #d3d9df;
+}
+.btn-light:not(:disabled):not(.disabled):active:focus, .btn-light:not(:disabled):not(.disabled).active:focus, .show > .btn-light.dropdown-toggle:focus {
+ -webkit-box-shadow: 0 0 0 0.2rem rgba(248, 249, 250, 0.5);
+ box-shadow: 0 0 0 0.2rem rgba(248, 249, 250, 0.5);
+}
+
+.btn-dark {
+ color: #fff;
+ background-color: #343a40;
+ border-color: #343a40;
+}
+.btn-dark:hover {
+ color: #fff;
+ background-color: #23272b;
+ border-color: #1d2124;
+}
+.btn-dark:focus, .btn-dark.focus {
+ -webkit-box-shadow: 0 0 0 0.2rem rgba(52, 58, 64, 0.5);
+ box-shadow: 0 0 0 0.2rem rgba(52, 58, 64, 0.5);
+}
+.btn-dark.disabled, .btn-dark:disabled {
+ color: #fff;
+ background-color: #343a40;
+ border-color: #343a40;
+}
+.btn-dark:not(:disabled):not(.disabled):active, .btn-dark:not(:disabled):not(.disabled).active, .show > .btn-dark.dropdown-toggle {
+ color: #fff;
+ background-color: #1d2124;
+ border-color: #171a1d;
+}
+.btn-dark:not(:disabled):not(.disabled):active:focus, .btn-dark:not(:disabled):not(.disabled).active:focus, .show > .btn-dark.dropdown-toggle:focus {
+ -webkit-box-shadow: 0 0 0 0.2rem rgba(52, 58, 64, 0.5);
+ box-shadow: 0 0 0 0.2rem rgba(52, 58, 64, 0.5);
+}
+
+.btn-outline-primary {
+ color: #007bff;
+ background-color: transparent;
+ background-image: none;
+ border-color: #007bff;
+}
+.btn-outline-primary:hover {
+ color: #fff;
+ background-color: #007bff;
+ border-color: #007bff;
+}
+.btn-outline-primary:focus, .btn-outline-primary.focus {
+ -webkit-box-shadow: 0 0 0 0.2rem rgba(0, 123, 255, 0.5);
+ box-shadow: 0 0 0 0.2rem rgba(0, 123, 255, 0.5);
+}
+.btn-outline-primary.disabled, .btn-outline-primary:disabled {
+ color: #007bff;
+ background-color: transparent;
+}
+.btn-outline-primary:not(:disabled):not(.disabled):active, .btn-outline-primary:not(:disabled):not(.disabled).active, .show > .btn-outline-primary.dropdown-toggle {
+ color: #fff;
+ background-color: #007bff;
+ border-color: #007bff;
+}
+.btn-outline-primary:not(:disabled):not(.disabled):active:focus, .btn-outline-primary:not(:disabled):not(.disabled).active:focus, .show > .btn-outline-primary.dropdown-toggle:focus {
+ -webkit-box-shadow: 0 0 0 0.2rem rgba(0, 123, 255, 0.5);
+ box-shadow: 0 0 0 0.2rem rgba(0, 123, 255, 0.5);
+}
+
+.btn-outline-secondary {
+ color: #6c757d;
+ background-color: transparent;
+ background-image: none;
+ border-color: #6c757d;
+}
+.btn-outline-secondary:hover {
+ color: #fff;
+ background-color: #6c757d;
+ border-color: #6c757d;
+}
+.btn-outline-secondary:focus, .btn-outline-secondary.focus {
+ -webkit-box-shadow: 0 0 0 0.2rem rgba(108, 117, 125, 0.5);
+ box-shadow: 0 0 0 0.2rem rgba(108, 117, 125, 0.5);
+}
+.btn-outline-secondary.disabled, .btn-outline-secondary:disabled {
+ color: #6c757d;
+ background-color: transparent;
+}
+.btn-outline-secondary:not(:disabled):not(.disabled):active, .btn-outline-secondary:not(:disabled):not(.disabled).active, .show > .btn-outline-secondary.dropdown-toggle {
+ color: #fff;
+ background-color: #6c757d;
+ border-color: #6c757d;
+}
+.btn-outline-secondary:not(:disabled):not(.disabled):active:focus, .btn-outline-secondary:not(:disabled):not(.disabled).active:focus, .show > .btn-outline-secondary.dropdown-toggle:focus {
+ -webkit-box-shadow: 0 0 0 0.2rem rgba(108, 117, 125, 0.5);
+ box-shadow: 0 0 0 0.2rem rgba(108, 117, 125, 0.5);
+}
+
+.btn-outline-success {
+ color: #28a745;
+ background-color: transparent;
+ background-image: none;
+ border-color: #28a745;
+}
+.btn-outline-success:hover {
+ color: #fff;
+ background-color: #28a745;
+ border-color: #28a745;
+}
+.btn-outline-success:focus, .btn-outline-success.focus {
+ -webkit-box-shadow: 0 0 0 0.2rem rgba(40, 167, 69, 0.5);
+ box-shadow: 0 0 0 0.2rem rgba(40, 167, 69, 0.5);
+}
+.btn-outline-success.disabled, .btn-outline-success:disabled {
+ color: #28a745;
+ background-color: transparent;
+}
+.btn-outline-success:not(:disabled):not(.disabled):active, .btn-outline-success:not(:disabled):not(.disabled).active, .show > .btn-outline-success.dropdown-toggle {
+ color: #fff;
+ background-color: #28a745;
+ border-color: #28a745;
+}
+.btn-outline-success:not(:disabled):not(.disabled):active:focus, .btn-outline-success:not(:disabled):not(.disabled).active:focus, .show > .btn-outline-success.dropdown-toggle:focus {
+ -webkit-box-shadow: 0 0 0 0.2rem rgba(40, 167, 69, 0.5);
+ box-shadow: 0 0 0 0.2rem rgba(40, 167, 69, 0.5);
+}
+
+.btn-outline-info {
+ color: #17a2b8;
+ background-color: transparent;
+ background-image: none;
+ border-color: #17a2b8;
+}
+.btn-outline-info:hover {
+ color: #fff;
+ background-color: #17a2b8;
+ border-color: #17a2b8;
+}
+.btn-outline-info:focus, .btn-outline-info.focus {
+ -webkit-box-shadow: 0 0 0 0.2rem rgba(23, 162, 184, 0.5);
+ box-shadow: 0 0 0 0.2rem rgba(23, 162, 184, 0.5);
+}
+.btn-outline-info.disabled, .btn-outline-info:disabled {
+ color: #17a2b8;
+ background-color: transparent;
+}
+.btn-outline-info:not(:disabled):not(.disabled):active, .btn-outline-info:not(:disabled):not(.disabled).active, .show > .btn-outline-info.dropdown-toggle {
+ color: #fff;
+ background-color: #17a2b8;
+ border-color: #17a2b8;
+}
+.btn-outline-info:not(:disabled):not(.disabled):active:focus, .btn-outline-info:not(:disabled):not(.disabled).active:focus, .show > .btn-outline-info.dropdown-toggle:focus {
+ -webkit-box-shadow: 0 0 0 0.2rem rgba(23, 162, 184, 0.5);
+ box-shadow: 0 0 0 0.2rem rgba(23, 162, 184, 0.5);
+}
+
+.btn-outline-warning {
+ color: #ffc107;
+ background-color: transparent;
+ background-image: none;
+ border-color: #ffc107;
+}
+.btn-outline-warning:hover {
+ color: #212529;
+ background-color: #ffc107;
+ border-color: #ffc107;
+}
+.btn-outline-warning:focus, .btn-outline-warning.focus {
+ -webkit-box-shadow: 0 0 0 0.2rem rgba(255, 193, 7, 0.5);
+ box-shadow: 0 0 0 0.2rem rgba(255, 193, 7, 0.5);
+}
+.btn-outline-warning.disabled, .btn-outline-warning:disabled {
+ color: #ffc107;
+ background-color: transparent;
+}
+.btn-outline-warning:not(:disabled):not(.disabled):active, .btn-outline-warning:not(:disabled):not(.disabled).active, .show > .btn-outline-warning.dropdown-toggle {
+ color: #212529;
+ background-color: #ffc107;
+ border-color: #ffc107;
+}
+.btn-outline-warning:not(:disabled):not(.disabled):active:focus, .btn-outline-warning:not(:disabled):not(.disabled).active:focus, .show > .btn-outline-warning.dropdown-toggle:focus {
+ -webkit-box-shadow: 0 0 0 0.2rem rgba(255, 193, 7, 0.5);
+ box-shadow: 0 0 0 0.2rem rgba(255, 193, 7, 0.5);
+}
+
+.btn-outline-danger {
+ color: #dc3545;
+ background-color: transparent;
+ background-image: none;
+ border-color: #dc3545;
+}
+.btn-outline-danger:hover {
+ color: #fff;
+ background-color: #dc3545;
+ border-color: #dc3545;
+}
+.btn-outline-danger:focus, .btn-outline-danger.focus {
+ -webkit-box-shadow: 0 0 0 0.2rem rgba(220, 53, 69, 0.5);
+ box-shadow: 0 0 0 0.2rem rgba(220, 53, 69, 0.5);
+}
+.btn-outline-danger.disabled, .btn-outline-danger:disabled {
+ color: #dc3545;
+ background-color: transparent;
+}
+.btn-outline-danger:not(:disabled):not(.disabled):active, .btn-outline-danger:not(:disabled):not(.disabled).active, .show > .btn-outline-danger.dropdown-toggle {
+ color: #fff;
+ background-color: #dc3545;
+ border-color: #dc3545;
+}
+.btn-outline-danger:not(:disabled):not(.disabled):active:focus, .btn-outline-danger:not(:disabled):not(.disabled).active:focus, .show > .btn-outline-danger.dropdown-toggle:focus {
+ -webkit-box-shadow: 0 0 0 0.2rem rgba(220, 53, 69, 0.5);
+ box-shadow: 0 0 0 0.2rem rgba(220, 53, 69, 0.5);
+}
+
+.btn-outline-light {
+ color: #f8f9fa;
+ background-color: transparent;
+ background-image: none;
+ border-color: #f8f9fa;
+}
+.btn-outline-light:hover {
+ color: #212529;
+ background-color: #f8f9fa;
+ border-color: #f8f9fa;
+}
+.btn-outline-light:focus, .btn-outline-light.focus {
+ -webkit-box-shadow: 0 0 0 0.2rem rgba(248, 249, 250, 0.5);
+ box-shadow: 0 0 0 0.2rem rgba(248, 249, 250, 0.5);
+}
+.btn-outline-light.disabled, .btn-outline-light:disabled {
+ color: #f8f9fa;
+ background-color: transparent;
+}
+.btn-outline-light:not(:disabled):not(.disabled):active, .btn-outline-light:not(:disabled):not(.disabled).active, .show > .btn-outline-light.dropdown-toggle {
+ color: #212529;
+ background-color: #f8f9fa;
+ border-color: #f8f9fa;
+}
+.btn-outline-light:not(:disabled):not(.disabled):active:focus, .btn-outline-light:not(:disabled):not(.disabled).active:focus, .show > .btn-outline-light.dropdown-toggle:focus {
+ -webkit-box-shadow: 0 0 0 0.2rem rgba(248, 249, 250, 0.5);
+ box-shadow: 0 0 0 0.2rem rgba(248, 249, 250, 0.5);
+}
+
+.btn-outline-dark {
+ color: #343a40;
+ background-color: transparent;
+ background-image: none;
+ border-color: #343a40;
+}
+.btn-outline-dark:hover {
+ color: #fff;
+ background-color: #343a40;
+ border-color: #343a40;
+}
+.btn-outline-dark:focus, .btn-outline-dark.focus {
+ -webkit-box-shadow: 0 0 0 0.2rem rgba(52, 58, 64, 0.5);
+ box-shadow: 0 0 0 0.2rem rgba(52, 58, 64, 0.5);
+}
+.btn-outline-dark.disabled, .btn-outline-dark:disabled {
+ color: #343a40;
+ background-color: transparent;
+}
+.btn-outline-dark:not(:disabled):not(.disabled):active, .btn-outline-dark:not(:disabled):not(.disabled).active, .show > .btn-outline-dark.dropdown-toggle {
+ color: #fff;
+ background-color: #343a40;
+ border-color: #343a40;
+}
+.btn-outline-dark:not(:disabled):not(.disabled):active:focus, .btn-outline-dark:not(:disabled):not(.disabled).active:focus, .show > .btn-outline-dark.dropdown-toggle:focus {
+ -webkit-box-shadow: 0 0 0 0.2rem rgba(52, 58, 64, 0.5);
+ box-shadow: 0 0 0 0.2rem rgba(52, 58, 64, 0.5);
+}
+
+.btn-link {
+ font-weight: 400;
+ color: #007bff;
+ background-color: transparent;
+}
+.btn-link:hover {
+ color: #0056b3;
+ text-decoration: underline;
+ background-color: transparent;
+ border-color: transparent;
+}
+.btn-link:focus, .btn-link.focus {
+ text-decoration: underline;
+ border-color: transparent;
+ -webkit-box-shadow: none;
+ box-shadow: none;
+}
+.btn-link:disabled, .btn-link.disabled {
+ color: #6c757d;
+}
+
+.btn-lg, .btn-group-lg > .btn {
+ padding: 0.5rem 1rem;
+ font-size: 1.25rem;
+ line-height: 1.5;
+ border-radius: 0.3rem;
+}
+
+.btn-sm, .btn-group-sm > .btn {
+ padding: 0.25rem 0.5rem;
+ font-size: 0.875rem;
+ line-height: 1.5;
+ border-radius: 0.2rem;
+}
+
+.btn-block {
+ display: block;
+ width: 100%;
+}
+.btn-block + .btn-block {
+ margin-top: 0.5rem;
+}
+
+input[type="submit"].btn-block,
+input[type="reset"].btn-block,
+input[type="button"].btn-block {
+ width: 100%;
+}
+
+.fade {
+ opacity: 0;
+ -webkit-transition: opacity 0.15s linear;
+ transition: opacity 0.15s linear;
+}
+.fade.show {
+ opacity: 1;
+}
+
+.collapse {
+ display: none;
+}
+.collapse.show {
+ display: block;
+}
+
+tr.collapse.show {
+ display: table-row;
+}
+
+tbody.collapse.show {
+ display: table-row-group;
+}
+
+.collapsing {
+ position: relative;
+ height: 0;
+ overflow: hidden;
+ -webkit-transition: height 0.35s ease;
+ transition: height 0.35s ease;
+}
+
+.dropup,
+.dropdown {
+ position: relative;
+}
+
+.dropdown-toggle::after {
+ display: inline-block;
+ width: 0;
+ height: 0;
+ margin-left: 0.255em;
+ vertical-align: 0.255em;
+ content: "";
+ border-top: 0.3em solid;
+ border-right: 0.3em solid transparent;
+ border-bottom: 0;
+ border-left: 0.3em solid transparent;
+}
+.dropdown-toggle:empty::after {
+ margin-left: 0;
+}
+
+.dropdown-menu {
+ position: absolute;
+ top: 100%;
+ left: 0;
+ z-index: 1000;
+ display: none;
+ float: left;
+ min-width: 10rem;
+ padding: 0.5rem 0;
+ margin: 0.125rem 0 0;
+ font-size: 1rem;
+ color: #212529;
+ text-align: left;
+ list-style: none;
+ background-color: #fff;
+ background-clip: padding-box;
+ border: 1px solid rgba(0, 0, 0, 0.15);
+ border-radius: 0.25rem;
+}
+
+.dropup .dropdown-menu {
+ margin-top: 0;
+ margin-bottom: 0.125rem;
+}
+.dropup .dropdown-toggle::after {
+ display: inline-block;
+ width: 0;
+ height: 0;
+ margin-left: 0.255em;
+ vertical-align: 0.255em;
+ content: "";
+ border-top: 0;
+ border-right: 0.3em solid transparent;
+ border-bottom: 0.3em solid;
+ border-left: 0.3em solid transparent;
+}
+.dropup .dropdown-toggle:empty::after {
+ margin-left: 0;
+}
+
+.dropright .dropdown-menu {
+ margin-top: 0;
+ margin-left: 0.125rem;
+}
+.dropright .dropdown-toggle::after {
+ display: inline-block;
+ width: 0;
+ height: 0;
+ margin-left: 0.255em;
+ vertical-align: 0.255em;
+ content: "";
+ border-top: 0.3em solid transparent;
+ border-bottom: 0.3em solid transparent;
+ border-left: 0.3em solid;
+}
+.dropright .dropdown-toggle:empty::after {
+ margin-left: 0;
+}
+.dropright .dropdown-toggle::after {
+ vertical-align: 0;
+}
+
+.dropleft .dropdown-menu {
+ margin-top: 0;
+ margin-right: 0.125rem;
+}
+.dropleft .dropdown-toggle::after {
+ display: inline-block;
+ width: 0;
+ height: 0;
+ margin-left: 0.255em;
+ vertical-align: 0.255em;
+ content: "";
+}
+.dropleft .dropdown-toggle::after {
+ display: none;
+}
+.dropleft .dropdown-toggle::before {
+ display: inline-block;
+ width: 0;
+ height: 0;
+ margin-right: 0.255em;
+ vertical-align: 0.255em;
+ content: "";
+ border-top: 0.3em solid transparent;
+ border-right: 0.3em solid;
+ border-bottom: 0.3em solid transparent;
+}
+.dropleft .dropdown-toggle:empty::after {
+ margin-left: 0;
+}
+.dropleft .dropdown-toggle::before {
+ vertical-align: 0;
+}
+
+.dropdown-divider {
+ height: 0;
+ margin: 0.5rem 0;
+ overflow: hidden;
+ border-top: 1px solid #e9ecef;
+}
+
+.dropdown-item {
+ display: block;
+ width: 100%;
+ padding: 0.25rem 1.5rem;
+ clear: both;
+ font-weight: 400;
+ color: #212529;
+ text-align: inherit;
+ white-space: nowrap;
+ background-color: transparent;
+ border: 0;
+}
+.dropdown-item:hover, .dropdown-item:focus {
+ color: #16181b;
+ text-decoration: none;
+ background-color: #f8f9fa;
+}
+.dropdown-item.active, .dropdown-item:active {
+ color: #fff;
+ text-decoration: none;
+ background-color: #007bff;
+}
+.dropdown-item.disabled, .dropdown-item:disabled {
+ color: #6c757d;
+ background-color: transparent;
+}
+
+.dropdown-menu.show {
+ display: block;
+}
+
+.dropdown-header {
+ display: block;
+ padding: 0.5rem 1.5rem;
+ margin-bottom: 0;
+ font-size: 0.875rem;
+ color: #6c757d;
+ white-space: nowrap;
+}
+
+.btn-group,
+.btn-group-vertical {
+ position: relative;
+ display: -webkit-inline-box;
+ display: -ms-inline-flexbox;
+ display: inline-flex;
+ vertical-align: middle;
+}
+.btn-group > .btn,
+.btn-group-vertical > .btn {
+ position: relative;
+ -webkit-box-flex: 0;
+ -ms-flex: 0 1 auto;
+ flex: 0 1 auto;
+}
+.btn-group > .btn:hover,
+.btn-group-vertical > .btn:hover {
+ z-index: 1;
+}
+.btn-group > .btn:focus, .btn-group > .btn:active, .btn-group > .btn.active,
+.btn-group-vertical > .btn:focus,
+.btn-group-vertical > .btn:active,
+.btn-group-vertical > .btn.active {
+ z-index: 1;
+}
+.btn-group .btn + .btn,
+.btn-group .btn + .btn-group,
+.btn-group .btn-group + .btn,
+.btn-group .btn-group + .btn-group,
+.btn-group-vertical .btn + .btn,
+.btn-group-vertical .btn + .btn-group,
+.btn-group-vertical .btn-group + .btn,
+.btn-group-vertical .btn-group + .btn-group {
+ margin-left: -1px;
+}
+
+.btn-toolbar {
+ display: -webkit-box;
+ display: -ms-flexbox;
+ display: flex;
+ -ms-flex-wrap: wrap;
+ flex-wrap: wrap;
+ -webkit-box-pack: start;
+ -ms-flex-pack: start;
+ justify-content: flex-start;
+}
+.btn-toolbar .input-group {
+ width: auto;
+}
+
+.btn-group > .btn:first-child {
+ margin-left: 0;
+}
+.btn-group > .btn:not(:last-child):not(.dropdown-toggle),
+.btn-group > .btn-group:not(:last-child) > .btn {
+ border-top-right-radius: 0;
+ border-bottom-right-radius: 0;
+}
+.btn-group > .btn:not(:first-child),
+.btn-group > .btn-group:not(:first-child) > .btn {
+ border-top-left-radius: 0;
+ border-bottom-left-radius: 0;
+}
+
+.dropdown-toggle-split {
+ padding-right: 0.5625rem;
+ padding-left: 0.5625rem;
+}
+.dropdown-toggle-split::after {
+ margin-left: 0;
+}
+
+.btn-sm + .dropdown-toggle-split, .btn-group-sm > .btn + .dropdown-toggle-split {
+ padding-right: 0.375rem;
+ padding-left: 0.375rem;
+}
+
+.btn-lg + .dropdown-toggle-split, .btn-group-lg > .btn + .dropdown-toggle-split {
+ padding-right: 0.75rem;
+ padding-left: 0.75rem;
+}
+
+.btn-group-vertical {
+ -webkit-box-orient: vertical;
+ -webkit-box-direction: normal;
+ -ms-flex-direction: column;
+ flex-direction: column;
+ -webkit-box-align: start;
+ -ms-flex-align: start;
+ align-items: flex-start;
+ -webkit-box-pack: center;
+ -ms-flex-pack: center;
+ justify-content: center;
+}
+.btn-group-vertical .btn,
+.btn-group-vertical .btn-group {
+ width: 100%;
+}
+.btn-group-vertical > .btn + .btn,
+.btn-group-vertical > .btn + .btn-group,
+.btn-group-vertical > .btn-group + .btn,
+.btn-group-vertical > .btn-group + .btn-group {
+ margin-top: -1px;
+ margin-left: 0;
+}
+.btn-group-vertical > .btn:not(:last-child):not(.dropdown-toggle),
+.btn-group-vertical > .btn-group:not(:last-child) > .btn {
+ border-bottom-right-radius: 0;
+ border-bottom-left-radius: 0;
+}
+.btn-group-vertical > .btn:not(:first-child),
+.btn-group-vertical > .btn-group:not(:first-child) > .btn {
+ border-top-left-radius: 0;
+ border-top-right-radius: 0;
+}
+
+.btn-group-toggle > .btn,
+.btn-group-toggle > .btn-group > .btn {
+ margin-bottom: 0;
+}
+.btn-group-toggle > .btn input[type="radio"],
+.btn-group-toggle > .btn input[type="checkbox"],
+.btn-group-toggle > .btn-group > .btn input[type="radio"],
+.btn-group-toggle > .btn-group > .btn input[type="checkbox"] {
+ position: absolute;
+ clip: rect(0, 0, 0, 0);
+ pointer-events: none;
+}
+
+.input-group {
+ position: relative;
+ display: -webkit-box;
+ display: -ms-flexbox;
+ display: flex;
+ -ms-flex-wrap: wrap;
+ flex-wrap: wrap;
+ -webkit-box-align: stretch;
+ -ms-flex-align: stretch;
+ align-items: stretch;
+ width: 100%;
+}
+.input-group > .form-control,
+.input-group > .custom-select,
+.input-group > .custom-file {
+ position: relative;
+ -webkit-box-flex: 1;
+ -ms-flex: 1 1 auto;
+ flex: 1 1 auto;
+ width: 1%;
+ margin-bottom: 0;
+}
+.input-group > .form-control:focus,
+.input-group > .custom-select:focus,
+.input-group > .custom-file:focus {
+ z-index: 3;
+}
+.input-group > .form-control + .form-control,
+.input-group > .form-control + .custom-select,
+.input-group > .form-control + .custom-file,
+.input-group > .custom-select + .form-control,
+.input-group > .custom-select + .custom-select,
+.input-group > .custom-select + .custom-file,
+.input-group > .custom-file + .form-control,
+.input-group > .custom-file + .custom-select,
+.input-group > .custom-file + .custom-file {
+ margin-left: -1px;
+}
+.input-group > .form-control:not(:last-child),
+.input-group > .custom-select:not(:last-child) {
+ border-top-right-radius: 0;
+ border-bottom-right-radius: 0;
+}
+.input-group > .form-control:not(:first-child),
+.input-group > .custom-select:not(:first-child) {
+ border-top-left-radius: 0;
+ border-bottom-left-radius: 0;
+}
+.input-group > .custom-file {
+ display: -webkit-box;
+ display: -ms-flexbox;
+ display: flex;
+ -webkit-box-align: center;
+ -ms-flex-align: center;
+ align-items: center;
+}
+.input-group > .custom-file:not(:last-child) .custom-file-label, .input-group > .custom-file:not(:last-child) .custom-file-label::before {
+ border-top-right-radius: 0;
+ border-bottom-right-radius: 0;
+}
+.input-group > .custom-file:not(:first-child) .custom-file-label, .input-group > .custom-file:not(:first-child) .custom-file-label::before {
+ border-top-left-radius: 0;
+ border-bottom-left-radius: 0;
+}
+
+.input-group-prepend,
+.input-group-append {
+ display: -webkit-box;
+ display: -ms-flexbox;
+ display: flex;
+}
+.input-group-prepend .btn,
+.input-group-append .btn {
+ position: relative;
+ z-index: 2;
+}
+.input-group-prepend .btn + .btn,
+.input-group-prepend .btn + .input-group-text,
+.input-group-prepend .input-group-text + .input-group-text,
+.input-group-prepend .input-group-text + .btn,
+.input-group-append .btn + .btn,
+.input-group-append .btn + .input-group-text,
+.input-group-append .input-group-text + .input-group-text,
+.input-group-append .input-group-text + .btn {
+ margin-left: -1px;
+}
+
+.input-group-prepend {
+ margin-right: -1px;
+}
+
+.input-group-append {
+ margin-left: -1px;
+}
+
+.input-group-text {
+ display: -webkit-box;
+ display: -ms-flexbox;
+ display: flex;
+ -webkit-box-align: center;
+ -ms-flex-align: center;
+ align-items: center;
+ padding: 0.375rem 0.75rem;
+ margin-bottom: 0;
+ font-size: 1rem;
+ font-weight: 400;
+ line-height: 1.5;
+ color: #495057;
+ text-align: center;
+ white-space: nowrap;
+ background-color: #e9ecef;
+ border: 1px solid #ced4da;
+ border-radius: 0.25rem;
+}
+.input-group-text input[type="radio"],
+.input-group-text input[type="checkbox"] {
+ margin-top: 0;
+}
+
+.input-group > .input-group-prepend > .btn,
+.input-group > .input-group-prepend > .input-group-text,
+.input-group > .input-group-append:not(:last-child) > .btn,
+.input-group > .input-group-append:not(:last-child) > .input-group-text,
+.input-group > .input-group-append:last-child > .btn:not(:last-child):not(.dropdown-toggle),
+.input-group > .input-group-append:last-child > .input-group-text:not(:last-child) {
+ border-top-right-radius: 0;
+ border-bottom-right-radius: 0;
+}
+
+.input-group > .input-group-append > .btn,
+.input-group > .input-group-append > .input-group-text,
+.input-group > .input-group-prepend:not(:first-child) > .btn,
+.input-group > .input-group-prepend:not(:first-child) > .input-group-text,
+.input-group > .input-group-prepend:first-child > .btn:not(:first-child),
+.input-group > .input-group-prepend:first-child > .input-group-text:not(:first-child) {
+ border-top-left-radius: 0;
+ border-bottom-left-radius: 0;
+}
+
+.custom-control {
+ position: relative;
+ display: block;
+ min-height: 1.5rem;
+ padding-left: 1.5rem;
+}
+
+.custom-control-inline {
+ display: -webkit-inline-box;
+ display: -ms-inline-flexbox;
+ display: inline-flex;
+ margin-right: 1rem;
+}
+
+.custom-control-input {
+ position: absolute;
+ z-index: -1;
+ opacity: 0;
+}
+.custom-control-input:checked ~ .custom-control-label::before {
+ color: #fff;
+ background-color: #007bff;
+}
+.custom-control-input:focus ~ .custom-control-label::before {
+ -webkit-box-shadow: 0 0 0 1px #fff, 0 0 0 0.2rem rgba(0, 123, 255, 0.25);
+ box-shadow: 0 0 0 1px #fff, 0 0 0 0.2rem rgba(0, 123, 255, 0.25);
+}
+.custom-control-input:active ~ .custom-control-label::before {
+ color: #fff;
+ background-color: #b3d7ff;
+}
+.custom-control-input:disabled ~ .custom-control-label {
+ color: #6c757d;
+}
+.custom-control-input:disabled ~ .custom-control-label::before {
+ background-color: #e9ecef;
+}
+
+.custom-control-label {
+ margin-bottom: 0;
+}
+.custom-control-label::before {
+ position: absolute;
+ top: 0.25rem;
+ left: 0;
+ display: block;
+ width: 1rem;
+ height: 1rem;
+ pointer-events: none;
+ content: "";
+ -webkit-user-select: none;
+ -moz-user-select: none;
+ -ms-user-select: none;
+ user-select: none;
+ background-color: #dee2e6;
+}
+.custom-control-label::after {
+ position: absolute;
+ top: 0.25rem;
+ left: 0;
+ display: block;
+ width: 1rem;
+ height: 1rem;
+ content: "";
+ background-repeat: no-repeat;
+ background-position: center center;
+ background-size: 50% 50%;
+}
+
+.custom-checkbox .custom-control-label::before {
+ border-radius: 0.25rem;
+}
+.custom-checkbox .custom-control-input:checked ~ .custom-control-label::before {
+ background-color: #007bff;
+}
+.custom-checkbox .custom-control-input:checked ~ .custom-control-label::after {
+ background-image: url("data:image/svg+xml;charset=utf8,%3Csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 8 8'%3E%3Cpath fill='%23fff' d='M6.564.75l-3.59 3.612-1.538-1.55L0 4.26 2.974 7.25 8 2.193z'/%3E%3C/svg%3E");
+}
+.custom-checkbox .custom-control-input:indeterminate ~ .custom-control-label::before {
+ background-color: #007bff;
+}
+.custom-checkbox .custom-control-input:indeterminate ~ .custom-control-label::after {
+ background-image: url("data:image/svg+xml;charset=utf8,%3Csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 4 4'%3E%3Cpath stroke='%23fff' d='M0 2h4'/%3E%3C/svg%3E");
+}
+.custom-checkbox .custom-control-input:disabled:checked ~ .custom-control-label::before {
+ background-color: rgba(0, 123, 255, 0.5);
+}
+.custom-checkbox .custom-control-input:disabled:indeterminate ~ .custom-control-label::before {
+ background-color: rgba(0, 123, 255, 0.5);
+}
+
+.custom-radio .custom-control-label::before {
+ border-radius: 50%;
+}
+.custom-radio .custom-control-input:checked ~ .custom-control-label::before {
+ background-color: #007bff;
+}
+.custom-radio .custom-control-input:checked ~ .custom-control-label::after {
+ background-image: url("data:image/svg+xml;charset=utf8,%3Csvg xmlns='http://www.w3.org/2000/svg' viewBox='-4 -4 8 8'%3E%3Ccircle r='3' fill='%23fff'/%3E%3C/svg%3E");
+}
+.custom-radio .custom-control-input:disabled:checked ~ .custom-control-label::before {
+ background-color: rgba(0, 123, 255, 0.5);
+}
+
+.custom-select {
+ display: inline-block;
+ width: 100%;
+ height: calc(2.25rem + 2px);
+ padding: 0.375rem 1.75rem 0.375rem 0.75rem;
+ line-height: 1.5;
+ color: #495057;
+ vertical-align: middle;
+ background: #fff url("data:image/svg+xml;charset=utf8,%3Csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 4 5'%3E%3Cpath fill='%23343a40' d='M2 0L0 2h4zm0 5L0 3h4z'/%3E%3C/svg%3E") no-repeat right 0.75rem center;
+ background-size: 8px 10px;
+ border: 1px solid #ced4da;
+ border-radius: 0.25rem;
+ -webkit-appearance: none;
+ -moz-appearance: none;
+ appearance: none;
+}
+.custom-select:focus {
+ border-color: #80bdff;
+ outline: 0;
+ -webkit-box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.075), 0 0 5px rgba(128, 189, 255, 0.5);
+ box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.075), 0 0 5px rgba(128, 189, 255, 0.5);
+}
+.custom-select:focus::-ms-value {
+ color: #495057;
+ background-color: #fff;
+}
+.custom-select[multiple], .custom-select[size]:not([size="1"]) {
+ height: auto;
+ padding-right: 0.75rem;
+ background-image: none;
+}
+.custom-select:disabled {
+ color: #6c757d;
+ background-color: #e9ecef;
+}
+.custom-select::-ms-expand {
+ opacity: 0;
+}
+
+.custom-select-sm {
+ height: calc(1.8125rem + 2px);
+ padding-top: 0.375rem;
+ padding-bottom: 0.375rem;
+ font-size: 75%;
+}
+
+.custom-select-lg {
+ height: calc(2.875rem + 2px);
+ padding-top: 0.375rem;
+ padding-bottom: 0.375rem;
+ font-size: 125%;
+}
+
+.custom-file {
+ position: relative;
+ display: inline-block;
+ width: 100%;
+ height: calc(2.25rem + 2px);
+ margin-bottom: 0;
+}
+
+.custom-file-input {
+ position: relative;
+ z-index: 2;
+ width: 100%;
+ height: calc(2.25rem + 2px);
+ margin: 0;
+ opacity: 0;
+}
+.custom-file-input:focus ~ .custom-file-control {
+ border-color: #80bdff;
+ -webkit-box-shadow: 0 0 0 0.2rem rgba(0, 123, 255, 0.25);
+ box-shadow: 0 0 0 0.2rem rgba(0, 123, 255, 0.25);
+}
+.custom-file-input:focus ~ .custom-file-control::before {
+ border-color: #80bdff;
+}
+.custom-file-input:lang(en) ~ .custom-file-label::after {
+ content: "Browse";
+}
+
+.custom-file-label {
+ position: absolute;
+ top: 0;
+ right: 0;
+ left: 0;
+ z-index: 1;
+ height: calc(2.25rem + 2px);
+ padding: 0.375rem 0.75rem;
+ line-height: 1.5;
+ color: #495057;
+ background-color: #fff;
+ border: 1px solid #ced4da;
+ border-radius: 0.25rem;
+}
+.custom-file-label::after {
+ position: absolute;
+ top: 0;
+ right: 0;
+ bottom: 0;
+ z-index: 3;
+ display: block;
+ height: calc(calc(2.25rem + 2px) - 1px * 2);
+ padding: 0.375rem 0.75rem;
+ line-height: 1.5;
+ color: #495057;
+ content: "Browse";
+ background-color: #e9ecef;
+ border-left: 1px solid #ced4da;
+ border-radius: 0 0.25rem 0.25rem 0;
+}
+
+.nav {
+ display: -webkit-box;
+ display: -ms-flexbox;
+ display: flex;
+ -ms-flex-wrap: wrap;
+ flex-wrap: wrap;
+ padding-left: 0;
+ margin-bottom: 0;
+ list-style: none;
+}
+
+.nav-link {
+ display: block;
+ padding: 0.5rem 1rem;
+}
+.nav-link:hover, .nav-link:focus {
+ text-decoration: none;
+}
+.nav-link.disabled {
+ color: #6c757d;
+}
+
+.nav-tabs {
+ border-bottom: 1px solid #dee2e6;
+}
+.nav-tabs .nav-item {
+ margin-bottom: -1px;
+}
+.nav-tabs .nav-link {
+ border: 1px solid transparent;
+ border-top-left-radius: 0.25rem;
+ border-top-right-radius: 0.25rem;
+}
+.nav-tabs .nav-link:hover, .nav-tabs .nav-link:focus {
+ border-color: #e9ecef #e9ecef #dee2e6;
+}
+.nav-tabs .nav-link.disabled {
+ color: #6c757d;
+ background-color: transparent;
+ border-color: transparent;
+}
+.nav-tabs .nav-link.active,
+.nav-tabs .nav-item.show .nav-link {
+ color: #495057;
+ background-color: #fff;
+ border-color: #dee2e6 #dee2e6 #fff;
+}
+.nav-tabs .dropdown-menu {
+ margin-top: -1px;
+ border-top-left-radius: 0;
+ border-top-right-radius: 0;
+}
+
+.nav-pills .nav-link {
+ border-radius: 0.25rem;
+}
+.nav-pills .nav-link.active,
+.nav-pills .show > .nav-link {
+ color: #fff;
+ background-color: #007bff;
+}
+
+.nav-fill .nav-item {
+ -webkit-box-flex: 1;
+ -ms-flex: 1 1 auto;
+ flex: 1 1 auto;
+ text-align: center;
+}
+
+.nav-justified .nav-item {
+ -ms-flex-preferred-size: 0;
+ flex-basis: 0;
+ -webkit-box-flex: 1;
+ -ms-flex-positive: 1;
+ flex-grow: 1;
+ text-align: center;
+}
+
+.tab-content > .tab-pane {
+ display: none;
+}
+.tab-content > .active {
+ display: block;
+}
+
+.navbar {
+ position: relative;
+ display: -webkit-box;
+ display: -ms-flexbox;
+ display: flex;
+ -ms-flex-wrap: wrap;
+ flex-wrap: wrap;
+ -webkit-box-align: center;
+ -ms-flex-align: center;
+ align-items: center;
+ -webkit-box-pack: justify;
+ -ms-flex-pack: justify;
+ justify-content: space-between;
+ padding: 0.5rem 1rem;
+}
+.navbar > .container,
+.navbar > .container-fluid {
+ display: -webkit-box;
+ display: -ms-flexbox;
+ display: flex;
+ -ms-flex-wrap: wrap;
+ flex-wrap: wrap;
+ -webkit-box-align: center;
+ -ms-flex-align: center;
+ align-items: center;
+ -webkit-box-pack: justify;
+ -ms-flex-pack: justify;
+ justify-content: space-between;
+}
+
+.navbar-brand {
+ display: inline-block;
+ padding-top: 0.3125rem;
+ padding-bottom: 0.3125rem;
+ margin-right: 1rem;
+ font-size: 1.25rem;
+ line-height: inherit;
+ white-space: nowrap;
+}
+.navbar-brand:hover, .navbar-brand:focus {
+ text-decoration: none;
+}
+
+.navbar-nav {
+ display: -webkit-box;
+ display: -ms-flexbox;
+ display: flex;
+ -webkit-box-orient: vertical;
+ -webkit-box-direction: normal;
+ -ms-flex-direction: column;
+ flex-direction: column;
+ padding-left: 0;
+ margin-bottom: 0;
+ list-style: none;
+}
+.navbar-nav .nav-link {
+ padding-right: 0;
+ padding-left: 0;
+}
+.navbar-nav .dropdown-menu {
+ position: static;
+ float: none;
+}
+
+.navbar-text {
+ display: inline-block;
+ padding-top: 0.5rem;
+ padding-bottom: 0.5rem;
+}
+
+.navbar-collapse {
+ -ms-flex-preferred-size: 100%;
+ flex-basis: 100%;
+ -webkit-box-flex: 1;
+ -ms-flex-positive: 1;
+ flex-grow: 1;
+ -webkit-box-align: center;
+ -ms-flex-align: center;
+ align-items: center;
+}
+
+.navbar-toggler {
+ padding: 0.25rem 0.75rem;
+ font-size: 1.25rem;
+ line-height: 1;
+ background-color: transparent;
+ border: 1px solid transparent;
+ border-radius: 0.25rem;
+}
+.navbar-toggler:hover, .navbar-toggler:focus {
+ text-decoration: none;
+}
+.navbar-toggler:not(:disabled):not(.disabled) {
+ cursor: pointer;
+}
+
+.navbar-toggler-icon {
+ display: inline-block;
+ width: 1.5em;
+ height: 1.5em;
+ vertical-align: middle;
+ content: "";
+ background: no-repeat center center;
+ background-size: 100% 100%;
+}
+
+@media (max-width: 575.98px) {
+ .navbar-expand-sm > .container,
+ .navbar-expand-sm > .container-fluid {
+ padding-right: 0;
+ padding-left: 0;
+ }
+}
+@media (min-width: 576px) {
+ .navbar-expand-sm {
+ -webkit-box-orient: horizontal;
+ -webkit-box-direction: normal;
+ -ms-flex-flow: row nowrap;
+ flex-flow: row nowrap;
+ -webkit-box-pack: start;
+ -ms-flex-pack: start;
+ justify-content: flex-start;
+ }
+ .navbar-expand-sm .navbar-nav {
+ -webkit-box-orient: horizontal;
+ -webkit-box-direction: normal;
+ -ms-flex-direction: row;
+ flex-direction: row;
+ }
+ .navbar-expand-sm .navbar-nav .dropdown-menu {
+ position: absolute;
+ }
+ .navbar-expand-sm .navbar-nav .dropdown-menu-right {
+ right: 0;
+ left: auto;
+ }
+ .navbar-expand-sm .navbar-nav .nav-link {
+ padding-right: 0.5rem;
+ padding-left: 0.5rem;
+ }
+ .navbar-expand-sm > .container,
+ .navbar-expand-sm > .container-fluid {
+ -ms-flex-wrap: nowrap;
+ flex-wrap: nowrap;
+ }
+ .navbar-expand-sm .navbar-collapse {
+ display: -webkit-box !important;
+ display: -ms-flexbox !important;
+ display: flex !important;
+ -ms-flex-preferred-size: auto;
+ flex-basis: auto;
+ }
+ .navbar-expand-sm .navbar-toggler {
+ display: none;
+ }
+ .navbar-expand-sm .dropup .dropdown-menu {
+ top: auto;
+ bottom: 100%;
+ }
+}
+@media (max-width: 767.98px) {
+ .navbar-expand-md > .container,
+ .navbar-expand-md > .container-fluid {
+ padding-right: 0;
+ padding-left: 0;
+ }
+}
+@media (min-width: 768px) {
+ .navbar-expand-md {
+ -webkit-box-orient: horizontal;
+ -webkit-box-direction: normal;
+ -ms-flex-flow: row nowrap;
+ flex-flow: row nowrap;
+ -webkit-box-pack: start;
+ -ms-flex-pack: start;
+ justify-content: flex-start;
+ }
+ .navbar-expand-md .navbar-nav {
+ -webkit-box-orient: horizontal;
+ -webkit-box-direction: normal;
+ -ms-flex-direction: row;
+ flex-direction: row;
+ }
+ .navbar-expand-md .navbar-nav .dropdown-menu {
+ position: absolute;
+ }
+ .navbar-expand-md .navbar-nav .dropdown-menu-right {
+ right: 0;
+ left: auto;
+ }
+ .navbar-expand-md .navbar-nav .nav-link {
+ padding-right: 0.5rem;
+ padding-left: 0.5rem;
+ }
+ .navbar-expand-md > .container,
+ .navbar-expand-md > .container-fluid {
+ -ms-flex-wrap: nowrap;
+ flex-wrap: nowrap;
+ }
+ .navbar-expand-md .navbar-collapse {
+ display: -webkit-box !important;
+ display: -ms-flexbox !important;
+ display: flex !important;
+ -ms-flex-preferred-size: auto;
+ flex-basis: auto;
+ }
+ .navbar-expand-md .navbar-toggler {
+ display: none;
+ }
+ .navbar-expand-md .dropup .dropdown-menu {
+ top: auto;
+ bottom: 100%;
+ }
+}
+@media (max-width: 991.98px) {
+ .navbar-expand-lg > .container,
+ .navbar-expand-lg > .container-fluid {
+ padding-right: 0;
+ padding-left: 0;
+ }
+}
+@media (min-width: 992px) {
+ .navbar-expand-lg {
+ -webkit-box-orient: horizontal;
+ -webkit-box-direction: normal;
+ -ms-flex-flow: row nowrap;
+ flex-flow: row nowrap;
+ -webkit-box-pack: start;
+ -ms-flex-pack: start;
+ justify-content: flex-start;
+ }
+ .navbar-expand-lg .navbar-nav {
+ -webkit-box-orient: horizontal;
+ -webkit-box-direction: normal;
+ -ms-flex-direction: row;
+ flex-direction: row;
+ }
+ .navbar-expand-lg .navbar-nav .dropdown-menu {
+ position: absolute;
+ }
+ .navbar-expand-lg .navbar-nav .dropdown-menu-right {
+ right: 0;
+ left: auto;
+ }
+ .navbar-expand-lg .navbar-nav .nav-link {
+ padding-right: 0.5rem;
+ padding-left: 0.5rem;
+ }
+ .navbar-expand-lg > .container,
+ .navbar-expand-lg > .container-fluid {
+ -ms-flex-wrap: nowrap;
+ flex-wrap: nowrap;
+ }
+ .navbar-expand-lg .navbar-collapse {
+ display: -webkit-box !important;
+ display: -ms-flexbox !important;
+ display: flex !important;
+ -ms-flex-preferred-size: auto;
+ flex-basis: auto;
+ }
+ .navbar-expand-lg .navbar-toggler {
+ display: none;
+ }
+ .navbar-expand-lg .dropup .dropdown-menu {
+ top: auto;
+ bottom: 100%;
+ }
+}
+@media (max-width: 1199.98px) {
+ .navbar-expand-xl > .container,
+ .navbar-expand-xl > .container-fluid {
+ padding-right: 0;
+ padding-left: 0;
+ }
+}
+@media (min-width: 1200px) {
+ .navbar-expand-xl {
+ -webkit-box-orient: horizontal;
+ -webkit-box-direction: normal;
+ -ms-flex-flow: row nowrap;
+ flex-flow: row nowrap;
+ -webkit-box-pack: start;
+ -ms-flex-pack: start;
+ justify-content: flex-start;
+ }
+ .navbar-expand-xl .navbar-nav {
+ -webkit-box-orient: horizontal;
+ -webkit-box-direction: normal;
+ -ms-flex-direction: row;
+ flex-direction: row;
+ }
+ .navbar-expand-xl .navbar-nav .dropdown-menu {
+ position: absolute;
+ }
+ .navbar-expand-xl .navbar-nav .dropdown-menu-right {
+ right: 0;
+ left: auto;
+ }
+ .navbar-expand-xl .navbar-nav .nav-link {
+ padding-right: 0.5rem;
+ padding-left: 0.5rem;
+ }
+ .navbar-expand-xl > .container,
+ .navbar-expand-xl > .container-fluid {
+ -ms-flex-wrap: nowrap;
+ flex-wrap: nowrap;
+ }
+ .navbar-expand-xl .navbar-collapse {
+ display: -webkit-box !important;
+ display: -ms-flexbox !important;
+ display: flex !important;
+ -ms-flex-preferred-size: auto;
+ flex-basis: auto;
+ }
+ .navbar-expand-xl .navbar-toggler {
+ display: none;
+ }
+ .navbar-expand-xl .dropup .dropdown-menu {
+ top: auto;
+ bottom: 100%;
+ }
+}
+.navbar-expand {
+ -webkit-box-orient: horizontal;
+ -webkit-box-direction: normal;
+ -ms-flex-flow: row nowrap;
+ flex-flow: row nowrap;
+ -webkit-box-pack: start;
+ -ms-flex-pack: start;
+ justify-content: flex-start;
+}
+.navbar-expand > .container,
+.navbar-expand > .container-fluid {
+ padding-right: 0;
+ padding-left: 0;
+}
+.navbar-expand .navbar-nav {
+ -webkit-box-orient: horizontal;
+ -webkit-box-direction: normal;
+ -ms-flex-direction: row;
+ flex-direction: row;
+}
+.navbar-expand .navbar-nav .dropdown-menu {
+ position: absolute;
+}
+.navbar-expand .navbar-nav .dropdown-menu-right {
+ right: 0;
+ left: auto;
+}
+.navbar-expand .navbar-nav .nav-link {
+ padding-right: 0.5rem;
+ padding-left: 0.5rem;
+}
+.navbar-expand > .container,
+.navbar-expand > .container-fluid {
+ -ms-flex-wrap: nowrap;
+ flex-wrap: nowrap;
+}
+.navbar-expand .navbar-collapse {
+ display: -webkit-box !important;
+ display: -ms-flexbox !important;
+ display: flex !important;
+ -ms-flex-preferred-size: auto;
+ flex-basis: auto;
+}
+.navbar-expand .navbar-toggler {
+ display: none;
+}
+.navbar-expand .dropup .dropdown-menu {
+ top: auto;
+ bottom: 100%;
+}
+
+.navbar-light .navbar-brand {
+ color: rgba(0, 0, 0, 0.9);
+}
+.navbar-light .navbar-brand:hover, .navbar-light .navbar-brand:focus {
+ color: rgba(0, 0, 0, 0.9);
+}
+.navbar-light .navbar-nav .nav-link {
+ color: rgba(0, 0, 0, 0.5);
+}
+.navbar-light .navbar-nav .nav-link:hover, .navbar-light .navbar-nav .nav-link:focus {
+ color: rgba(0, 0, 0, 0.7);
+}
+.navbar-light .navbar-nav .nav-link.disabled {
+ color: rgba(0, 0, 0, 0.3);
+}
+.navbar-light .navbar-nav .show > .nav-link,
+.navbar-light .navbar-nav .active > .nav-link,
+.navbar-light .navbar-nav .nav-link.show,
+.navbar-light .navbar-nav .nav-link.active {
+ color: rgba(0, 0, 0, 0.9);
+}
+.navbar-light .navbar-toggler {
+ color: rgba(0, 0, 0, 0.5);
+ border-color: rgba(0, 0, 0, 0.1);
+}
+.navbar-light .navbar-toggler-icon {
+ background-image: url("data:image/svg+xml;charset=utf8,%3Csvg viewBox='0 0 30 30' xmlns='http://www.w3.org/2000/svg'%3E%3Cpath stroke='rgba(0, 0, 0, 0.5)' stroke-width='2' stroke-linecap='round' stroke-miterlimit='10' d='M4 7h22M4 15h22M4 23h22'/%3E%3C/svg%3E");
+}
+.navbar-light .navbar-text {
+ color: rgba(0, 0, 0, 0.5);
+}
+.navbar-light .navbar-text a {
+ color: rgba(0, 0, 0, 0.9);
+}
+.navbar-light .navbar-text a:hover, .navbar-light .navbar-text a:focus {
+ color: rgba(0, 0, 0, 0.9);
+}
+
+.navbar-dark .navbar-brand {
+ color: #fff;
+}
+.navbar-dark .navbar-brand:hover, .navbar-dark .navbar-brand:focus {
+ color: #fff;
+}
+.navbar-dark .navbar-nav .nav-link {
+ color: rgba(255, 255, 255, 0.5);
+}
+.navbar-dark .navbar-nav .nav-link:hover, .navbar-dark .navbar-nav .nav-link:focus {
+ color: rgba(255, 255, 255, 0.75);
+}
+.navbar-dark .navbar-nav .nav-link.disabled {
+ color: rgba(255, 255, 255, 0.25);
+}
+.navbar-dark .navbar-nav .show > .nav-link,
+.navbar-dark .navbar-nav .active > .nav-link,
+.navbar-dark .navbar-nav .nav-link.show,
+.navbar-dark .navbar-nav .nav-link.active {
+ color: #fff;
+}
+.navbar-dark .navbar-toggler {
+ color: rgba(255, 255, 255, 0.5);
+ border-color: rgba(255, 255, 255, 0.1);
+}
+.navbar-dark .navbar-toggler-icon {
+ background-image: url("data:image/svg+xml;charset=utf8,%3Csvg viewBox='0 0 30 30' xmlns='http://www.w3.org/2000/svg'%3E%3Cpath stroke='rgba(255, 255, 255, 0.5)' stroke-width='2' stroke-linecap='round' stroke-miterlimit='10' d='M4 7h22M4 15h22M4 23h22'/%3E%3C/svg%3E");
+}
+.navbar-dark .navbar-text {
+ color: rgba(255, 255, 255, 0.5);
+}
+.navbar-dark .navbar-text a {
+ color: #fff;
+}
+.navbar-dark .navbar-text a:hover, .navbar-dark .navbar-text a:focus {
+ color: #fff;
+}
+
+.card {
+ position: relative;
+ display: -webkit-box;
+ display: -ms-flexbox;
+ display: flex;
+ -webkit-box-orient: vertical;
+ -webkit-box-direction: normal;
+ -ms-flex-direction: column;
+ flex-direction: column;
+ min-width: 0;
+ word-wrap: break-word;
+ background-color: #fff;
+ background-clip: border-box;
+ border: 1px solid rgba(0, 0, 0, 0.125);
+ border-radius: 0.25rem;
+}
+.card > hr {
+ margin-right: 0;
+ margin-left: 0;
+}
+.card > .list-group:first-child .list-group-item:first-child {
+ border-top-left-radius: 0.25rem;
+ border-top-right-radius: 0.25rem;
+}
+.card > .list-group:last-child .list-group-item:last-child {
+ border-bottom-right-radius: 0.25rem;
+ border-bottom-left-radius: 0.25rem;
+}
+
+.card-body {
+ -webkit-box-flex: 1;
+ -ms-flex: 1 1 auto;
+ flex: 1 1 auto;
+ padding: 1.25rem;
+}
+
+.card-title {
+ margin-bottom: 0.75rem;
+}
+
+.card-subtitle {
+ margin-top: -0.375rem;
+ margin-bottom: 0;
+}
+
+.card-text:last-child {
+ margin-bottom: 0;
+}
+
+.card-link:hover {
+ text-decoration: none;
+}
+.card-link + .card-link {
+ margin-left: 1.25rem;
+}
+
+.card-header {
+ padding: 0.75rem 1.25rem;
+ margin-bottom: 0;
+ background-color: rgba(0, 0, 0, 0.03);
+ border-bottom: 1px solid rgba(0, 0, 0, 0.125);
+}
+.card-header:first-child {
+ border-radius: calc(0.25rem - 1px) calc(0.25rem - 1px) 0 0;
+}
+.card-header + .list-group .list-group-item:first-child {
+ border-top: 0;
+}
+
+.card-footer {
+ padding: 0.75rem 1.25rem;
+ background-color: rgba(0, 0, 0, 0.03);
+ border-top: 1px solid rgba(0, 0, 0, 0.125);
+}
+.card-footer:last-child {
+ border-radius: 0 0 calc(0.25rem - 1px) calc(0.25rem - 1px);
+}
+
+.card-header-tabs {
+ margin-right: -0.625rem;
+ margin-bottom: -0.75rem;
+ margin-left: -0.625rem;
+ border-bottom: 0;
+}
+
+.card-header-pills {
+ margin-right: -0.625rem;
+ margin-left: -0.625rem;
+}
+
+.card-img-overlay {
+ position: absolute;
+ top: 0;
+ right: 0;
+ bottom: 0;
+ left: 0;
+ padding: 1.25rem;
+}
+
+.card-img {
+ width: 100%;
+ border-radius: calc(0.25rem - 1px);
+}
+
+.card-img-top {
+ width: 100%;
+ border-top-left-radius: calc(0.25rem - 1px);
+ border-top-right-radius: calc(0.25rem - 1px);
+}
+
+.card-img-bottom {
+ width: 100%;
+ border-bottom-right-radius: calc(0.25rem - 1px);
+ border-bottom-left-radius: calc(0.25rem - 1px);
+}
+
+.card-deck {
+ display: -webkit-box;
+ display: -ms-flexbox;
+ display: flex;
+ -webkit-box-orient: vertical;
+ -webkit-box-direction: normal;
+ -ms-flex-direction: column;
+ flex-direction: column;
+}
+.card-deck .card {
+ margin-bottom: 15px;
+}
+@media (min-width: 576px) {
+ .card-deck {
+ -webkit-box-orient: horizontal;
+ -webkit-box-direction: normal;
+ -ms-flex-flow: row wrap;
+ flex-flow: row wrap;
+ margin-right: -15px;
+ margin-left: -15px;
+ }
+ .card-deck .card {
+ display: -webkit-box;
+ display: -ms-flexbox;
+ display: flex;
+ -webkit-box-flex: 1;
+ -ms-flex: 1 0 0%;
+ flex: 1 0 0%;
+ -webkit-box-orient: vertical;
+ -webkit-box-direction: normal;
+ -ms-flex-direction: column;
+ flex-direction: column;
+ margin-right: 15px;
+ margin-bottom: 0;
+ margin-left: 15px;
+ }
+}
+
+.card-group {
+ display: -webkit-box;
+ display: -ms-flexbox;
+ display: flex;
+ -webkit-box-orient: vertical;
+ -webkit-box-direction: normal;
+ -ms-flex-direction: column;
+ flex-direction: column;
+}
+.card-group > .card {
+ margin-bottom: 15px;
+}
+@media (min-width: 576px) {
+ .card-group {
+ -webkit-box-orient: horizontal;
+ -webkit-box-direction: normal;
+ -ms-flex-flow: row wrap;
+ flex-flow: row wrap;
+ }
+ .card-group > .card {
+ -webkit-box-flex: 1;
+ -ms-flex: 1 0 0%;
+ flex: 1 0 0%;
+ margin-bottom: 0;
+ }
+ .card-group > .card + .card {
+ margin-left: 0;
+ border-left: 0;
+ }
+ .card-group > .card:first-child {
+ border-top-right-radius: 0;
+ border-bottom-right-radius: 0;
+ }
+ .card-group > .card:first-child .card-img-top,
+ .card-group > .card:first-child .card-header {
+ border-top-right-radius: 0;
+ }
+ .card-group > .card:first-child .card-img-bottom,
+ .card-group > .card:first-child .card-footer {
+ border-bottom-right-radius: 0;
+ }
+ .card-group > .card:last-child {
+ border-top-left-radius: 0;
+ border-bottom-left-radius: 0;
+ }
+ .card-group > .card:last-child .card-img-top,
+ .card-group > .card:last-child .card-header {
+ border-top-left-radius: 0;
+ }
+ .card-group > .card:last-child .card-img-bottom,
+ .card-group > .card:last-child .card-footer {
+ border-bottom-left-radius: 0;
+ }
+ .card-group > .card:only-child {
+ border-radius: 0.25rem;
+ }
+ .card-group > .card:only-child .card-img-top,
+ .card-group > .card:only-child .card-header {
+ border-top-left-radius: 0.25rem;
+ border-top-right-radius: 0.25rem;
+ }
+ .card-group > .card:only-child .card-img-bottom,
+ .card-group > .card:only-child .card-footer {
+ border-bottom-right-radius: 0.25rem;
+ border-bottom-left-radius: 0.25rem;
+ }
+ .card-group > .card:not(:first-child):not(:last-child):not(:only-child) {
+ border-radius: 0;
+ }
+ .card-group > .card:not(:first-child):not(:last-child):not(:only-child) .card-img-top,
+ .card-group > .card:not(:first-child):not(:last-child):not(:only-child) .card-img-bottom,
+ .card-group > .card:not(:first-child):not(:last-child):not(:only-child) .card-header,
+ .card-group > .card:not(:first-child):not(:last-child):not(:only-child) .card-footer {
+ border-radius: 0;
+ }
+}
+
+.card-columns .card {
+ margin-bottom: 0.75rem;
+}
+@media (min-width: 576px) {
+ .card-columns {
+ -webkit-column-count: 3;
+ -moz-column-count: 3;
+ column-count: 3;
+ -webkit-column-gap: 1.25rem;
+ -moz-column-gap: 1.25rem;
+ column-gap: 1.25rem;
+ }
+ .card-columns .card {
+ display: inline-block;
+ width: 100%;
+ }
+}
+
+.breadcrumb {
+ display: -webkit-box;
+ display: -ms-flexbox;
+ display: flex;
+ -ms-flex-wrap: wrap;
+ flex-wrap: wrap;
+ padding: 0.75rem 1rem;
+ margin-bottom: 1rem;
+ list-style: none;
+ background-color: #e9ecef;
+ border-radius: 0.25rem;
+}
+
+.breadcrumb-item + .breadcrumb-item::before {
+ display: inline-block;
+ padding-right: 0.5rem;
+ padding-left: 0.5rem;
+ color: #6c757d;
+ content: "/";
+}
+.breadcrumb-item + .breadcrumb-item:hover::before {
+ text-decoration: underline;
+}
+.breadcrumb-item + .breadcrumb-item:hover::before {
+ text-decoration: none;
+}
+.breadcrumb-item.active {
+ color: #6c757d;
+}
+
+.pagination {
+ display: -webkit-box;
+ display: -ms-flexbox;
+ display: flex;
+ padding-left: 0;
+ list-style: none;
+ border-radius: 0.25rem;
+}
+
+.page-link {
+ position: relative;
+ display: block;
+ padding: 0.5rem 0.75rem;
+ margin-left: -1px;
+ line-height: 1.25;
+ color: #007bff;
+ background-color: #fff;
+ border: 1px solid #dee2e6;
+}
+.page-link:hover {
+ color: #0056b3;
+ text-decoration: none;
+ background-color: #e9ecef;
+ border-color: #dee2e6;
+}
+.page-link:focus {
+ z-index: 2;
+ outline: 0;
+ -webkit-box-shadow: 0 0 0 0.2rem rgba(0, 123, 255, 0.25);
+ box-shadow: 0 0 0 0.2rem rgba(0, 123, 255, 0.25);
+}
+.page-link:not(:disabled):not(.disabled) {
+ cursor: pointer;
+}
+
+.page-item:first-child .page-link {
+ margin-left: 0;
+ border-top-left-radius: 0.25rem;
+ border-bottom-left-radius: 0.25rem;
+}
+.page-item:last-child .page-link {
+ border-top-right-radius: 0.25rem;
+ border-bottom-right-radius: 0.25rem;
+}
+.page-item.active .page-link {
+ z-index: 1;
+ color: #fff;
+ background-color: #007bff;
+ border-color: #007bff;
+}
+.page-item.disabled .page-link {
+ color: #6c757d;
+ pointer-events: none;
+ cursor: auto;
+ background-color: #fff;
+ border-color: #dee2e6;
+}
+
+.pagination-lg .page-link {
+ padding: 0.75rem 1.5rem;
+ font-size: 1.25rem;
+ line-height: 1.5;
+}
+.pagination-lg .page-item:first-child .page-link {
+ border-top-left-radius: 0.3rem;
+ border-bottom-left-radius: 0.3rem;
+}
+.pagination-lg .page-item:last-child .page-link {
+ border-top-right-radius: 0.3rem;
+ border-bottom-right-radius: 0.3rem;
+}
+
+.pagination-sm .page-link {
+ padding: 0.25rem 0.5rem;
+ font-size: 0.875rem;
+ line-height: 1.5;
+}
+.pagination-sm .page-item:first-child .page-link {
+ border-top-left-radius: 0.2rem;
+ border-bottom-left-radius: 0.2rem;
+}
+.pagination-sm .page-item:last-child .page-link {
+ border-top-right-radius: 0.2rem;
+ border-bottom-right-radius: 0.2rem;
+}
+
+.badge {
+ display: inline-block;
+ padding: 0.25em 0.4em;
+ font-size: 75%;
+ font-weight: 700;
+ line-height: 1;
+ text-align: center;
+ white-space: nowrap;
+ vertical-align: baseline;
+ border-radius: 0.25rem;
+}
+.badge:empty {
+ display: none;
+}
+
+.btn .badge {
+ position: relative;
+ top: -1px;
+}
+
+.badge-pill {
+ padding-right: 0.6em;
+ padding-left: 0.6em;
+ border-radius: 10rem;
+}
+
+.badge-primary {
+ color: #fff;
+ background-color: #007bff;
+}
+.badge-primary[href]:hover, .badge-primary[href]:focus {
+ color: #fff;
+ text-decoration: none;
+ background-color: #0062cc;
+}
+
+.badge-secondary {
+ color: #fff;
+ background-color: #6c757d;
+}
+.badge-secondary[href]:hover, .badge-secondary[href]:focus {
+ color: #fff;
+ text-decoration: none;
+ background-color: #545b62;
+}
+
+.badge-success {
+ color: #fff;
+ background-color: #28a745;
+}
+.badge-success[href]:hover, .badge-success[href]:focus {
+ color: #fff;
+ text-decoration: none;
+ background-color: #1e7e34;
+}
+
+.badge-info {
+ color: #fff;
+ background-color: #17a2b8;
+}
+.badge-info[href]:hover, .badge-info[href]:focus {
+ color: #fff;
+ text-decoration: none;
+ background-color: #117a8b;
+}
+
+.badge-warning {
+ color: #212529;
+ background-color: #ffc107;
+}
+.badge-warning[href]:hover, .badge-warning[href]:focus {
+ color: #212529;
+ text-decoration: none;
+ background-color: #d39e00;
+}
+
+.badge-danger {
+ color: #fff;
+ background-color: #dc3545;
+}
+.badge-danger[href]:hover, .badge-danger[href]:focus {
+ color: #fff;
+ text-decoration: none;
+ background-color: #bd2130;
+}
+
+.badge-light {
+ color: #212529;
+ background-color: #f8f9fa;
+}
+.badge-light[href]:hover, .badge-light[href]:focus {
+ color: #212529;
+ text-decoration: none;
+ background-color: #dae0e5;
+}
+
+.badge-dark {
+ color: #fff;
+ background-color: #343a40;
+}
+.badge-dark[href]:hover, .badge-dark[href]:focus {
+ color: #fff;
+ text-decoration: none;
+ background-color: #1d2124;
+}
+
+.jumbotron {
+ padding: 2rem 1rem;
+ margin-bottom: 2rem;
+ background-color: #e9ecef;
+ border-radius: 0.3rem;
+}
+@media (min-width: 576px) {
+ .jumbotron {
+ padding: 4rem 2rem;
+ }
+}
+
+.jumbotron-fluid {
+ padding-right: 0;
+ padding-left: 0;
+ border-radius: 0;
+}
+
+.alert {
+ position: relative;
+ padding: 0.75rem 1.25rem;
+ margin-bottom: 1rem;
+ border: 1px solid transparent;
+ border-radius: 0.25rem;
+}
+
+.alert-heading {
+ color: inherit;
+}
+
+.alert-link {
+ font-weight: 700;
+}
+
+.alert-dismissible {
+ padding-right: 4rem;
+}
+.alert-dismissible .close {
+ position: absolute;
+ top: 0;
+ right: 0;
+ padding: 0.75rem 1.25rem;
+ color: inherit;
+}
+
+.alert-primary {
+ color: #004085;
+ background-color: #cce5ff;
+ border-color: #b8daff;
+}
+.alert-primary hr {
+ border-top-color: #9fcdff;
+}
+.alert-primary .alert-link {
+ color: #002752;
+}
+
+.alert-secondary {
+ color: #383d41;
+ background-color: #e2e3e5;
+ border-color: #d6d8db;
+}
+.alert-secondary hr {
+ border-top-color: #c8cbcf;
+}
+.alert-secondary .alert-link {
+ color: #202326;
+}
+
+.alert-success {
+ color: #155724;
+ background-color: #d4edda;
+ border-color: #c3e6cb;
+}
+.alert-success hr {
+ border-top-color: #b1dfbb;
+}
+.alert-success .alert-link {
+ color: #0b2e13;
+}
+
+.alert-info {
+ color: #0c5460;
+ background-color: #d1ecf1;
+ border-color: #bee5eb;
+}
+.alert-info hr {
+ border-top-color: #abdde5;
+}
+.alert-info .alert-link {
+ color: #062c33;
+}
+
+.alert-warning {
+ color: #856404;
+ background-color: #fff3cd;
+ border-color: #ffeeba;
+}
+.alert-warning hr {
+ border-top-color: #ffe8a1;
+}
+.alert-warning .alert-link {
+ color: #533f03;
+}
+
+.alert-danger {
+ color: #721c24;
+ background-color: #f8d7da;
+ border-color: #f5c6cb;
+}
+.alert-danger hr {
+ border-top-color: #f1b0b7;
+}
+.alert-danger .alert-link {
+ color: #491217;
+}
+
+.alert-light {
+ color: #818182;
+ background-color: #fefefe;
+ border-color: #fdfdfe;
+}
+.alert-light hr {
+ border-top-color: #ececf6;
+}
+.alert-light .alert-link {
+ color: #686868;
+}
+
+.alert-dark {
+ color: #1b1e21;
+ background-color: #d6d8d9;
+ border-color: #c6c8ca;
+}
+.alert-dark hr {
+ border-top-color: #b9bbbe;
+}
+.alert-dark .alert-link {
+ color: #040505;
+}
+
+@-webkit-keyframes progress-bar-stripes {
+ from {
+ background-position: 1rem 0;
+ }
+ to {
+ background-position: 0 0;
+ }
+}
+
+@keyframes progress-bar-stripes {
+ from {
+ background-position: 1rem 0;
+ }
+ to {
+ background-position: 0 0;
+ }
+}
+.progress {
+ display: -webkit-box;
+ display: -ms-flexbox;
+ display: flex;
+ height: 1rem;
+ overflow: hidden;
+ font-size: 0.75rem;
+ background-color: #e9ecef;
+ border-radius: 0.25rem;
+}
+
+.progress-bar {
+ display: -webkit-box;
+ display: -ms-flexbox;
+ display: flex;
+ -webkit-box-orient: vertical;
+ -webkit-box-direction: normal;
+ -ms-flex-direction: column;
+ flex-direction: column;
+ -webkit-box-pack: center;
+ -ms-flex-pack: center;
+ justify-content: center;
+ color: #fff;
+ text-align: center;
+ background-color: #007bff;
+ -webkit-transition: width 0.6s ease;
+ transition: width 0.6s ease;
+}
+
+.progress-bar-striped {
+ background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
+ background-size: 1rem 1rem;
+}
+
+.progress-bar-animated {
+ -webkit-animation: progress-bar-stripes 1s linear infinite;
+ animation: progress-bar-stripes 1s linear infinite;
+}
+
+.media {
+ display: -webkit-box;
+ display: -ms-flexbox;
+ display: flex;
+ -webkit-box-align: start;
+ -ms-flex-align: start;
+ align-items: flex-start;
+}
+
+.media-body {
+ -webkit-box-flex: 1;
+ -ms-flex: 1;
+ flex: 1;
+}
+
+.list-group {
+ display: -webkit-box;
+ display: -ms-flexbox;
+ display: flex;
+ -webkit-box-orient: vertical;
+ -webkit-box-direction: normal;
+ -ms-flex-direction: column;
+ flex-direction: column;
+ padding-left: 0;
+ margin-bottom: 0;
+}
+
+.list-group-item-action {
+ width: 100%;
+ color: #495057;
+ text-align: inherit;
+}
+.list-group-item-action:hover, .list-group-item-action:focus {
+ color: #495057;
+ text-decoration: none;
+ background-color: #f8f9fa;
+}
+.list-group-item-action:active {
+ color: #212529;
+ background-color: #e9ecef;
+}
+
+.list-group-item {
+ position: relative;
+ display: block;
+ padding: 0.75rem 1.25rem;
+ margin-bottom: -1px;
+ background-color: #fff;
+ border: 1px solid rgba(0, 0, 0, 0.125);
+}
+.list-group-item:first-child {
+ border-top-left-radius: 0.25rem;
+ border-top-right-radius: 0.25rem;
+}
+.list-group-item:last-child {
+ margin-bottom: 0;
+ border-bottom-right-radius: 0.25rem;
+ border-bottom-left-radius: 0.25rem;
+}
+.list-group-item:hover, .list-group-item:focus {
+ z-index: 1;
+ text-decoration: none;
+}
+.list-group-item.disabled, .list-group-item:disabled {
+ color: #6c757d;
+ background-color: #fff;
+}
+.list-group-item.active {
+ z-index: 2;
+ color: #fff;
+ background-color: #007bff;
+ border-color: #007bff;
+}
+
+.list-group-flush .list-group-item {
+ border-right: 0;
+ border-left: 0;
+ border-radius: 0;
+}
+.list-group-flush:first-child .list-group-item:first-child {
+ border-top: 0;
+}
+.list-group-flush:last-child .list-group-item:last-child {
+ border-bottom: 0;
+}
+
+.list-group-item-primary {
+ color: #004085;
+ background-color: #b8daff;
+}
+.list-group-item-primary.list-group-item-action:hover, .list-group-item-primary.list-group-item-action:focus {
+ color: #004085;
+ background-color: #9fcdff;
+}
+.list-group-item-primary.list-group-item-action.active {
+ color: #fff;
+ background-color: #004085;
+ border-color: #004085;
+}
+
+.list-group-item-secondary {
+ color: #383d41;
+ background-color: #d6d8db;
+}
+.list-group-item-secondary.list-group-item-action:hover, .list-group-item-secondary.list-group-item-action:focus {
+ color: #383d41;
+ background-color: #c8cbcf;
+}
+.list-group-item-secondary.list-group-item-action.active {
+ color: #fff;
+ background-color: #383d41;
+ border-color: #383d41;
+}
+
+.list-group-item-success {
+ color: #155724;
+ background-color: #c3e6cb;
+}
+.list-group-item-success.list-group-item-action:hover, .list-group-item-success.list-group-item-action:focus {
+ color: #155724;
+ background-color: #b1dfbb;
+}
+.list-group-item-success.list-group-item-action.active {
+ color: #fff;
+ background-color: #155724;
+ border-color: #155724;
+}
+
+.list-group-item-info {
+ color: #0c5460;
+ background-color: #bee5eb;
+}
+.list-group-item-info.list-group-item-action:hover, .list-group-item-info.list-group-item-action:focus {
+ color: #0c5460;
+ background-color: #abdde5;
+}
+.list-group-item-info.list-group-item-action.active {
+ color: #fff;
+ background-color: #0c5460;
+ border-color: #0c5460;
+}
+
+.list-group-item-warning {
+ color: #856404;
+ background-color: #ffeeba;
+}
+.list-group-item-warning.list-group-item-action:hover, .list-group-item-warning.list-group-item-action:focus {
+ color: #856404;
+ background-color: #ffe8a1;
+}
+.list-group-item-warning.list-group-item-action.active {
+ color: #fff;
+ background-color: #856404;
+ border-color: #856404;
+}
+
+.list-group-item-danger {
+ color: #721c24;
+ background-color: #f5c6cb;
+}
+.list-group-item-danger.list-group-item-action:hover, .list-group-item-danger.list-group-item-action:focus {
+ color: #721c24;
+ background-color: #f1b0b7;
+}
+.list-group-item-danger.list-group-item-action.active {
+ color: #fff;
+ background-color: #721c24;
+ border-color: #721c24;
+}
+
+.list-group-item-light {
+ color: #818182;
+ background-color: #fdfdfe;
+}
+.list-group-item-light.list-group-item-action:hover, .list-group-item-light.list-group-item-action:focus {
+ color: #818182;
+ background-color: #ececf6;
+}
+.list-group-item-light.list-group-item-action.active {
+ color: #fff;
+ background-color: #818182;
+ border-color: #818182;
+}
+
+.list-group-item-dark {
+ color: #1b1e21;
+ background-color: #c6c8ca;
+}
+.list-group-item-dark.list-group-item-action:hover, .list-group-item-dark.list-group-item-action:focus {
+ color: #1b1e21;
+ background-color: #b9bbbe;
+}
+.list-group-item-dark.list-group-item-action.active {
+ color: #fff;
+ background-color: #1b1e21;
+ border-color: #1b1e21;
+}
+
+.close {
+ float: right;
+ font-size: 1.5rem;
+ font-weight: 700;
+ line-height: 1;
+ color: #000;
+ text-shadow: 0 1px 0 #fff;
+ opacity: .5;
+}
+.close:hover, .close:focus {
+ color: #000;
+ text-decoration: none;
+ opacity: .75;
+}
+.close:not(:disabled):not(.disabled) {
+ cursor: pointer;
+}
+
+button.close {
+ padding: 0;
+ background-color: transparent;
+ border: 0;
+ -webkit-appearance: none;
+}
+
+.modal-open {
+ overflow: hidden;
+}
+
+.modal {
+ position: fixed;
+ top: 0;
+ right: 0;
+ bottom: 0;
+ left: 0;
+ z-index: 1050;
+ display: none;
+ overflow: hidden;
+ outline: 0;
+}
+.modal-open .modal {
+ overflow-x: hidden;
+ overflow-y: auto;
+}
+
+.modal-dialog {
+ position: relative;
+ width: auto;
+ margin: 0.5rem;
+ pointer-events: none;
+}
+.modal.fade .modal-dialog {
+ -webkit-transition: -webkit-transform 0.3s ease-out;
+ transition: -webkit-transform 0.3s ease-out;
+ transition: transform 0.3s ease-out;
+ transition: transform 0.3s ease-out, -webkit-transform 0.3s ease-out;
+ -webkit-transform: translate(0, -25%);
+ transform: translate(0, -25%);
+}
+.modal.show .modal-dialog {
+ -webkit-transform: translate(0, 0);
+ transform: translate(0, 0);
+}
+
+.modal-dialog-centered {
+ display: -webkit-box;
+ display: -ms-flexbox;
+ display: flex;
+ -webkit-box-align: center;
+ -ms-flex-align: center;
+ align-items: center;
+ min-height: calc(100% - (0.5rem * 2));
+}
+
+.modal-content {
+ position: relative;
+ display: -webkit-box;
+ display: -ms-flexbox;
+ display: flex;
+ -webkit-box-orient: vertical;
+ -webkit-box-direction: normal;
+ -ms-flex-direction: column;
+ flex-direction: column;
+ width: 100%;
+ pointer-events: auto;
+ background-color: #fff;
+ background-clip: padding-box;
+ border: 1px solid rgba(0, 0, 0, 0.2);
+ border-radius: 0.3rem;
+ outline: 0;
+}
+
+.modal-backdrop {
+ position: fixed;
+ top: 0;
+ right: 0;
+ bottom: 0;
+ left: 0;
+ z-index: 1040;
+ background-color: #000;
+}
+.modal-backdrop.fade {
+ opacity: 0;
+}
+.modal-backdrop.show {
+ opacity: 0.5;
+}
+
+.modal-header {
+ display: -webkit-box;
+ display: -ms-flexbox;
+ display: flex;
+ -webkit-box-align: start;
+ -ms-flex-align: start;
+ align-items: flex-start;
+ -webkit-box-pack: justify;
+ -ms-flex-pack: justify;
+ justify-content: space-between;
+ padding: 1rem;
+ border-bottom: 1px solid #e9ecef;
+ border-top-left-radius: 0.3rem;
+ border-top-right-radius: 0.3rem;
+}
+.modal-header .close {
+ padding: 1rem;
+ margin: -1rem -1rem -1rem auto;
+}
+
+.modal-title {
+ margin-bottom: 0;
+ line-height: 1.5;
+}
+
+.modal-body {
+ position: relative;
+ -webkit-box-flex: 1;
+ -ms-flex: 1 1 auto;
+ flex: 1 1 auto;
+ padding: 1rem;
+}
+
+.modal-footer {
+ display: -webkit-box;
+ display: -ms-flexbox;
+ display: flex;
+ -webkit-box-align: center;
+ -ms-flex-align: center;
+ align-items: center;
+ -webkit-box-pack: end;
+ -ms-flex-pack: end;
+ justify-content: flex-end;
+ padding: 1rem;
+ border-top: 1px solid #e9ecef;
+}
+.modal-footer > :not(:first-child) {
+ margin-left: .25rem;
+}
+.modal-footer > :not(:last-child) {
+ margin-right: .25rem;
+}
+
+.modal-scrollbar-measure {
+ position: absolute;
+ top: -9999px;
+ width: 50px;
+ height: 50px;
+ overflow: scroll;
+}
+
+@media (min-width: 576px) {
+ .modal-dialog {
+ max-width: 500px;
+ margin: 1.75rem auto;
+ }
+
+ .modal-dialog-centered {
+ min-height: calc(100% - (1.75rem * 2));
+ }
+
+ .modal-sm {
+ max-width: 300px;
+ }
+}
+@media (min-width: 992px) {
+ .modal-lg {
+ max-width: 800px;
+ }
+}
+.tooltip {
+ position: absolute;
+ z-index: 1070;
+ display: block;
+ margin: 0;
+ font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, "Helvetica Neue", Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";
+ font-style: normal;
+ font-weight: 400;
+ line-height: 1.5;
+ text-align: left;
+ text-align: start;
+ text-decoration: none;
+ text-shadow: none;
+ text-transform: none;
+ letter-spacing: normal;
+ word-break: normal;
+ word-spacing: normal;
+ white-space: normal;
+ line-break: auto;
+ font-size: 0.875rem;
+ word-wrap: break-word;
+ opacity: 0;
+}
+.tooltip.show {
+ opacity: 0.9;
+}
+.tooltip .arrow {
+ position: absolute;
+ display: block;
+ width: 0.8rem;
+ height: 0.4rem;
+}
+.tooltip .arrow::before {
+ position: absolute;
+ content: "";
+ border-color: transparent;
+ border-style: solid;
+}
+
+.bs-tooltip-top, .bs-tooltip-auto[x-placement^="top"] {
+ padding: 0.4rem 0;
+}
+.bs-tooltip-top .arrow, .bs-tooltip-auto[x-placement^="top"] .arrow {
+ bottom: 0;
+}
+.bs-tooltip-top .arrow::before, .bs-tooltip-auto[x-placement^="top"] .arrow::before {
+ top: 0;
+ border-width: 0.4rem 0.4rem 0;
+ border-top-color: #000;
+}
+
+.bs-tooltip-right, .bs-tooltip-auto[x-placement^="right"] {
+ padding: 0 0.4rem;
+}
+.bs-tooltip-right .arrow, .bs-tooltip-auto[x-placement^="right"] .arrow {
+ left: 0;
+ width: 0.4rem;
+ height: 0.8rem;
+}
+.bs-tooltip-right .arrow::before, .bs-tooltip-auto[x-placement^="right"] .arrow::before {
+ right: 0;
+ border-width: 0.4rem 0.4rem 0.4rem 0;
+ border-right-color: #000;
+}
+
+.bs-tooltip-bottom, .bs-tooltip-auto[x-placement^="bottom"] {
+ padding: 0.4rem 0;
+}
+.bs-tooltip-bottom .arrow, .bs-tooltip-auto[x-placement^="bottom"] .arrow {
+ top: 0;
+}
+.bs-tooltip-bottom .arrow::before, .bs-tooltip-auto[x-placement^="bottom"] .arrow::before {
+ bottom: 0;
+ border-width: 0 0.4rem 0.4rem;
+ border-bottom-color: #000;
+}
+
+.bs-tooltip-left, .bs-tooltip-auto[x-placement^="left"] {
+ padding: 0 0.4rem;
+}
+.bs-tooltip-left .arrow, .bs-tooltip-auto[x-placement^="left"] .arrow {
+ right: 0;
+ width: 0.4rem;
+ height: 0.8rem;
+}
+.bs-tooltip-left .arrow::before, .bs-tooltip-auto[x-placement^="left"] .arrow::before {
+ left: 0;
+ border-width: 0.4rem 0 0.4rem 0.4rem;
+ border-left-color: #000;
+}
+
+.tooltip-inner {
+ max-width: 200px;
+ padding: 0.25rem 0.5rem;
+ color: #fff;
+ text-align: center;
+ background-color: #000;
+ border-radius: 0.25rem;
+}
+
+.popover {
+ position: absolute;
+ top: 0;
+ left: 0;
+ z-index: 1060;
+ display: block;
+ max-width: 276px;
+ font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, "Helvetica Neue", Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";
+ font-style: normal;
+ font-weight: 400;
+ line-height: 1.5;
+ text-align: left;
+ text-align: start;
+ text-decoration: none;
+ text-shadow: none;
+ text-transform: none;
+ letter-spacing: normal;
+ word-break: normal;
+ word-spacing: normal;
+ white-space: normal;
+ line-break: auto;
+ font-size: 0.875rem;
+ word-wrap: break-word;
+ background-color: #fff;
+ background-clip: padding-box;
+ border: 1px solid rgba(0, 0, 0, 0.2);
+ border-radius: 0.3rem;
+}
+.popover .arrow {
+ position: absolute;
+ display: block;
+ width: 1rem;
+ height: 0.5rem;
+ margin: 0 0.3rem;
+}
+.popover .arrow::before, .popover .arrow::after {
+ position: absolute;
+ display: block;
+ content: "";
+ border-color: transparent;
+ border-style: solid;
+}
+
+.bs-popover-top, .bs-popover-auto[x-placement^="top"] {
+ margin-bottom: 0.5rem;
+}
+.bs-popover-top .arrow, .bs-popover-auto[x-placement^="top"] .arrow {
+ bottom: calc((0.5rem + 1px) * -1);
+}
+.bs-popover-top .arrow::before, .bs-popover-auto[x-placement^="top"] .arrow::before,
+.bs-popover-top .arrow::after,
+.bs-popover-auto[x-placement^="top"] .arrow::after {
+ border-width: 0.5rem 0.5rem 0;
+}
+.bs-popover-top .arrow::before, .bs-popover-auto[x-placement^="top"] .arrow::before {
+ bottom: 0;
+ border-top-color: rgba(0, 0, 0, 0.25);
+}
+.bs-popover-top .arrow::after, .bs-popover-auto[x-placement^="top"] .arrow::after {
+ bottom: 1px;
+ border-top-color: #fff;
+}
+
+.bs-popover-right, .bs-popover-auto[x-placement^="right"] {
+ margin-left: 0.5rem;
+}
+.bs-popover-right .arrow, .bs-popover-auto[x-placement^="right"] .arrow {
+ left: calc((0.5rem + 1px) * -1);
+ width: 0.5rem;
+ height: 1rem;
+ margin: 0.3rem 0;
+}
+.bs-popover-right .arrow::before, .bs-popover-auto[x-placement^="right"] .arrow::before,
+.bs-popover-right .arrow::after,
+.bs-popover-auto[x-placement^="right"] .arrow::after {
+ border-width: 0.5rem 0.5rem 0.5rem 0;
+}
+.bs-popover-right .arrow::before, .bs-popover-auto[x-placement^="right"] .arrow::before {
+ left: 0;
+ border-right-color: rgba(0, 0, 0, 0.25);
+}
+.bs-popover-right .arrow::after, .bs-popover-auto[x-placement^="right"] .arrow::after {
+ left: 1px;
+ border-right-color: #fff;
+}
+
+.bs-popover-bottom, .bs-popover-auto[x-placement^="bottom"] {
+ margin-top: 0.5rem;
+}
+.bs-popover-bottom .arrow, .bs-popover-auto[x-placement^="bottom"] .arrow {
+ top: calc((0.5rem + 1px) * -1);
+}
+.bs-popover-bottom .arrow::before, .bs-popover-auto[x-placement^="bottom"] .arrow::before,
+.bs-popover-bottom .arrow::after,
+.bs-popover-auto[x-placement^="bottom"] .arrow::after {
+ border-width: 0 0.5rem 0.5rem 0.5rem;
+}
+.bs-popover-bottom .arrow::before, .bs-popover-auto[x-placement^="bottom"] .arrow::before {
+ top: 0;
+ border-bottom-color: rgba(0, 0, 0, 0.25);
+}
+.bs-popover-bottom .arrow::after, .bs-popover-auto[x-placement^="bottom"] .arrow::after {
+ top: 1px;
+ border-bottom-color: #fff;
+}
+.bs-popover-bottom .popover-header::before, .bs-popover-auto[x-placement^="bottom"] .popover-header::before {
+ position: absolute;
+ top: 0;
+ left: 50%;
+ display: block;
+ width: 1rem;
+ margin-left: -0.5rem;
+ content: "";
+ border-bottom: 1px solid #f7f7f7;
+}
+
+.bs-popover-left, .bs-popover-auto[x-placement^="left"] {
+ margin-right: 0.5rem;
+}
+.bs-popover-left .arrow, .bs-popover-auto[x-placement^="left"] .arrow {
+ right: calc((0.5rem + 1px) * -1);
+ width: 0.5rem;
+ height: 1rem;
+ margin: 0.3rem 0;
+}
+.bs-popover-left .arrow::before, .bs-popover-auto[x-placement^="left"] .arrow::before,
+.bs-popover-left .arrow::after,
+.bs-popover-auto[x-placement^="left"] .arrow::after {
+ border-width: 0.5rem 0 0.5rem 0.5rem;
+}
+.bs-popover-left .arrow::before, .bs-popover-auto[x-placement^="left"] .arrow::before {
+ right: 0;
+ border-left-color: rgba(0, 0, 0, 0.25);
+}
+.bs-popover-left .arrow::after, .bs-popover-auto[x-placement^="left"] .arrow::after {
+ right: 1px;
+ border-left-color: #fff;
+}
+
+.popover-header {
+ padding: 0.5rem 0.75rem;
+ margin-bottom: 0;
+ font-size: 1rem;
+ color: inherit;
+ background-color: #f7f7f7;
+ border-bottom: 1px solid #ebebeb;
+ border-top-left-radius: calc(0.3rem - 1px);
+ border-top-right-radius: calc(0.3rem - 1px);
+}
+.popover-header:empty {
+ display: none;
+}
+
+.popover-body {
+ padding: 0.5rem 0.75rem;
+ color: #212529;
+}
+
+.carousel {
+ position: relative;
+}
+
+.carousel-inner {
+ position: relative;
+ width: 100%;
+ overflow: hidden;
+}
+
+.carousel-item {
+ position: relative;
+ display: none;
+ -webkit-box-align: center;
+ -ms-flex-align: center;
+ align-items: center;
+ width: 100%;
+ -webkit-transition: -webkit-transform 0.6s ease;
+ transition: -webkit-transform 0.6s ease;
+ transition: transform 0.6s ease;
+ transition: transform 0.6s ease, -webkit-transform 0.6s ease;
+ -webkit-backface-visibility: hidden;
+ backface-visibility: hidden;
+ -webkit-perspective: 1000px;
+ perspective: 1000px;
+}
+
+.carousel-item.active,
+.carousel-item-next,
+.carousel-item-prev {
+ display: block;
+}
+
+.carousel-item-next,
+.carousel-item-prev {
+ position: absolute;
+ top: 0;
+}
+
+.carousel-item-next.carousel-item-left,
+.carousel-item-prev.carousel-item-right {
+ -webkit-transform: translateX(0);
+ transform: translateX(0);
+}
+@supports (transform-style: preserve-3d) {
+ .carousel-item-next.carousel-item-left,
+ .carousel-item-prev.carousel-item-right {
+ -webkit-transform: translate3d(0, 0, 0);
+ transform: translate3d(0, 0, 0);
+ }
+}
+
+.carousel-item-next,
+.active.carousel-item-right {
+ -webkit-transform: translateX(100%);
+ transform: translateX(100%);
+}
+@supports (transform-style: preserve-3d) {
+ .carousel-item-next,
+ .active.carousel-item-right {
+ -webkit-transform: translate3d(100%, 0, 0);
+ transform: translate3d(100%, 0, 0);
+ }
+}
+
+.carousel-item-prev,
+.active.carousel-item-left {
+ -webkit-transform: translateX(-100%);
+ transform: translateX(-100%);
+}
+@supports (transform-style: preserve-3d) {
+ .carousel-item-prev,
+ .active.carousel-item-left {
+ -webkit-transform: translate3d(-100%, 0, 0);
+ transform: translate3d(-100%, 0, 0);
+ }
+}
+
+.carousel-control-prev,
+.carousel-control-next {
+ position: absolute;
+ top: 0;
+ bottom: 0;
+ display: -webkit-box;
+ display: -ms-flexbox;
+ display: flex;
+ -webkit-box-align: center;
+ -ms-flex-align: center;
+ align-items: center;
+ -webkit-box-pack: center;
+ -ms-flex-pack: center;
+ justify-content: center;
+ width: 15%;
+ color: #fff;
+ text-align: center;
+ opacity: 0.5;
+}
+.carousel-control-prev:hover, .carousel-control-prev:focus,
+.carousel-control-next:hover,
+.carousel-control-next:focus {
+ color: #fff;
+ text-decoration: none;
+ outline: 0;
+ opacity: .9;
+}
+
+.carousel-control-prev {
+ left: 0;
+}
+
+.carousel-control-next {
+ right: 0;
+}
+
+.carousel-control-prev-icon,
+.carousel-control-next-icon {
+ display: inline-block;
+ width: 20px;
+ height: 20px;
+ background: transparent no-repeat center center;
+ background-size: 100% 100%;
+}
+
+.carousel-control-prev-icon {
+ background-image: url("data:image/svg+xml;charset=utf8,%3Csvg xmlns='http://www.w3.org/2000/svg' fill='%23fff' viewBox='0 0 8 8'%3E%3Cpath d='M5.25 0l-4 4 4 4 1.5-1.5-2.5-2.5 2.5-2.5-1.5-1.5z'/%3E%3C/svg%3E");
+}
+
+.carousel-control-next-icon {
+ background-image: url("data:image/svg+xml;charset=utf8,%3Csvg xmlns='http://www.w3.org/2000/svg' fill='%23fff' viewBox='0 0 8 8'%3E%3Cpath d='M2.75 0l-1.5 1.5 2.5 2.5-2.5 2.5 1.5 1.5 4-4-4-4z'/%3E%3C/svg%3E");
+}
+
+.carousel-indicators {
+ position: absolute;
+ right: 0;
+ bottom: 10px;
+ left: 0;
+ z-index: 15;
+ display: -webkit-box;
+ display: -ms-flexbox;
+ display: flex;
+ -webkit-box-pack: center;
+ -ms-flex-pack: center;
+ justify-content: center;
+ padding-left: 0;
+ margin-right: 15%;
+ margin-left: 15%;
+ list-style: none;
+}
+.carousel-indicators li {
+ position: relative;
+ -webkit-box-flex: 0;
+ -ms-flex: 0 1 auto;
+ flex: 0 1 auto;
+ width: 30px;
+ height: 3px;
+ margin-right: 3px;
+ margin-left: 3px;
+ text-indent: -999px;
+ background-color: rgba(255, 255, 255, 0.5);
+}
+.carousel-indicators li::before {
+ position: absolute;
+ top: -10px;
+ left: 0;
+ display: inline-block;
+ width: 100%;
+ height: 10px;
+ content: "";
+}
+.carousel-indicators li::after {
+ position: absolute;
+ bottom: -10px;
+ left: 0;
+ display: inline-block;
+ width: 100%;
+ height: 10px;
+ content: "";
+}
+.carousel-indicators .active {
+ background-color: #fff;
+}
+
+.carousel-caption {
+ position: absolute;
+ right: 15%;
+ bottom: 20px;
+ left: 15%;
+ z-index: 10;
+ padding-top: 20px;
+ padding-bottom: 20px;
+ color: #fff;
+ text-align: center;
+}
+
+.align-baseline {
+ vertical-align: baseline !important;
+}
+
+.align-top {
+ vertical-align: top !important;
+}
+
+.align-middle {
+ vertical-align: middle !important;
+}
+
+.align-bottom {
+ vertical-align: bottom !important;
+}
+
+.align-text-bottom {
+ vertical-align: text-bottom !important;
+}
+
+.align-text-top {
+ vertical-align: text-top !important;
+}
+
+.bg-primary {
+ background-color: #007bff !important;
+}
+
+a.bg-primary:hover, a.bg-primary:focus,
+button.bg-primary:hover,
+button.bg-primary:focus {
+ background-color: #0062cc !important;
+}
+
+.bg-secondary {
+ background-color: #6c757d !important;
+}
+
+a.bg-secondary:hover, a.bg-secondary:focus,
+button.bg-secondary:hover,
+button.bg-secondary:focus {
+ background-color: #545b62 !important;
+}
+
+.bg-success {
+ background-color: #28a745 !important;
+}
+
+a.bg-success:hover, a.bg-success:focus,
+button.bg-success:hover,
+button.bg-success:focus {
+ background-color: #1e7e34 !important;
+}
+
+.bg-info {
+ background-color: #17a2b8 !important;
+}
+
+a.bg-info:hover, a.bg-info:focus,
+button.bg-info:hover,
+button.bg-info:focus {
+ background-color: #117a8b !important;
+}
+
+.bg-warning {
+ background-color: #ffc107 !important;
+}
+
+a.bg-warning:hover, a.bg-warning:focus,
+button.bg-warning:hover,
+button.bg-warning:focus {
+ background-color: #d39e00 !important;
+}
+
+.bg-danger {
+ background-color: #dc3545 !important;
+}
+
+a.bg-danger:hover, a.bg-danger:focus,
+button.bg-danger:hover,
+button.bg-danger:focus {
+ background-color: #bd2130 !important;
+}
+
+.bg-light {
+ background-color: #f8f9fa !important;
+}
+
+a.bg-light:hover, a.bg-light:focus,
+button.bg-light:hover,
+button.bg-light:focus {
+ background-color: #dae0e5 !important;
+}
+
+.bg-dark {
+ background-color: #343a40 !important;
+}
+
+a.bg-dark:hover, a.bg-dark:focus,
+button.bg-dark:hover,
+button.bg-dark:focus {
+ background-color: #1d2124 !important;
+}
+
+.bg-white {
+ background-color: #fff !important;
+}
+
+.bg-transparent {
+ background-color: transparent !important;
+}
+
+.border {
+ border: 1px solid #dee2e6 !important;
+}
+
+.border-top {
+ border-top: 1px solid #dee2e6 !important;
+}
+
+.border-right {
+ border-right: 1px solid #dee2e6 !important;
+}
+
+.border-bottom {
+ border-bottom: 1px solid #dee2e6 !important;
+}
+
+.border-left {
+ border-left: 1px solid #dee2e6 !important;
+}
+
+.border-0 {
+ border: 0 !important;
+}
+
+.border-top-0 {
+ border-top: 0 !important;
+}
+
+.border-right-0 {
+ border-right: 0 !important;
+}
+
+.border-bottom-0 {
+ border-bottom: 0 !important;
+}
+
+.border-left-0 {
+ border-left: 0 !important;
+}
+
+.border-primary {
+ border-color: #007bff !important;
+}
+
+.border-secondary {
+ border-color: #6c757d !important;
+}
+
+.border-success {
+ border-color: #28a745 !important;
+}
+
+.border-info {
+ border-color: #17a2b8 !important;
+}
+
+.border-warning {
+ border-color: #ffc107 !important;
+}
+
+.border-danger {
+ border-color: #dc3545 !important;
+}
+
+.border-light {
+ border-color: #f8f9fa !important;
+}
+
+.border-dark {
+ border-color: #343a40 !important;
+}
+
+.border-white {
+ border-color: #fff !important;
+}
+
+.rounded {
+ border-radius: 0.25rem !important;
+}
+
+.rounded-top {
+ border-top-left-radius: 0.25rem !important;
+ border-top-right-radius: 0.25rem !important;
+}
+
+.rounded-right {
+ border-top-right-radius: 0.25rem !important;
+ border-bottom-right-radius: 0.25rem !important;
+}
+
+.rounded-bottom {
+ border-bottom-right-radius: 0.25rem !important;
+ border-bottom-left-radius: 0.25rem !important;
+}
+
+.rounded-left {
+ border-top-left-radius: 0.25rem !important;
+ border-bottom-left-radius: 0.25rem !important;
+}
+
+.rounded-circle {
+ border-radius: 50% !important;
+}
+
+.rounded-0 {
+ border-radius: 0 !important;
+}
+
+.clearfix::after {
+ display: block;
+ clear: both;
+ content: "";
+}
+
+.d-none {
+ display: none !important;
+}
+
+.d-inline {
+ display: inline !important;
+}
+
+.d-inline-block {
+ display: inline-block !important;
+}
+
+.d-block {
+ display: block !important;
+}
+
+.d-table {
+ display: table !important;
+}
+
+.d-table-row {
+ display: table-row !important;
+}
+
+.d-table-cell {
+ display: table-cell !important;
+}
+
+.d-flex {
+ display: -webkit-box !important;
+ display: -ms-flexbox !important;
+ display: flex !important;
+}
+
+.d-inline-flex {
+ display: -webkit-inline-box !important;
+ display: -ms-inline-flexbox !important;
+ display: inline-flex !important;
+}
+
+@media (min-width: 576px) {
+ .d-sm-none {
+ display: none !important;
+ }
+
+ .d-sm-inline {
+ display: inline !important;
+ }
+
+ .d-sm-inline-block {
+ display: inline-block !important;
+ }
+
+ .d-sm-block {
+ display: block !important;
+ }
+
+ .d-sm-table {
+ display: table !important;
+ }
+
+ .d-sm-table-row {
+ display: table-row !important;
+ }
+
+ .d-sm-table-cell {
+ display: table-cell !important;
+ }
+
+ .d-sm-flex {
+ display: -webkit-box !important;
+ display: -ms-flexbox !important;
+ display: flex !important;
+ }
+
+ .d-sm-inline-flex {
+ display: -webkit-inline-box !important;
+ display: -ms-inline-flexbox !important;
+ display: inline-flex !important;
+ }
+}
+@media (min-width: 768px) {
+ .d-md-none {
+ display: none !important;
+ }
+
+ .d-md-inline {
+ display: inline !important;
+ }
+
+ .d-md-inline-block {
+ display: inline-block !important;
+ }
+
+ .d-md-block {
+ display: block !important;
+ }
+
+ .d-md-table {
+ display: table !important;
+ }
+
+ .d-md-table-row {
+ display: table-row !important;
+ }
+
+ .d-md-table-cell {
+ display: table-cell !important;
+ }
+
+ .d-md-flex {
+ display: -webkit-box !important;
+ display: -ms-flexbox !important;
+ display: flex !important;
+ }
+
+ .d-md-inline-flex {
+ display: -webkit-inline-box !important;
+ display: -ms-inline-flexbox !important;
+ display: inline-flex !important;
+ }
+}
+@media (min-width: 992px) {
+ .d-lg-none {
+ display: none !important;
+ }
+
+ .d-lg-inline {
+ display: inline !important;
+ }
+
+ .d-lg-inline-block {
+ display: inline-block !important;
+ }
+
+ .d-lg-block {
+ display: block !important;
+ }
+
+ .d-lg-table {
+ display: table !important;
+ }
+
+ .d-lg-table-row {
+ display: table-row !important;
+ }
+
+ .d-lg-table-cell {
+ display: table-cell !important;
+ }
+
+ .d-lg-flex {
+ display: -webkit-box !important;
+ display: -ms-flexbox !important;
+ display: flex !important;
+ }
+
+ .d-lg-inline-flex {
+ display: -webkit-inline-box !important;
+ display: -ms-inline-flexbox !important;
+ display: inline-flex !important;
+ }
+}
+@media (min-width: 1200px) {
+ .d-xl-none {
+ display: none !important;
+ }
+
+ .d-xl-inline {
+ display: inline !important;
+ }
+
+ .d-xl-inline-block {
+ display: inline-block !important;
+ }
+
+ .d-xl-block {
+ display: block !important;
+ }
+
+ .d-xl-table {
+ display: table !important;
+ }
+
+ .d-xl-table-row {
+ display: table-row !important;
+ }
+
+ .d-xl-table-cell {
+ display: table-cell !important;
+ }
+
+ .d-xl-flex {
+ display: -webkit-box !important;
+ display: -ms-flexbox !important;
+ display: flex !important;
+ }
+
+ .d-xl-inline-flex {
+ display: -webkit-inline-box !important;
+ display: -ms-inline-flexbox !important;
+ display: inline-flex !important;
+ }
+}
+@media print {
+ .d-print-none {
+ display: none !important;
+ }
+
+ .d-print-inline {
+ display: inline !important;
+ }
+
+ .d-print-inline-block {
+ display: inline-block !important;
+ }
+
+ .d-print-block {
+ display: block !important;
+ }
+
+ .d-print-table {
+ display: table !important;
+ }
+
+ .d-print-table-row {
+ display: table-row !important;
+ }
+
+ .d-print-table-cell {
+ display: table-cell !important;
+ }
+
+ .d-print-flex {
+ display: -webkit-box !important;
+ display: -ms-flexbox !important;
+ display: flex !important;
+ }
+
+ .d-print-inline-flex {
+ display: -webkit-inline-box !important;
+ display: -ms-inline-flexbox !important;
+ display: inline-flex !important;
+ }
+}
+.embed-responsive {
+ position: relative;
+ display: block;
+ width: 100%;
+ padding: 0;
+ overflow: hidden;
+}
+.embed-responsive::before {
+ display: block;
+ content: "";
+}
+.embed-responsive .embed-responsive-item,
+.embed-responsive iframe,
+.embed-responsive embed,
+.embed-responsive object,
+.embed-responsive video {
+ position: absolute;
+ top: 0;
+ bottom: 0;
+ left: 0;
+ width: 100%;
+ height: 100%;
+ border: 0;
+}
+
+.embed-responsive-21by9::before {
+ padding-top: 42.8571428571%;
+}
+
+.embed-responsive-16by9::before {
+ padding-top: 56.25%;
+}
+
+.embed-responsive-4by3::before {
+ padding-top: 75%;
+}
+
+.embed-responsive-1by1::before {
+ padding-top: 100%;
+}
+
+.flex-row {
+ -webkit-box-orient: horizontal !important;
+ -webkit-box-direction: normal !important;
+ -ms-flex-direction: row !important;
+ flex-direction: row !important;
+}
+
+.flex-column {
+ -webkit-box-orient: vertical !important;
+ -webkit-box-direction: normal !important;
+ -ms-flex-direction: column !important;
+ flex-direction: column !important;
+}
+
+.flex-row-reverse {
+ -webkit-box-orient: horizontal !important;
+ -webkit-box-direction: reverse !important;
+ -ms-flex-direction: row-reverse !important;
+ flex-direction: row-reverse !important;
+}
+
+.flex-column-reverse {
+ -webkit-box-orient: vertical !important;
+ -webkit-box-direction: reverse !important;
+ -ms-flex-direction: column-reverse !important;
+ flex-direction: column-reverse !important;
+}
+
+.flex-wrap {
+ -ms-flex-wrap: wrap !important;
+ flex-wrap: wrap !important;
+}
+
+.flex-nowrap {
+ -ms-flex-wrap: nowrap !important;
+ flex-wrap: nowrap !important;
+}
+
+.flex-wrap-reverse {
+ -ms-flex-wrap: wrap-reverse !important;
+ flex-wrap: wrap-reverse !important;
+}
+
+.justify-content-start {
+ -webkit-box-pack: start !important;
+ -ms-flex-pack: start !important;
+ justify-content: flex-start !important;
+}
+
+.justify-content-end {
+ -webkit-box-pack: end !important;
+ -ms-flex-pack: end !important;
+ justify-content: flex-end !important;
+}
+
+.justify-content-center {
+ -webkit-box-pack: center !important;
+ -ms-flex-pack: center !important;
+ justify-content: center !important;
+}
+
+.justify-content-between {
+ -webkit-box-pack: justify !important;
+ -ms-flex-pack: justify !important;
+ justify-content: space-between !important;
+}
+
+.justify-content-around {
+ -ms-flex-pack: distribute !important;
+ justify-content: space-around !important;
+}
+
+.align-items-start {
+ -webkit-box-align: start !important;
+ -ms-flex-align: start !important;
+ align-items: flex-start !important;
+}
+
+.align-items-end {
+ -webkit-box-align: end !important;
+ -ms-flex-align: end !important;
+ align-items: flex-end !important;
+}
+
+.align-items-center {
+ -webkit-box-align: center !important;
+ -ms-flex-align: center !important;
+ align-items: center !important;
+}
+
+.align-items-baseline {
+ -webkit-box-align: baseline !important;
+ -ms-flex-align: baseline !important;
+ align-items: baseline !important;
+}
+
+.align-items-stretch {
+ -webkit-box-align: stretch !important;
+ -ms-flex-align: stretch !important;
+ align-items: stretch !important;
+}
+
+.align-content-start {
+ -ms-flex-line-pack: start !important;
+ align-content: flex-start !important;
+}
+
+.align-content-end {
+ -ms-flex-line-pack: end !important;
+ align-content: flex-end !important;
+}
+
+.align-content-center {
+ -ms-flex-line-pack: center !important;
+ align-content: center !important;
+}
+
+.align-content-between {
+ -ms-flex-line-pack: justify !important;
+ align-content: space-between !important;
+}
+
+.align-content-around {
+ -ms-flex-line-pack: distribute !important;
+ align-content: space-around !important;
+}
+
+.align-content-stretch {
+ -ms-flex-line-pack: stretch !important;
+ align-content: stretch !important;
+}
+
+.align-self-auto {
+ -ms-flex-item-align: auto !important;
+ align-self: auto !important;
+}
+
+.align-self-start {
+ -ms-flex-item-align: start !important;
+ align-self: flex-start !important;
+}
+
+.align-self-end {
+ -ms-flex-item-align: end !important;
+ align-self: flex-end !important;
+}
+
+.align-self-center {
+ -ms-flex-item-align: center !important;
+ align-self: center !important;
+}
+
+.align-self-baseline {
+ -ms-flex-item-align: baseline !important;
+ align-self: baseline !important;
+}
+
+.align-self-stretch {
+ -ms-flex-item-align: stretch !important;
+ align-self: stretch !important;
+}
+
+@media (min-width: 576px) {
+ .flex-sm-row {
+ -webkit-box-orient: horizontal !important;
+ -webkit-box-direction: normal !important;
+ -ms-flex-direction: row !important;
+ flex-direction: row !important;
+ }
+
+ .flex-sm-column {
+ -webkit-box-orient: vertical !important;
+ -webkit-box-direction: normal !important;
+ -ms-flex-direction: column !important;
+ flex-direction: column !important;
+ }
+
+ .flex-sm-row-reverse {
+ -webkit-box-orient: horizontal !important;
+ -webkit-box-direction: reverse !important;
+ -ms-flex-direction: row-reverse !important;
+ flex-direction: row-reverse !important;
+ }
+
+ .flex-sm-column-reverse {
+ -webkit-box-orient: vertical !important;
+ -webkit-box-direction: reverse !important;
+ -ms-flex-direction: column-reverse !important;
+ flex-direction: column-reverse !important;
+ }
+
+ .flex-sm-wrap {
+ -ms-flex-wrap: wrap !important;
+ flex-wrap: wrap !important;
+ }
+
+ .flex-sm-nowrap {
+ -ms-flex-wrap: nowrap !important;
+ flex-wrap: nowrap !important;
+ }
+
+ .flex-sm-wrap-reverse {
+ -ms-flex-wrap: wrap-reverse !important;
+ flex-wrap: wrap-reverse !important;
+ }
+
+ .justify-content-sm-start {
+ -webkit-box-pack: start !important;
+ -ms-flex-pack: start !important;
+ justify-content: flex-start !important;
+ }
+
+ .justify-content-sm-end {
+ -webkit-box-pack: end !important;
+ -ms-flex-pack: end !important;
+ justify-content: flex-end !important;
+ }
+
+ .justify-content-sm-center {
+ -webkit-box-pack: center !important;
+ -ms-flex-pack: center !important;
+ justify-content: center !important;
+ }
+
+ .justify-content-sm-between {
+ -webkit-box-pack: justify !important;
+ -ms-flex-pack: justify !important;
+ justify-content: space-between !important;
+ }
+
+ .justify-content-sm-around {
+ -ms-flex-pack: distribute !important;
+ justify-content: space-around !important;
+ }
+
+ .align-items-sm-start {
+ -webkit-box-align: start !important;
+ -ms-flex-align: start !important;
+ align-items: flex-start !important;
+ }
+
+ .align-items-sm-end {
+ -webkit-box-align: end !important;
+ -ms-flex-align: end !important;
+ align-items: flex-end !important;
+ }
+
+ .align-items-sm-center {
+ -webkit-box-align: center !important;
+ -ms-flex-align: center !important;
+ align-items: center !important;
+ }
+
+ .align-items-sm-baseline {
+ -webkit-box-align: baseline !important;
+ -ms-flex-align: baseline !important;
+ align-items: baseline !important;
+ }
+
+ .align-items-sm-stretch {
+ -webkit-box-align: stretch !important;
+ -ms-flex-align: stretch !important;
+ align-items: stretch !important;
+ }
+
+ .align-content-sm-start {
+ -ms-flex-line-pack: start !important;
+ align-content: flex-start !important;
+ }
+
+ .align-content-sm-end {
+ -ms-flex-line-pack: end !important;
+ align-content: flex-end !important;
+ }
+
+ .align-content-sm-center {
+ -ms-flex-line-pack: center !important;
+ align-content: center !important;
+ }
+
+ .align-content-sm-between {
+ -ms-flex-line-pack: justify !important;
+ align-content: space-between !important;
+ }
+
+ .align-content-sm-around {
+ -ms-flex-line-pack: distribute !important;
+ align-content: space-around !important;
+ }
+
+ .align-content-sm-stretch {
+ -ms-flex-line-pack: stretch !important;
+ align-content: stretch !important;
+ }
+
+ .align-self-sm-auto {
+ -ms-flex-item-align: auto !important;
+ align-self: auto !important;
+ }
+
+ .align-self-sm-start {
+ -ms-flex-item-align: start !important;
+ align-self: flex-start !important;
+ }
+
+ .align-self-sm-end {
+ -ms-flex-item-align: end !important;
+ align-self: flex-end !important;
+ }
+
+ .align-self-sm-center {
+ -ms-flex-item-align: center !important;
+ align-self: center !important;
+ }
+
+ .align-self-sm-baseline {
+ -ms-flex-item-align: baseline !important;
+ align-self: baseline !important;
+ }
+
+ .align-self-sm-stretch {
+ -ms-flex-item-align: stretch !important;
+ align-self: stretch !important;
+ }
+}
+@media (min-width: 768px) {
+ .flex-md-row {
+ -webkit-box-orient: horizontal !important;
+ -webkit-box-direction: normal !important;
+ -ms-flex-direction: row !important;
+ flex-direction: row !important;
+ }
+
+ .flex-md-column {
+ -webkit-box-orient: vertical !important;
+ -webkit-box-direction: normal !important;
+ -ms-flex-direction: column !important;
+ flex-direction: column !important;
+ }
+
+ .flex-md-row-reverse {
+ -webkit-box-orient: horizontal !important;
+ -webkit-box-direction: reverse !important;
+ -ms-flex-direction: row-reverse !important;
+ flex-direction: row-reverse !important;
+ }
+
+ .flex-md-column-reverse {
+ -webkit-box-orient: vertical !important;
+ -webkit-box-direction: reverse !important;
+ -ms-flex-direction: column-reverse !important;
+ flex-direction: column-reverse !important;
+ }
+
+ .flex-md-wrap {
+ -ms-flex-wrap: wrap !important;
+ flex-wrap: wrap !important;
+ }
+
+ .flex-md-nowrap {
+ -ms-flex-wrap: nowrap !important;
+ flex-wrap: nowrap !important;
+ }
+
+ .flex-md-wrap-reverse {
+ -ms-flex-wrap: wrap-reverse !important;
+ flex-wrap: wrap-reverse !important;
+ }
+
+ .justify-content-md-start {
+ -webkit-box-pack: start !important;
+ -ms-flex-pack: start !important;
+ justify-content: flex-start !important;
+ }
+
+ .justify-content-md-end {
+ -webkit-box-pack: end !important;
+ -ms-flex-pack: end !important;
+ justify-content: flex-end !important;
+ }
+
+ .justify-content-md-center {
+ -webkit-box-pack: center !important;
+ -ms-flex-pack: center !important;
+ justify-content: center !important;
+ }
+
+ .justify-content-md-between {
+ -webkit-box-pack: justify !important;
+ -ms-flex-pack: justify !important;
+ justify-content: space-between !important;
+ }
+
+ .justify-content-md-around {
+ -ms-flex-pack: distribute !important;
+ justify-content: space-around !important;
+ }
+
+ .align-items-md-start {
+ -webkit-box-align: start !important;
+ -ms-flex-align: start !important;
+ align-items: flex-start !important;
+ }
+
+ .align-items-md-end {
+ -webkit-box-align: end !important;
+ -ms-flex-align: end !important;
+ align-items: flex-end !important;
+ }
+
+ .align-items-md-center {
+ -webkit-box-align: center !important;
+ -ms-flex-align: center !important;
+ align-items: center !important;
+ }
+
+ .align-items-md-baseline {
+ -webkit-box-align: baseline !important;
+ -ms-flex-align: baseline !important;
+ align-items: baseline !important;
+ }
+
+ .align-items-md-stretch {
+ -webkit-box-align: stretch !important;
+ -ms-flex-align: stretch !important;
+ align-items: stretch !important;
+ }
+
+ .align-content-md-start {
+ -ms-flex-line-pack: start !important;
+ align-content: flex-start !important;
+ }
+
+ .align-content-md-end {
+ -ms-flex-line-pack: end !important;
+ align-content: flex-end !important;
+ }
+
+ .align-content-md-center {
+ -ms-flex-line-pack: center !important;
+ align-content: center !important;
+ }
+
+ .align-content-md-between {
+ -ms-flex-line-pack: justify !important;
+ align-content: space-between !important;
+ }
+
+ .align-content-md-around {
+ -ms-flex-line-pack: distribute !important;
+ align-content: space-around !important;
+ }
+
+ .align-content-md-stretch {
+ -ms-flex-line-pack: stretch !important;
+ align-content: stretch !important;
+ }
+
+ .align-self-md-auto {
+ -ms-flex-item-align: auto !important;
+ align-self: auto !important;
+ }
+
+ .align-self-md-start {
+ -ms-flex-item-align: start !important;
+ align-self: flex-start !important;
+ }
+
+ .align-self-md-end {
+ -ms-flex-item-align: end !important;
+ align-self: flex-end !important;
+ }
+
+ .align-self-md-center {
+ -ms-flex-item-align: center !important;
+ align-self: center !important;
+ }
+
+ .align-self-md-baseline {
+ -ms-flex-item-align: baseline !important;
+ align-self: baseline !important;
+ }
+
+ .align-self-md-stretch {
+ -ms-flex-item-align: stretch !important;
+ align-self: stretch !important;
+ }
+}
+@media (min-width: 992px) {
+ .flex-lg-row {
+ -webkit-box-orient: horizontal !important;
+ -webkit-box-direction: normal !important;
+ -ms-flex-direction: row !important;
+ flex-direction: row !important;
+ }
+
+ .flex-lg-column {
+ -webkit-box-orient: vertical !important;
+ -webkit-box-direction: normal !important;
+ -ms-flex-direction: column !important;
+ flex-direction: column !important;
+ }
+
+ .flex-lg-row-reverse {
+ -webkit-box-orient: horizontal !important;
+ -webkit-box-direction: reverse !important;
+ -ms-flex-direction: row-reverse !important;
+ flex-direction: row-reverse !important;
+ }
+
+ .flex-lg-column-reverse {
+ -webkit-box-orient: vertical !important;
+ -webkit-box-direction: reverse !important;
+ -ms-flex-direction: column-reverse !important;
+ flex-direction: column-reverse !important;
+ }
+
+ .flex-lg-wrap {
+ -ms-flex-wrap: wrap !important;
+ flex-wrap: wrap !important;
+ }
+
+ .flex-lg-nowrap {
+ -ms-flex-wrap: nowrap !important;
+ flex-wrap: nowrap !important;
+ }
+
+ .flex-lg-wrap-reverse {
+ -ms-flex-wrap: wrap-reverse !important;
+ flex-wrap: wrap-reverse !important;
+ }
+
+ .justify-content-lg-start {
+ -webkit-box-pack: start !important;
+ -ms-flex-pack: start !important;
+ justify-content: flex-start !important;
+ }
+
+ .justify-content-lg-end {
+ -webkit-box-pack: end !important;
+ -ms-flex-pack: end !important;
+ justify-content: flex-end !important;
+ }
+
+ .justify-content-lg-center {
+ -webkit-box-pack: center !important;
+ -ms-flex-pack: center !important;
+ justify-content: center !important;
+ }
+
+ .justify-content-lg-between {
+ -webkit-box-pack: justify !important;
+ -ms-flex-pack: justify !important;
+ justify-content: space-between !important;
+ }
+
+ .justify-content-lg-around {
+ -ms-flex-pack: distribute !important;
+ justify-content: space-around !important;
+ }
+
+ .align-items-lg-start {
+ -webkit-box-align: start !important;
+ -ms-flex-align: start !important;
+ align-items: flex-start !important;
+ }
+
+ .align-items-lg-end {
+ -webkit-box-align: end !important;
+ -ms-flex-align: end !important;
+ align-items: flex-end !important;
+ }
+
+ .align-items-lg-center {
+ -webkit-box-align: center !important;
+ -ms-flex-align: center !important;
+ align-items: center !important;
+ }
+
+ .align-items-lg-baseline {
+ -webkit-box-align: baseline !important;
+ -ms-flex-align: baseline !important;
+ align-items: baseline !important;
+ }
+
+ .align-items-lg-stretch {
+ -webkit-box-align: stretch !important;
+ -ms-flex-align: stretch !important;
+ align-items: stretch !important;
+ }
+
+ .align-content-lg-start {
+ -ms-flex-line-pack: start !important;
+ align-content: flex-start !important;
+ }
+
+ .align-content-lg-end {
+ -ms-flex-line-pack: end !important;
+ align-content: flex-end !important;
+ }
+
+ .align-content-lg-center {
+ -ms-flex-line-pack: center !important;
+ align-content: center !important;
+ }
+
+ .align-content-lg-between {
+ -ms-flex-line-pack: justify !important;
+ align-content: space-between !important;
+ }
+
+ .align-content-lg-around {
+ -ms-flex-line-pack: distribute !important;
+ align-content: space-around !important;
+ }
+
+ .align-content-lg-stretch {
+ -ms-flex-line-pack: stretch !important;
+ align-content: stretch !important;
+ }
+
+ .align-self-lg-auto {
+ -ms-flex-item-align: auto !important;
+ align-self: auto !important;
+ }
+
+ .align-self-lg-start {
+ -ms-flex-item-align: start !important;
+ align-self: flex-start !important;
+ }
+
+ .align-self-lg-end {
+ -ms-flex-item-align: end !important;
+ align-self: flex-end !important;
+ }
+
+ .align-self-lg-center {
+ -ms-flex-item-align: center !important;
+ align-self: center !important;
+ }
+
+ .align-self-lg-baseline {
+ -ms-flex-item-align: baseline !important;
+ align-self: baseline !important;
+ }
+
+ .align-self-lg-stretch {
+ -ms-flex-item-align: stretch !important;
+ align-self: stretch !important;
+ }
+}
+@media (min-width: 1200px) {
+ .flex-xl-row {
+ -webkit-box-orient: horizontal !important;
+ -webkit-box-direction: normal !important;
+ -ms-flex-direction: row !important;
+ flex-direction: row !important;
+ }
+
+ .flex-xl-column {
+ -webkit-box-orient: vertical !important;
+ -webkit-box-direction: normal !important;
+ -ms-flex-direction: column !important;
+ flex-direction: column !important;
+ }
+
+ .flex-xl-row-reverse {
+ -webkit-box-orient: horizontal !important;
+ -webkit-box-direction: reverse !important;
+ -ms-flex-direction: row-reverse !important;
+ flex-direction: row-reverse !important;
+ }
+
+ .flex-xl-column-reverse {
+ -webkit-box-orient: vertical !important;
+ -webkit-box-direction: reverse !important;
+ -ms-flex-direction: column-reverse !important;
+ flex-direction: column-reverse !important;
+ }
+
+ .flex-xl-wrap {
+ -ms-flex-wrap: wrap !important;
+ flex-wrap: wrap !important;
+ }
+
+ .flex-xl-nowrap {
+ -ms-flex-wrap: nowrap !important;
+ flex-wrap: nowrap !important;
+ }
+
+ .flex-xl-wrap-reverse {
+ -ms-flex-wrap: wrap-reverse !important;
+ flex-wrap: wrap-reverse !important;
+ }
+
+ .justify-content-xl-start {
+ -webkit-box-pack: start !important;
+ -ms-flex-pack: start !important;
+ justify-content: flex-start !important;
+ }
+
+ .justify-content-xl-end {
+ -webkit-box-pack: end !important;
+ -ms-flex-pack: end !important;
+ justify-content: flex-end !important;
+ }
+
+ .justify-content-xl-center {
+ -webkit-box-pack: center !important;
+ -ms-flex-pack: center !important;
+ justify-content: center !important;
+ }
+
+ .justify-content-xl-between {
+ -webkit-box-pack: justify !important;
+ -ms-flex-pack: justify !important;
+ justify-content: space-between !important;
+ }
+
+ .justify-content-xl-around {
+ -ms-flex-pack: distribute !important;
+ justify-content: space-around !important;
+ }
+
+ .align-items-xl-start {
+ -webkit-box-align: start !important;
+ -ms-flex-align: start !important;
+ align-items: flex-start !important;
+ }
+
+ .align-items-xl-end {
+ -webkit-box-align: end !important;
+ -ms-flex-align: end !important;
+ align-items: flex-end !important;
+ }
+
+ .align-items-xl-center {
+ -webkit-box-align: center !important;
+ -ms-flex-align: center !important;
+ align-items: center !important;
+ }
+
+ .align-items-xl-baseline {
+ -webkit-box-align: baseline !important;
+ -ms-flex-align: baseline !important;
+ align-items: baseline !important;
+ }
+
+ .align-items-xl-stretch {
+ -webkit-box-align: stretch !important;
+ -ms-flex-align: stretch !important;
+ align-items: stretch !important;
+ }
+
+ .align-content-xl-start {
+ -ms-flex-line-pack: start !important;
+ align-content: flex-start !important;
+ }
+
+ .align-content-xl-end {
+ -ms-flex-line-pack: end !important;
+ align-content: flex-end !important;
+ }
+
+ .align-content-xl-center {
+ -ms-flex-line-pack: center !important;
+ align-content: center !important;
+ }
+
+ .align-content-xl-between {
+ -ms-flex-line-pack: justify !important;
+ align-content: space-between !important;
+ }
+
+ .align-content-xl-around {
+ -ms-flex-line-pack: distribute !important;
+ align-content: space-around !important;
+ }
+
+ .align-content-xl-stretch {
+ -ms-flex-line-pack: stretch !important;
+ align-content: stretch !important;
+ }
+
+ .align-self-xl-auto {
+ -ms-flex-item-align: auto !important;
+ align-self: auto !important;
+ }
+
+ .align-self-xl-start {
+ -ms-flex-item-align: start !important;
+ align-self: flex-start !important;
+ }
+
+ .align-self-xl-end {
+ -ms-flex-item-align: end !important;
+ align-self: flex-end !important;
+ }
+
+ .align-self-xl-center {
+ -ms-flex-item-align: center !important;
+ align-self: center !important;
+ }
+
+ .align-self-xl-baseline {
+ -ms-flex-item-align: baseline !important;
+ align-self: baseline !important;
+ }
+
+ .align-self-xl-stretch {
+ -ms-flex-item-align: stretch !important;
+ align-self: stretch !important;
+ }
+}
+.float-left {
+ float: left !important;
+}
+
+.float-right {
+ float: right !important;
+}
+
+.float-none {
+ float: none !important;
+}
+
+@media (min-width: 576px) {
+ .float-sm-left {
+ float: left !important;
+ }
+
+ .float-sm-right {
+ float: right !important;
+ }
+
+ .float-sm-none {
+ float: none !important;
+ }
+}
+@media (min-width: 768px) {
+ .float-md-left {
+ float: left !important;
+ }
+
+ .float-md-right {
+ float: right !important;
+ }
+
+ .float-md-none {
+ float: none !important;
+ }
+}
+@media (min-width: 992px) {
+ .float-lg-left {
+ float: left !important;
+ }
+
+ .float-lg-right {
+ float: right !important;
+ }
+
+ .float-lg-none {
+ float: none !important;
+ }
+}
+@media (min-width: 1200px) {
+ .float-xl-left {
+ float: left !important;
+ }
+
+ .float-xl-right {
+ float: right !important;
+ }
+
+ .float-xl-none {
+ float: none !important;
+ }
+}
+.position-static {
+ position: static !important;
+}
+
+.position-relative {
+ position: relative !important;
+}
+
+.position-absolute {
+ position: absolute !important;
+}
+
+.position-fixed {
+ position: fixed !important;
+}
+
+.position-sticky {
+ position: sticky !important;
+}
+
+.fixed-top {
+ position: fixed;
+ top: 0;
+ right: 0;
+ left: 0;
+ z-index: 1030;
+}
+
+.fixed-bottom {
+ position: fixed;
+ right: 0;
+ bottom: 0;
+ left: 0;
+ z-index: 1030;
+}
+
+@supports (position: sticky) {
+ .sticky-top {
+ position: sticky;
+ top: 0;
+ z-index: 1020;
+ }
+}
+
+.sr-only {
+ position: absolute;
+ width: 1px;
+ height: 1px;
+ padding: 0;
+ overflow: hidden;
+ clip: rect(0, 0, 0, 0);
+ white-space: nowrap;
+ -webkit-clip-path: inset(50%);
+ clip-path: inset(50%);
+ border: 0;
+}
+
+.sr-only-focusable:active, .sr-only-focusable:focus {
+ position: static;
+ width: auto;
+ height: auto;
+ overflow: visible;
+ clip: auto;
+ white-space: normal;
+ -webkit-clip-path: none;
+ clip-path: none;
+}
+
+.w-25 {
+ width: 25% !important;
+}
+
+.w-50 {
+ width: 50% !important;
+}
+
+.w-75 {
+ width: 75% !important;
+}
+
+.w-100 {
+ width: 100% !important;
+}
+
+.h-25 {
+ height: 25% !important;
+}
+
+.h-50 {
+ height: 50% !important;
+}
+
+.h-75 {
+ height: 75% !important;
+}
+
+.h-100 {
+ height: 100% !important;
+}
+
+.mw-100 {
+ max-width: 100% !important;
+}
+
+.mh-100 {
+ max-height: 100% !important;
+}
+
+.m-0 {
+ margin: 0 !important;
+}
+
+.mt-0,
+.my-0 {
+ margin-top: 0 !important;
+}
+
+.mr-0,
+.mx-0 {
+ margin-right: 0 !important;
+}
+
+.mb-0,
+.my-0 {
+ margin-bottom: 0 !important;
+}
+
+.ml-0,
+.mx-0 {
+ margin-left: 0 !important;
+}
+
+.m-1 {
+ margin: 0.25rem !important;
+}
+
+.mt-1,
+.my-1 {
+ margin-top: 0.25rem !important;
+}
+
+.mr-1,
+.mx-1 {
+ margin-right: 0.25rem !important;
+}
+
+.mb-1,
+.my-1 {
+ margin-bottom: 0.25rem !important;
+}
+
+.ml-1,
+.mx-1 {
+ margin-left: 0.25rem !important;
+}
+
+.m-2 {
+ margin: 0.5rem !important;
+}
+
+.mt-2,
+.my-2 {
+ margin-top: 0.5rem !important;
+}
+
+.mr-2,
+.mx-2 {
+ margin-right: 0.5rem !important;
+}
+
+.mb-2,
+.my-2 {
+ margin-bottom: 0.5rem !important;
+}
+
+.ml-2,
+.mx-2 {
+ margin-left: 0.5rem !important;
+}
+
+.m-3 {
+ margin: 1rem !important;
+}
+
+.mt-3,
+.my-3 {
+ margin-top: 1rem !important;
+}
+
+.mr-3,
+.mx-3 {
+ margin-right: 1rem !important;
+}
+
+.mb-3,
+.my-3 {
+ margin-bottom: 1rem !important;
+}
+
+.ml-3,
+.mx-3 {
+ margin-left: 1rem !important;
+}
+
+.m-4 {
+ margin: 1.5rem !important;
+}
+
+.mt-4,
+.my-4 {
+ margin-top: 1.5rem !important;
+}
+
+.mr-4,
+.mx-4 {
+ margin-right: 1.5rem !important;
+}
+
+.mb-4,
+.my-4 {
+ margin-bottom: 1.5rem !important;
+}
+
+.ml-4,
+.mx-4 {
+ margin-left: 1.5rem !important;
+}
+
+.m-5 {
+ margin: 3rem !important;
+}
+
+.mt-5,
+.my-5 {
+ margin-top: 3rem !important;
+}
+
+.mr-5,
+.mx-5 {
+ margin-right: 3rem !important;
+}
+
+.mb-5,
+.my-5 {
+ margin-bottom: 3rem !important;
+}
+
+.ml-5,
+.mx-5 {
+ margin-left: 3rem !important;
+}
+
+.p-0 {
+ padding: 0 !important;
+}
+
+.pt-0,
+.py-0 {
+ padding-top: 0 !important;
+}
+
+.pr-0,
+.px-0 {
+ padding-right: 0 !important;
+}
+
+.pb-0,
+.py-0 {
+ padding-bottom: 0 !important;
+}
+
+.pl-0,
+.px-0 {
+ padding-left: 0 !important;
+}
+
+.p-1 {
+ padding: 0.25rem !important;
+}
+
+.pt-1,
+.py-1 {
+ padding-top: 0.25rem !important;
+}
+
+.pr-1,
+.px-1 {
+ padding-right: 0.25rem !important;
+}
+
+.pb-1,
+.py-1 {
+ padding-bottom: 0.25rem !important;
+}
+
+.pl-1,
+.px-1 {
+ padding-left: 0.25rem !important;
+}
+
+.p-2 {
+ padding: 0.5rem !important;
+}
+
+.pt-2,
+.py-2 {
+ padding-top: 0.5rem !important;
+}
+
+.pr-2,
+.px-2 {
+ padding-right: 0.5rem !important;
+}
+
+.pb-2,
+.py-2 {
+ padding-bottom: 0.5rem !important;
+}
+
+.pl-2,
+.px-2 {
+ padding-left: 0.5rem !important;
+}
+
+.p-3 {
+ padding: 1rem !important;
+}
+
+.pt-3,
+.py-3 {
+ padding-top: 1rem !important;
+}
+
+.pr-3,
+.px-3 {
+ padding-right: 1rem !important;
+}
+
+.pb-3,
+.py-3 {
+ padding-bottom: 1rem !important;
+}
+
+.pl-3,
+.px-3 {
+ padding-left: 1rem !important;
+}
+
+.p-4 {
+ padding: 1.5rem !important;
+}
+
+.pt-4,
+.py-4 {
+ padding-top: 1.5rem !important;
+}
+
+.pr-4,
+.px-4 {
+ padding-right: 1.5rem !important;
+}
+
+.pb-4,
+.py-4 {
+ padding-bottom: 1.5rem !important;
+}
+
+.pl-4,
+.px-4 {
+ padding-left: 1.5rem !important;
+}
+
+.p-5 {
+ padding: 3rem !important;
+}
+
+.pt-5,
+.py-5 {
+ padding-top: 3rem !important;
+}
+
+.pr-5,
+.px-5 {
+ padding-right: 3rem !important;
+}
+
+.pb-5,
+.py-5 {
+ padding-bottom: 3rem !important;
+}
+
+.pl-5,
+.px-5 {
+ padding-left: 3rem !important;
+}
+
+.m-auto {
+ margin: auto !important;
+}
+
+.mt-auto,
+.my-auto {
+ margin-top: auto !important;
+}
+
+.mr-auto,
+.mx-auto {
+ margin-right: auto !important;
+}
+
+.mb-auto,
+.my-auto {
+ margin-bottom: auto !important;
+}
+
+.ml-auto,
+.mx-auto {
+ margin-left: auto !important;
+}
+
+@media (min-width: 576px) {
+ .m-sm-0 {
+ margin: 0 !important;
+ }
+
+ .mt-sm-0,
+ .my-sm-0 {
+ margin-top: 0 !important;
+ }
+
+ .mr-sm-0,
+ .mx-sm-0 {
+ margin-right: 0 !important;
+ }
+
+ .mb-sm-0,
+ .my-sm-0 {
+ margin-bottom: 0 !important;
+ }
+
+ .ml-sm-0,
+ .mx-sm-0 {
+ margin-left: 0 !important;
+ }
+
+ .m-sm-1 {
+ margin: 0.25rem !important;
+ }
+
+ .mt-sm-1,
+ .my-sm-1 {
+ margin-top: 0.25rem !important;
+ }
+
+ .mr-sm-1,
+ .mx-sm-1 {
+ margin-right: 0.25rem !important;
+ }
+
+ .mb-sm-1,
+ .my-sm-1 {
+ margin-bottom: 0.25rem !important;
+ }
+
+ .ml-sm-1,
+ .mx-sm-1 {
+ margin-left: 0.25rem !important;
+ }
+
+ .m-sm-2 {
+ margin: 0.5rem !important;
+ }
+
+ .mt-sm-2,
+ .my-sm-2 {
+ margin-top: 0.5rem !important;
+ }
+
+ .mr-sm-2,
+ .mx-sm-2 {
+ margin-right: 0.5rem !important;
+ }
+
+ .mb-sm-2,
+ .my-sm-2 {
+ margin-bottom: 0.5rem !important;
+ }
+
+ .ml-sm-2,
+ .mx-sm-2 {
+ margin-left: 0.5rem !important;
+ }
+
+ .m-sm-3 {
+ margin: 1rem !important;
+ }
+
+ .mt-sm-3,
+ .my-sm-3 {
+ margin-top: 1rem !important;
+ }
+
+ .mr-sm-3,
+ .mx-sm-3 {
+ margin-right: 1rem !important;
+ }
+
+ .mb-sm-3,
+ .my-sm-3 {
+ margin-bottom: 1rem !important;
+ }
+
+ .ml-sm-3,
+ .mx-sm-3 {
+ margin-left: 1rem !important;
+ }
+
+ .m-sm-4 {
+ margin: 1.5rem !important;
+ }
+
+ .mt-sm-4,
+ .my-sm-4 {
+ margin-top: 1.5rem !important;
+ }
+
+ .mr-sm-4,
+ .mx-sm-4 {
+ margin-right: 1.5rem !important;
+ }
+
+ .mb-sm-4,
+ .my-sm-4 {
+ margin-bottom: 1.5rem !important;
+ }
+
+ .ml-sm-4,
+ .mx-sm-4 {
+ margin-left: 1.5rem !important;
+ }
+
+ .m-sm-5 {
+ margin: 3rem !important;
+ }
+
+ .mt-sm-5,
+ .my-sm-5 {
+ margin-top: 3rem !important;
+ }
+
+ .mr-sm-5,
+ .mx-sm-5 {
+ margin-right: 3rem !important;
+ }
+
+ .mb-sm-5,
+ .my-sm-5 {
+ margin-bottom: 3rem !important;
+ }
+
+ .ml-sm-5,
+ .mx-sm-5 {
+ margin-left: 3rem !important;
+ }
+
+ .p-sm-0 {
+ padding: 0 !important;
+ }
+
+ .pt-sm-0,
+ .py-sm-0 {
+ padding-top: 0 !important;
+ }
+
+ .pr-sm-0,
+ .px-sm-0 {
+ padding-right: 0 !important;
+ }
+
+ .pb-sm-0,
+ .py-sm-0 {
+ padding-bottom: 0 !important;
+ }
+
+ .pl-sm-0,
+ .px-sm-0 {
+ padding-left: 0 !important;
+ }
+
+ .p-sm-1 {
+ padding: 0.25rem !important;
+ }
+
+ .pt-sm-1,
+ .py-sm-1 {
+ padding-top: 0.25rem !important;
+ }
+
+ .pr-sm-1,
+ .px-sm-1 {
+ padding-right: 0.25rem !important;
+ }
+
+ .pb-sm-1,
+ .py-sm-1 {
+ padding-bottom: 0.25rem !important;
+ }
+
+ .pl-sm-1,
+ .px-sm-1 {
+ padding-left: 0.25rem !important;
+ }
+
+ .p-sm-2 {
+ padding: 0.5rem !important;
+ }
+
+ .pt-sm-2,
+ .py-sm-2 {
+ padding-top: 0.5rem !important;
+ }
+
+ .pr-sm-2,
+ .px-sm-2 {
+ padding-right: 0.5rem !important;
+ }
+
+ .pb-sm-2,
+ .py-sm-2 {
+ padding-bottom: 0.5rem !important;
+ }
+
+ .pl-sm-2,
+ .px-sm-2 {
+ padding-left: 0.5rem !important;
+ }
+
+ .p-sm-3 {
+ padding: 1rem !important;
+ }
+
+ .pt-sm-3,
+ .py-sm-3 {
+ padding-top: 1rem !important;
+ }
+
+ .pr-sm-3,
+ .px-sm-3 {
+ padding-right: 1rem !important;
+ }
+
+ .pb-sm-3,
+ .py-sm-3 {
+ padding-bottom: 1rem !important;
+ }
+
+ .pl-sm-3,
+ .px-sm-3 {
+ padding-left: 1rem !important;
+ }
+
+ .p-sm-4 {
+ padding: 1.5rem !important;
+ }
+
+ .pt-sm-4,
+ .py-sm-4 {
+ padding-top: 1.5rem !important;
+ }
+
+ .pr-sm-4,
+ .px-sm-4 {
+ padding-right: 1.5rem !important;
+ }
+
+ .pb-sm-4,
+ .py-sm-4 {
+ padding-bottom: 1.5rem !important;
+ }
+
+ .pl-sm-4,
+ .px-sm-4 {
+ padding-left: 1.5rem !important;
+ }
+
+ .p-sm-5 {
+ padding: 3rem !important;
+ }
+
+ .pt-sm-5,
+ .py-sm-5 {
+ padding-top: 3rem !important;
+ }
+
+ .pr-sm-5,
+ .px-sm-5 {
+ padding-right: 3rem !important;
+ }
+
+ .pb-sm-5,
+ .py-sm-5 {
+ padding-bottom: 3rem !important;
+ }
+
+ .pl-sm-5,
+ .px-sm-5 {
+ padding-left: 3rem !important;
+ }
+
+ .m-sm-auto {
+ margin: auto !important;
+ }
+
+ .mt-sm-auto,
+ .my-sm-auto {
+ margin-top: auto !important;
+ }
+
+ .mr-sm-auto,
+ .mx-sm-auto {
+ margin-right: auto !important;
+ }
+
+ .mb-sm-auto,
+ .my-sm-auto {
+ margin-bottom: auto !important;
+ }
+
+ .ml-sm-auto,
+ .mx-sm-auto {
+ margin-left: auto !important;
+ }
+}
+@media (min-width: 768px) {
+ .m-md-0 {
+ margin: 0 !important;
+ }
+
+ .mt-md-0,
+ .my-md-0 {
+ margin-top: 0 !important;
+ }
+
+ .mr-md-0,
+ .mx-md-0 {
+ margin-right: 0 !important;
+ }
+
+ .mb-md-0,
+ .my-md-0 {
+ margin-bottom: 0 !important;
+ }
+
+ .ml-md-0,
+ .mx-md-0 {
+ margin-left: 0 !important;
+ }
+
+ .m-md-1 {
+ margin: 0.25rem !important;
+ }
+
+ .mt-md-1,
+ .my-md-1 {
+ margin-top: 0.25rem !important;
+ }
+
+ .mr-md-1,
+ .mx-md-1 {
+ margin-right: 0.25rem !important;
+ }
+
+ .mb-md-1,
+ .my-md-1 {
+ margin-bottom: 0.25rem !important;
+ }
+
+ .ml-md-1,
+ .mx-md-1 {
+ margin-left: 0.25rem !important;
+ }
+
+ .m-md-2 {
+ margin: 0.5rem !important;
+ }
+
+ .mt-md-2,
+ .my-md-2 {
+ margin-top: 0.5rem !important;
+ }
+
+ .mr-md-2,
+ .mx-md-2 {
+ margin-right: 0.5rem !important;
+ }
+
+ .mb-md-2,
+ .my-md-2 {
+ margin-bottom: 0.5rem !important;
+ }
+
+ .ml-md-2,
+ .mx-md-2 {
+ margin-left: 0.5rem !important;
+ }
+
+ .m-md-3 {
+ margin: 1rem !important;
+ }
+
+ .mt-md-3,
+ .my-md-3 {
+ margin-top: 1rem !important;
+ }
+
+ .mr-md-3,
+ .mx-md-3 {
+ margin-right: 1rem !important;
+ }
+
+ .mb-md-3,
+ .my-md-3 {
+ margin-bottom: 1rem !important;
+ }
+
+ .ml-md-3,
+ .mx-md-3 {
+ margin-left: 1rem !important;
+ }
+
+ .m-md-4 {
+ margin: 1.5rem !important;
+ }
+
+ .mt-md-4,
+ .my-md-4 {
+ margin-top: 1.5rem !important;
+ }
+
+ .mr-md-4,
+ .mx-md-4 {
+ margin-right: 1.5rem !important;
+ }
+
+ .mb-md-4,
+ .my-md-4 {
+ margin-bottom: 1.5rem !important;
+ }
+
+ .ml-md-4,
+ .mx-md-4 {
+ margin-left: 1.5rem !important;
+ }
+
+ .m-md-5 {
+ margin: 3rem !important;
+ }
+
+ .mt-md-5,
+ .my-md-5 {
+ margin-top: 3rem !important;
+ }
+
+ .mr-md-5,
+ .mx-md-5 {
+ margin-right: 3rem !important;
+ }
+
+ .mb-md-5,
+ .my-md-5 {
+ margin-bottom: 3rem !important;
+ }
+
+ .ml-md-5,
+ .mx-md-5 {
+ margin-left: 3rem !important;
+ }
+
+ .p-md-0 {
+ padding: 0 !important;
+ }
+
+ .pt-md-0,
+ .py-md-0 {
+ padding-top: 0 !important;
+ }
+
+ .pr-md-0,
+ .px-md-0 {
+ padding-right: 0 !important;
+ }
+
+ .pb-md-0,
+ .py-md-0 {
+ padding-bottom: 0 !important;
+ }
+
+ .pl-md-0,
+ .px-md-0 {
+ padding-left: 0 !important;
+ }
+
+ .p-md-1 {
+ padding: 0.25rem !important;
+ }
+
+ .pt-md-1,
+ .py-md-1 {
+ padding-top: 0.25rem !important;
+ }
+
+ .pr-md-1,
+ .px-md-1 {
+ padding-right: 0.25rem !important;
+ }
+
+ .pb-md-1,
+ .py-md-1 {
+ padding-bottom: 0.25rem !important;
+ }
+
+ .pl-md-1,
+ .px-md-1 {
+ padding-left: 0.25rem !important;
+ }
+
+ .p-md-2 {
+ padding: 0.5rem !important;
+ }
+
+ .pt-md-2,
+ .py-md-2 {
+ padding-top: 0.5rem !important;
+ }
+
+ .pr-md-2,
+ .px-md-2 {
+ padding-right: 0.5rem !important;
+ }
+
+ .pb-md-2,
+ .py-md-2 {
+ padding-bottom: 0.5rem !important;
+ }
+
+ .pl-md-2,
+ .px-md-2 {
+ padding-left: 0.5rem !important;
+ }
+
+ .p-md-3 {
+ padding: 1rem !important;
+ }
+
+ .pt-md-3,
+ .py-md-3 {
+ padding-top: 1rem !important;
+ }
+
+ .pr-md-3,
+ .px-md-3 {
+ padding-right: 1rem !important;
+ }
+
+ .pb-md-3,
+ .py-md-3 {
+ padding-bottom: 1rem !important;
+ }
+
+ .pl-md-3,
+ .px-md-3 {
+ padding-left: 1rem !important;
+ }
+
+ .p-md-4 {
+ padding: 1.5rem !important;
+ }
+
+ .pt-md-4,
+ .py-md-4 {
+ padding-top: 1.5rem !important;
+ }
+
+ .pr-md-4,
+ .px-md-4 {
+ padding-right: 1.5rem !important;
+ }
+
+ .pb-md-4,
+ .py-md-4 {
+ padding-bottom: 1.5rem !important;
+ }
+
+ .pl-md-4,
+ .px-md-4 {
+ padding-left: 1.5rem !important;
+ }
+
+ .p-md-5 {
+ padding: 3rem !important;
+ }
+
+ .pt-md-5,
+ .py-md-5 {
+ padding-top: 3rem !important;
+ }
+
+ .pr-md-5,
+ .px-md-5 {
+ padding-right: 3rem !important;
+ }
+
+ .pb-md-5,
+ .py-md-5 {
+ padding-bottom: 3rem !important;
+ }
+
+ .pl-md-5,
+ .px-md-5 {
+ padding-left: 3rem !important;
+ }
+
+ .m-md-auto {
+ margin: auto !important;
+ }
+
+ .mt-md-auto,
+ .my-md-auto {
+ margin-top: auto !important;
+ }
+
+ .mr-md-auto,
+ .mx-md-auto {
+ margin-right: auto !important;
+ }
+
+ .mb-md-auto,
+ .my-md-auto {
+ margin-bottom: auto !important;
+ }
+
+ .ml-md-auto,
+ .mx-md-auto {
+ margin-left: auto !important;
+ }
+}
+@media (min-width: 992px) {
+ .m-lg-0 {
+ margin: 0 !important;
+ }
+
+ .mt-lg-0,
+ .my-lg-0 {
+ margin-top: 0 !important;
+ }
+
+ .mr-lg-0,
+ .mx-lg-0 {
+ margin-right: 0 !important;
+ }
+
+ .mb-lg-0,
+ .my-lg-0 {
+ margin-bottom: 0 !important;
+ }
+
+ .ml-lg-0,
+ .mx-lg-0 {
+ margin-left: 0 !important;
+ }
+
+ .m-lg-1 {
+ margin: 0.25rem !important;
+ }
+
+ .mt-lg-1,
+ .my-lg-1 {
+ margin-top: 0.25rem !important;
+ }
+
+ .mr-lg-1,
+ .mx-lg-1 {
+ margin-right: 0.25rem !important;
+ }
+
+ .mb-lg-1,
+ .my-lg-1 {
+ margin-bottom: 0.25rem !important;
+ }
+
+ .ml-lg-1,
+ .mx-lg-1 {
+ margin-left: 0.25rem !important;
+ }
+
+ .m-lg-2 {
+ margin: 0.5rem !important;
+ }
+
+ .mt-lg-2,
+ .my-lg-2 {
+ margin-top: 0.5rem !important;
+ }
+
+ .mr-lg-2,
+ .mx-lg-2 {
+ margin-right: 0.5rem !important;
+ }
+
+ .mb-lg-2,
+ .my-lg-2 {
+ margin-bottom: 0.5rem !important;
+ }
+
+ .ml-lg-2,
+ .mx-lg-2 {
+ margin-left: 0.5rem !important;
+ }
+
+ .m-lg-3 {
+ margin: 1rem !important;
+ }
+
+ .mt-lg-3,
+ .my-lg-3 {
+ margin-top: 1rem !important;
+ }
+
+ .mr-lg-3,
+ .mx-lg-3 {
+ margin-right: 1rem !important;
+ }
+
+ .mb-lg-3,
+ .my-lg-3 {
+ margin-bottom: 1rem !important;
+ }
+
+ .ml-lg-3,
+ .mx-lg-3 {
+ margin-left: 1rem !important;
+ }
+
+ .m-lg-4 {
+ margin: 1.5rem !important;
+ }
+
+ .mt-lg-4,
+ .my-lg-4 {
+ margin-top: 1.5rem !important;
+ }
+
+ .mr-lg-4,
+ .mx-lg-4 {
+ margin-right: 1.5rem !important;
+ }
+
+ .mb-lg-4,
+ .my-lg-4 {
+ margin-bottom: 1.5rem !important;
+ }
+
+ .ml-lg-4,
+ .mx-lg-4 {
+ margin-left: 1.5rem !important;
+ }
+
+ .m-lg-5 {
+ margin: 3rem !important;
+ }
+
+ .mt-lg-5,
+ .my-lg-5 {
+ margin-top: 3rem !important;
+ }
+
+ .mr-lg-5,
+ .mx-lg-5 {
+ margin-right: 3rem !important;
+ }
+
+ .mb-lg-5,
+ .my-lg-5 {
+ margin-bottom: 3rem !important;
+ }
+
+ .ml-lg-5,
+ .mx-lg-5 {
+ margin-left: 3rem !important;
+ }
+
+ .p-lg-0 {
+ padding: 0 !important;
+ }
+
+ .pt-lg-0,
+ .py-lg-0 {
+ padding-top: 0 !important;
+ }
+
+ .pr-lg-0,
+ .px-lg-0 {
+ padding-right: 0 !important;
+ }
+
+ .pb-lg-0,
+ .py-lg-0 {
+ padding-bottom: 0 !important;
+ }
+
+ .pl-lg-0,
+ .px-lg-0 {
+ padding-left: 0 !important;
+ }
+
+ .p-lg-1 {
+ padding: 0.25rem !important;
+ }
+
+ .pt-lg-1,
+ .py-lg-1 {
+ padding-top: 0.25rem !important;
+ }
+
+ .pr-lg-1,
+ .px-lg-1 {
+ padding-right: 0.25rem !important;
+ }
+
+ .pb-lg-1,
+ .py-lg-1 {
+ padding-bottom: 0.25rem !important;
+ }
+
+ .pl-lg-1,
+ .px-lg-1 {
+ padding-left: 0.25rem !important;
+ }
+
+ .p-lg-2 {
+ padding: 0.5rem !important;
+ }
+
+ .pt-lg-2,
+ .py-lg-2 {
+ padding-top: 0.5rem !important;
+ }
+
+ .pr-lg-2,
+ .px-lg-2 {
+ padding-right: 0.5rem !important;
+ }
+
+ .pb-lg-2,
+ .py-lg-2 {
+ padding-bottom: 0.5rem !important;
+ }
+
+ .pl-lg-2,
+ .px-lg-2 {
+ padding-left: 0.5rem !important;
+ }
+
+ .p-lg-3 {
+ padding: 1rem !important;
+ }
+
+ .pt-lg-3,
+ .py-lg-3 {
+ padding-top: 1rem !important;
+ }
+
+ .pr-lg-3,
+ .px-lg-3 {
+ padding-right: 1rem !important;
+ }
+
+ .pb-lg-3,
+ .py-lg-3 {
+ padding-bottom: 1rem !important;
+ }
+
+ .pl-lg-3,
+ .px-lg-3 {
+ padding-left: 1rem !important;
+ }
+
+ .p-lg-4 {
+ padding: 1.5rem !important;
+ }
+
+ .pt-lg-4,
+ .py-lg-4 {
+ padding-top: 1.5rem !important;
+ }
+
+ .pr-lg-4,
+ .px-lg-4 {
+ padding-right: 1.5rem !important;
+ }
+
+ .pb-lg-4,
+ .py-lg-4 {
+ padding-bottom: 1.5rem !important;
+ }
+
+ .pl-lg-4,
+ .px-lg-4 {
+ padding-left: 1.5rem !important;
+ }
+
+ .p-lg-5 {
+ padding: 3rem !important;
+ }
+
+ .pt-lg-5,
+ .py-lg-5 {
+ padding-top: 3rem !important;
+ }
+
+ .pr-lg-5,
+ .px-lg-5 {
+ padding-right: 3rem !important;
+ }
+
+ .pb-lg-5,
+ .py-lg-5 {
+ padding-bottom: 3rem !important;
+ }
+
+ .pl-lg-5,
+ .px-lg-5 {
+ padding-left: 3rem !important;
+ }
+
+ .m-lg-auto {
+ margin: auto !important;
+ }
+
+ .mt-lg-auto,
+ .my-lg-auto {
+ margin-top: auto !important;
+ }
+
+ .mr-lg-auto,
+ .mx-lg-auto {
+ margin-right: auto !important;
+ }
+
+ .mb-lg-auto,
+ .my-lg-auto {
+ margin-bottom: auto !important;
+ }
+
+ .ml-lg-auto,
+ .mx-lg-auto {
+ margin-left: auto !important;
+ }
+}
+@media (min-width: 1200px) {
+ .m-xl-0 {
+ margin: 0 !important;
+ }
+
+ .mt-xl-0,
+ .my-xl-0 {
+ margin-top: 0 !important;
+ }
+
+ .mr-xl-0,
+ .mx-xl-0 {
+ margin-right: 0 !important;
+ }
+
+ .mb-xl-0,
+ .my-xl-0 {
+ margin-bottom: 0 !important;
+ }
+
+ .ml-xl-0,
+ .mx-xl-0 {
+ margin-left: 0 !important;
+ }
+
+ .m-xl-1 {
+ margin: 0.25rem !important;
+ }
+
+ .mt-xl-1,
+ .my-xl-1 {
+ margin-top: 0.25rem !important;
+ }
+
+ .mr-xl-1,
+ .mx-xl-1 {
+ margin-right: 0.25rem !important;
+ }
+
+ .mb-xl-1,
+ .my-xl-1 {
+ margin-bottom: 0.25rem !important;
+ }
+
+ .ml-xl-1,
+ .mx-xl-1 {
+ margin-left: 0.25rem !important;
+ }
+
+ .m-xl-2 {
+ margin: 0.5rem !important;
+ }
+
+ .mt-xl-2,
+ .my-xl-2 {
+ margin-top: 0.5rem !important;
+ }
+
+ .mr-xl-2,
+ .mx-xl-2 {
+ margin-right: 0.5rem !important;
+ }
+
+ .mb-xl-2,
+ .my-xl-2 {
+ margin-bottom: 0.5rem !important;
+ }
+
+ .ml-xl-2,
+ .mx-xl-2 {
+ margin-left: 0.5rem !important;
+ }
+
+ .m-xl-3 {
+ margin: 1rem !important;
+ }
+
+ .mt-xl-3,
+ .my-xl-3 {
+ margin-top: 1rem !important;
+ }
+
+ .mr-xl-3,
+ .mx-xl-3 {
+ margin-right: 1rem !important;
+ }
+
+ .mb-xl-3,
+ .my-xl-3 {
+ margin-bottom: 1rem !important;
+ }
+
+ .ml-xl-3,
+ .mx-xl-3 {
+ margin-left: 1rem !important;
+ }
+
+ .m-xl-4 {
+ margin: 1.5rem !important;
+ }
+
+ .mt-xl-4,
+ .my-xl-4 {
+ margin-top: 1.5rem !important;
+ }
+
+ .mr-xl-4,
+ .mx-xl-4 {
+ margin-right: 1.5rem !important;
+ }
+
+ .mb-xl-4,
+ .my-xl-4 {
+ margin-bottom: 1.5rem !important;
+ }
+
+ .ml-xl-4,
+ .mx-xl-4 {
+ margin-left: 1.5rem !important;
+ }
+
+ .m-xl-5 {
+ margin: 3rem !important;
+ }
+
+ .mt-xl-5,
+ .my-xl-5 {
+ margin-top: 3rem !important;
+ }
+
+ .mr-xl-5,
+ .mx-xl-5 {
+ margin-right: 3rem !important;
+ }
+
+ .mb-xl-5,
+ .my-xl-5 {
+ margin-bottom: 3rem !important;
+ }
+
+ .ml-xl-5,
+ .mx-xl-5 {
+ margin-left: 3rem !important;
+ }
+
+ .p-xl-0 {
+ padding: 0 !important;
+ }
+
+ .pt-xl-0,
+ .py-xl-0 {
+ padding-top: 0 !important;
+ }
+
+ .pr-xl-0,
+ .px-xl-0 {
+ padding-right: 0 !important;
+ }
+
+ .pb-xl-0,
+ .py-xl-0 {
+ padding-bottom: 0 !important;
+ }
+
+ .pl-xl-0,
+ .px-xl-0 {
+ padding-left: 0 !important;
+ }
+
+ .p-xl-1 {
+ padding: 0.25rem !important;
+ }
+
+ .pt-xl-1,
+ .py-xl-1 {
+ padding-top: 0.25rem !important;
+ }
+
+ .pr-xl-1,
+ .px-xl-1 {
+ padding-right: 0.25rem !important;
+ }
+
+ .pb-xl-1,
+ .py-xl-1 {
+ padding-bottom: 0.25rem !important;
+ }
+
+ .pl-xl-1,
+ .px-xl-1 {
+ padding-left: 0.25rem !important;
+ }
+
+ .p-xl-2 {
+ padding: 0.5rem !important;
+ }
+
+ .pt-xl-2,
+ .py-xl-2 {
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+}
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+}
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+ src: url("../fonts/FreightSans/freight-sans-light.woff2") format("woff2"), url("../fonts/FreightSans/freight-sans-light.woff") format("woff");
+}
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+}
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+}
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+ src: url("../fonts/FreightSans/freight-sans-book.woff2") format("woff2"), url("../fonts/FreightSans/freight-sans-book.woff") format("woff");
+}
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+ font-style: normal;
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+}
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+ font-weight: 500;
+ font-style: normal;
+ unicode-range: u+0020-007f;
+ src: local("IBMPlexMono-Medium"), url("../fonts/IBMPlexMono/IBMPlexMono-Medium.woff2") format("woff2"), url("../fonts/IBMPlexMono/IBMPlexMono-Medium.woff") format("woff");
+}
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+ font-weight: 400;
+ font-style: normal;
+ unicode-range: u+0020-007f;
+ src: local("IBMPlexMono-Regular"), url("../fonts/IBMPlexMono/IBMPlexMono-Regular.woff2") format("woff2"), url("../fonts/IBMPlexMono/IBMPlexMono-Regular.woff") format("woff");
+}
+@font-face {
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+ font-weight: 300;
+ font-style: normal;
+ unicode-range: u+0020-007f;
+ src: local("IBMPlexMono-Light"), url("../fonts/IBMPlexMono/IBMPlexMono-Light.woff2") format("woff2"), url("../fonts/IBMPlexMono/IBMPlexMono-Light.woff") format("woff");
+}
+html {
+ position: relative;
+ min-height: 100%;
+ font-size: 12px;
+}
+@media screen and (min-width: 768px) {
+ html {
+ font-size: 16px;
+ }
+}
+
+* {
+ -webkit-box-sizing: border-box;
+ box-sizing: border-box;
+}
+
+body {
+ font-family: FreightSans, Helvetica Neue, Helvetica, Arial, sans-serif;
+}
+
+a:link,
+a:visited,
+a:hover {
+ text-decoration: none;
+ color: #e44c2c;
+}
+
+a.with-right-arrow, .btn.with-right-arrow {
+ padding-right: 1.375rem;
+ position: relative;
+ background-image: url("../images/chevron-right-orange.svg");
+ background-size: 6px 13px;
+ background-position: center right 5px;
+ background-repeat: no-repeat;
+}
+@media screen and (min-width: 768px) {
+ a.with-right-arrow, .btn.with-right-arrow {
+ background-size: 8px 14px;
+ background-position: center right 12px;
+ padding-right: 2rem;
+ }
+}
+
+::-webkit-input-placeholder {
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+}
+
+::-moz-placeholder {
+ color: #e44c2c;
+}
+
+:-ms-input-placeholder {
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+}
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+:-moz-placeholder {
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+}
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+ border: none;
+ border-bottom: 1px solid #939393;
+ width: 100%;
+ background-color: transparent;
+ outline: none;
+ font-size: 1.125rem;
+ letter-spacing: 0.25px;
+ line-height: 2.25rem;
+}
+.email-subscribe-form input[type="submit"] {
+ position: absolute;
+ right: 0;
+ top: 10px;
+ height: 15px;
+ width: 15px;
+ background-image: url("../images/arrow-right-with-tail.svg");
+ background-color: transparent;
+ background-repeat: no-repeat;
+ background-size: 15px 15px;
+ background-position: center center;
+ -webkit-appearance: none;
+ -moz-appearance: none;
+ appearance: none;
+ border: 0;
+}
+
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+ position: relative;
+}
+
+.anchorjs-link {
+ color: #6c6c6d !important;
+}
+@media screen and (min-width: 768px) {
+ .anchorjs-link:hover {
+ color: inherit;
+ text-decoration: none !important;
+ }
+}
+
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+}
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+code, kbd, pre, samp {
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+}
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+}
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+}
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+}
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+}
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+ display: flex;
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+ margin-right: auto;
+ position: fixed;
+ right: 0;
+ top: 0;
+ width: 100%;
+ z-index: 9999;
+ background-color: #ffffff;
+ border-bottom: 1px solid #e2e2e2;
+}
+@media screen and (min-width: 1200px) {
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+}
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+ display: -webkit-box;
+ display: -ms-flexbox;
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+}
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+}
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+}
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+}
+@media screen and (min-width: 1200px) {
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+}
+@media screen and (min-width: 1200px) {
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+}
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+ width: 25px;
+ height: 17px;
+ position: absolute;
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+}
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+}
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+}
+@media screen and (min-width: 1200px) {
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+ display: flex;
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+ -ms-flex-align: center;
+ align-items: center;
+ -webkit-box-pack: end;
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+ justify-content: flex-end;
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+}
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+ display: -ms-flexbox;
+ display: flex;
+ -webkit-box-align: center;
+ -ms-flex-align: center;
+ align-items: center;
+ margin: 0;
+}
+.header-holder .main-menu ul li {
+ display: inline-block;
+ margin-right: 34px;
+ position: relative;
+ color: #262626;
+}
+
+.header-holder .main-menu ul li a:hover {
+ color: #262626;
+}
+
+.header-holder .main-menu ul li.active:after {
+ content: "•";
+ bottom: -24px;
+ color: #262626;
+ font-size: 1.375rem;
+ left: 0;
+ position: absolute;
+ right: 0;
+ text-align: center;
+}
+
+
+.header-holder .main-menu ul li.active a {
+ color: #262626;
+}
+.header-holder .main-menu ul li.docs-active:after {
+ content: "•";
+ bottom: -24px;
+ color: #e44c2c;
+ font-size: 1.375rem;
+ left: -24px;
+ position: absolute;
+ right: 0;
+ text-align: center;
+}
+.header-holder .main-menu ul li:last-of-type {
+ margin-right: 0;
+}
+.header-holder .main-menu ul li a {
+ color: #ffffff;
+ font-size: 1.2rem;
+ letter-spacing: 0;
+ line-height: 2.125rem;
+ text-align: center;
+ text-decoration: none;
+}
+@media screen and (min-width: 1200px) {
+ .header-holder .main-menu ul li a:hover {
+ color: #e44c2c;
+ }
+}
+
+.mobile-main-menu {
+ display: none;
+}
+.mobile-main-menu.open {
+ background-color: #262626;
+ display: block;
+ height: 100%;
+ left: 0;
+ margin-left: auto;
+ margin-right: auto;
+ min-height: 100%;
+ position: fixed;
+ right: 0;
+ top: 0;
+ width: 100%;
+ z-index: 99999;
+}
+
+.mobile-main-menu .container-fluid {
+ -webkit-box-align: center;
+ -ms-flex-align: center;
+ align-items: center;
+ display: -webkit-box;
+ display: -ms-flexbox;
+ display: flex;
+ height: 68px;
+ position: relative;
+}
+.mobile-main-menu .container-fluid:before, .mobile-main-menu .container-fluid:after {
+ content: "";
+ display: table;
+}
+.mobile-main-menu .container-fluid:after {
+ clear: both;
+}
+.mobile-main-menu .container-fluid {
+ *zoom: 1;
+}
+
+.mobile-main-menu.open ul {
+ list-style-type: none;
+ padding: 0;
+}
+.mobile-main-menu.open ul li a, .mobile-main-menu.open .resources-mobile-menu-title {
+ font-size: 2rem;
+ color: #ffffff;
+ letter-spacing: 0;
+ line-height: 4rem;
+ text-decoration: none;
+}
+.mobile-main-menu.open ul li.active a {
+ color: #e44c2c;
+}
+
+.main-menu-close-button {
+ background-image: url("../images/icon-close.svg");
+ background-position: center center;
+ background-repeat: no-repeat;
+ background-size: 24px 24px;
+ height: 24px;
+ position: absolute;
+ right: 0;
+ width: 24px;
+ top: -4px;
+}
+
+.mobile-main-menu-header-container {
+ position: relative;
+}
+
+.mobile-main-menu-links-container {
+ display: -webkit-box;
+ display: -ms-flexbox;
+ display: flex;
+ -webkit-box-align: center;
+ -ms-flex-align: center;
+ align-items: center;
+ padding-left: 2.8125rem;
+ height: 90vh;
+ margin-top: -25px;
+ padding-top: 50%;
+ overflow-y: scroll;
+}
+.mobile-main-menu-links-container .main-menu {
+ height: 100vh;
+}
+
+.mobile-main-menu-links-container ul.resources-mobile-menu-items li {
+ padding-left: 15px;
+}
+
+.mobile-main-menu-links-container ul.resources-mobile-menu-items li a {
+ font-size: 18px;
+ line-height: 34px;
+}
+
+.site-footer {
+ padding: 2.5rem 0;
+ width: 100%;
+ background: #000000;
+ background-size: 100%;
+ margin-left: 0;
+ margin-right: 0;
+ position: relative;
+ z-index: 201;
+}
+@media screen and (min-width: 768px) {
+ .site-footer {
+ padding: 5rem 0;
+ }
+}
+
+.site-footer p {
+ color: #ffffff;
+}
+.site-footer ul {
+ list-style-type: none;
+ padding-left: 0;
+ margin-bottom: 0;
+}
+
+.site-footer ul li {
+ font-size: 1.125rem;
+ line-height: 2rem;
+ color: #A0A0A1;
+ padding-bottom: 0.375rem;
+}
+.site-footer ul li.list-title {
+ padding-bottom: 0.75rem;
+ color: #ffffff;
+}
+.site-footer a:link,
+.site-footer a:visited {
+ color: inherit;
+}
+@media screen and (min-width: 768px) {
+ .site-footer a:hover {
+ color: #e44c2c;
+ }
+}
+
+.site-footer .privacy-policy {
+ background: #000000;
+ display: flex;
+ border-bottom: 1px solid white;
+ padding-bottom: 10px;
+}
+
+.site-footer .privacy-policy-links {
+ background: #000000;
+ display: flex;
+ padding-top: 1rem;
+ padding-right: 1rem;
+ display: inline-flex;
+ color: white;
+}
+
+.site-footer .footer-links-wrapper {
+ display: flex;
+ flex-wrap: wrap;
+ border-bottom: 1px solid white;
+ padding-bottom: 1rem;
+}
+
+.site-footer .copyright {
+ padding-top: 1rem;
+ padding-right: 1rem;
+ display: inline-flex;
+ color: white;
+}
+
+.site-footer .copyright p {
+ color: white;
+}
+
+.site-footer .copyright a {
+ color: red;
+}
+
+.docs-tutorials-resources {
+ background-color: #262626;
+ color: #ffffff;
+ padding-top: 2.5rem;
+ padding-bottom: 2.5rem;
+ position: relative;
+ z-index: 201;
+}
+@media screen and (min-width: 768px) {
+ .docs-tutorials-resources {
+ padding-top: 5rem;
+ padding-bottom: 5rem;
+ }
+}
+.docs-tutorials-resources p {
+ color: #929292;
+ font-size: 1.125rem;
+}
+.docs-tutorials-resources h2 {
+ font-size: 1.5rem;
+ letter-spacing: -0.25px;
+ text-transform: none;
+ margin-bottom: 0.25rem;
+}
+@media screen and (min-width: 768px) {
+ .docs-tutorials-resources h2 {
+ margin-bottom: 1.25rem;
+ }
+}
+.docs-tutorials-resources .col-md-4 {
+ margin-bottom: 2rem;
+ text-align: center;
+}
+@media screen and (min-width: 768px) {
+ .docs-tutorials-resources .col-md-4 {
+ margin-bottom: 0;
+ }
+}
+.docs-tutorials-resources .with-right-arrow {
+ margin-left: 12px;
+}
+.docs-tutorials-resources .with-right-arrow:hover {
+ background-image: url("../images/chevron-right-white.svg");
+}
+.docs-tutorials-resources p {
+ font-size: 1rem;
+ line-height: 1.5rem;
+ letter-spacing: 0.22px;
+ color: #939393;
+ margin-bottom: 0;
+}
+@media screen and (min-width: 768px) {
+ .docs-tutorials-resources p {
+ margin-bottom: 1.25rem;
+ }
+}
+.docs-tutorials-resources a {
+ font-size: 1.125rem;
+ color: #e44c2c;
+}
+.docs-tutorials-resources a:hover {
+ color: #ffffff;
+}
+
+.footer-container {
+ position: relative;
+}
+
+@media screen and (min-width: 768px) {
+ .footer-logo-wrapper {
+ position: absolute;
+ top: 0;
+ left: 30px;
+ }
+}
+
+.footer-logo {
+ background-image: url("../images/logo-icon.svg");
+ background-position: center;
+ background-repeat: no-repeat;
+ background-size: 20px 24px;
+ display: block;
+ height: 24px;
+ margin-bottom: 2.8125rem;
+ width: 20px;
+}
+@media screen and (min-width: 768px) {
+ .footer-logo {
+ background-size: 29px 36px;
+ height: 36px;
+ margin-bottom: 0;
+ margin-bottom: 0;
+ width: 29px;
+ }
+}
+
+.footer-links-wrapper {
+ display: -webkit-box;
+ display: -ms-flexbox;
+ display: flex;
+ -ms-flex-wrap: wrap;
+ flex-wrap: wrap;
+}
+@media screen and (min-width: 768px) {
+ .footer-links-wrapper {
+ -ms-flex-wrap: initial;
+ flex-wrap: initial;
+ -webkit-box-pack: end;
+ -ms-flex-pack: end;
+ justify-content: flex-end;
+ }
+}
+
+.footer-links-col {
+ margin-bottom: 3.75rem;
+ width: 50%;
+}
+@media screen and (min-width: 768px) {
+ .footer-links-col {
+ margin-bottom: 0;
+ width: 14%;
+ margin-right: 23px;
+ }
+ .footer-links-col.follow-us-col {
+ width: 18%;
+ margin-right: 0;
+ }
+}
+@media (min-width: 768px) and (max-width: 1239px) {
+ .footer-links-col {
+ width: 18%;
+ margin-right: 30px;
+ }
+}
+
+.footer-social-icons {
+ margin: 8.5625rem 0 2.5rem 0;
+}
+.footer-social-icons a {
+ height: 32px;
+ width: 32px;
+ display: inline-block;
+ background-color: #CCCDD1;
+ border-radius: 50%;
+ margin-right: 5px;
+}
+.footer-social-icons a.facebook {
+ background-image: url("../images/logo-facebook-dark.svg");
+ background-position: center center;
+ background-size: 9px 18px;
+ background-repeat: no-repeat;
+}
+.footer-social-icons a.twitter {
+ background-image: url("../images/logo-twitter-dark.svg");
+ background-position: center center;
+ background-size: 17px 17px;
+ background-repeat: no-repeat;
+}
+.footer-social-icons a.youtube {
+ background-image: url("../images/logo-youtube-dark.svg");
+ background-position: center center;
+ background-repeat: no-repeat;
+}
+
+.site-footer .mc-field-group {
+ margin-top: -2px;
+}
+
+article.pytorch-article {
+ max-width: 920px;
+ margin: 0 auto;
+}
+article.pytorch-article h2,
+article.pytorch-article h3,
+article.pytorch-article h4,
+article.pytorch-article h5,
+article.pytorch-article h6 {
+ margin: 1.375rem 0;
+ color: #262626;
+}
+article.pytorch-article h2 {
+ font-size: 1.625rem;
+ letter-spacing: 1.33px;
+ line-height: 2rem;
+ text-transform: none;
+}
+article.pytorch-article h3 {
+ font-size: 1.5rem;
+ letter-spacing: -0.25px;
+ line-height: 1.875rem;
+ text-transform: none;
+}
+article.pytorch-article h4,
+article.pytorch-article h5,
+article.pytorch-article h6 {
+ font-size: 1.125rem;
+ letter-spacing: -0.19px;
+ line-height: 1.875rem;
+}
+article.pytorch-article p {
+ margin-bottom: 1.125rem;
+}
+article.pytorch-article p,
+article.pytorch-article ul li,
+article.pytorch-article ol li,
+article.pytorch-article dl dt,
+article.pytorch-article dl dd,
+article.pytorch-article blockquote {
+ font-size: 1rem;
+ color: #262626;
+ letter-spacing: 0.01px;
+ font-weight: 500;
+}
+article.pytorch-article table {
+ margin-bottom: 2.5rem;
+ width: 100%;
+}
+article.pytorch-article table thead {
+ border-bottom: 1px solid #cacaca;
+}
+article.pytorch-article table th {
+ padding: 0.625rem;
+ color: #262626;
+}
+article.pytorch-article table td {
+ padding: 0.3125rem;
+}
+article.pytorch-article table tr th:first-of-type,
+article.pytorch-article table tr td:first-of-type {
+ padding-left: 0;
+}
+article.pytorch-article table.docutils.field-list th.field-name {
+ padding: 0.3125rem;
+ padding-left: 0;
+}
+article.pytorch-article table.docutils.field-list td.field-body {
+ padding: 0.3125rem;
+}
+article.pytorch-article table.docutils.field-list td.field-body p:last-of-type {
+ margin-bottom: 0;
+}
+article.pytorch-article ul,
+article.pytorch-article ol {
+ margin: 1.5rem 0 3.125rem 0;
+}
+@media screen and (min-width: 768px) {
+ article.pytorch-article ul,
+ article.pytorch-article ol {
+ padding-left: 6.25rem;
+ }
+}
+article.pytorch-article ul li,
+article.pytorch-article ol li {
+ margin-bottom: 0.625rem;
+}
+article.pytorch-article dl {
+ margin-bottom: 1.5rem;
+}
+article.pytorch-article dl dt {
+ margin-bottom: 0.75rem;
+}
+article.pytorch-article pre {
+ margin-bottom: 2.5rem;
+}
+article.pytorch-article hr {
+ margin-top: 4.6875rem;
+ margin-bottom: 4.6875rem;
+}
+article.pytorch-article blockquote {
+ margin: 0 auto;
+ margin-bottom: 2.5rem;
+ width: 65%;
+}
+article.pytorch-article img {
+ width: 100%;
+}
+
+html {
+ height: 100%;
+}
+@media screen and (min-width: 768px) {
+ html {
+ font-size: 16px;
+ }
+}
+
+body {
+ background: #ffffff;
+ height: 100%;
+ margin: 0;
+}
+body.no-scroll {
+ height: 100%;
+ overflow: hidden;
+}
+
+p {
+ margin-top: 0;
+ margin-bottom: 1.125rem;
+}
+p a:link,
+p a:visited,
+p a:hover {
+ color: #e44c2c;
+ text-decoration: none;
+}
+@media screen and (min-width: 768px) {
+ p a:hover {
+ text-decoration: underline;
+ }
+}
+p a:link,
+p a:visited,
+p a:hover {
+ color: #ee4c2c;
+}
+
+.wy-breadcrumbs li a {
+ color: #ee4c2c;
+}
+
+ul.pytorch-breadcrumbs {
+ padding-left: 0;
+ list-style-type: none;
+}
+ul.pytorch-breadcrumbs li {
+ display: inline-block;
+ font-size: 0.875rem;
+}
+ul.pytorch-breadcrumbs a {
+ color: #ee4c2c;
+ text-decoration: none;
+}
+
+.table-of-contents-link-wrapper {
+ display: block;
+ margin-top: 0;
+ padding: 1.25rem 1.875rem;
+ background-color: #f3f4f7;
+ position: relative;
+ color: #262626;
+ font-size: 1.25rem;
+}
+.table-of-contents-link-wrapper.is-open .toggle-table-of-contents {
+ -webkit-transform: rotate(180deg);
+ transform: rotate(180deg);
+}
+@media screen and (min-width: 1200px) {
+ .table-of-contents-link-wrapper {
+ display: none;
+ }
+}
+
+.toggle-table-of-contents {
+ background-image: url("../images/chevron-down-grey.svg");
+ background-position: center center;
+ background-repeat: no-repeat;
+ background-size: 18px 18px;
+ height: 100%;
+ position: absolute;
+ right: 21px;
+ width: 30px;
+ top: 0;
+}
+
+.tutorials-header .header-logo {
+ background-image: url("../images/logo-dark.svg");
+}
+.tutorials-header .main-menu ul li a {
+ color: #262626;
+}
+
+.tutorials-header .main-menu ul li a:hover {
+ color: #262626;
+}
+
+.tutorials-header .main-menu .no-dropdown {
+ display: block;
+}
+
+.tutorials-header .main-menu .no-dropdown a {
+ color: #262626;
+}
+
+.tutorials-header .main-menu .no-dropdown a:hover {
+ color: #262626 !important;
+ border-bottom: 2px solid #262626;
+}
+
+.tutorials-header .main-menu-open-button {
+ background-image: url("../images/icon-menu-dots-dark.svg");
+}
+
+.rst-content footer .rating-hr.hr-top {
+ margin-bottom: -0.0625rem;
+}
+.rst-content footer .rating-hr.hr-bottom {
+ margin-top: -0.0625rem;
+}
+.rst-content footer .rating-container {
+ display: -webkit-inline-box;
+ display: -ms-inline-flexbox;
+ display: inline-flex;
+ font-size: 1.125rem;
+}
+.rst-content footer .rating-container .rating-prompt, .rst-content footer .rating-container .was-helpful-thank-you {
+ padding: 0.625rem 1.25rem 0.625rem 1.25rem;
+}
+.rst-content footer .rating-container .was-helpful-thank-you {
+ display: none;
+}
+.rst-content footer .rating-container .rating-prompt.yes-link, .rst-content footer .rating-container .rating-prompt.no-link {
+ color: #e44c2c;
+ cursor: pointer;
+}
+.rst-content footer .rating-container .rating-prompt.yes-link:hover, .rst-content footer .rating-container .rating-prompt.no-link:hover {
+ background-color: #e44c2c;
+ color: #ffffff;
+}
+.rst-content footer .rating-container .stars-outer {
+ display: inline-block;
+ position: relative;
+ font-family: FontAwesome;
+ padding: 0.625rem 1.25rem 0.625rem 1.25rem;
+}
+.rst-content footer .rating-container .stars-outer i {
+ cursor: pointer;
+}
+.rst-content footer .rating-container .stars-outer .star-fill {
+ color: #ee4c2c;
+}
+.rst-content footer div[role="contentinfo"] {
+ padding-top: 2.5rem;
+}
+.rst-content footer div[role="contentinfo"] p {
+ margin-bottom: 0;
+}
+
+h1 {
+ font-size: 2rem;
+ letter-spacing: 1.78px;
+ line-height: 2.5rem;
+ margin: 1.375rem 0;
+}
+
+span.pre {
+ color: #6c6c6d;
+ background-color: #f3f4f7;
+ padding: 2px 0px;
+}
+
+pre {
+ padding: 1.375rem;
+}
+
+.highlight .c1 {
+ color: #6c6c6d;
+}
+
+.headerlink {
+ display: none !important;
+}
+
+a:link.has-code,
+a:hover.has-code,
+a:visited.has-code {
+ color: #4974D1;
+}
+a:link.has-code span,
+a:hover.has-code span,
+a:visited.has-code span {
+ color: #4974D1;
+}
+
+article.pytorch-article ul,
+article.pytorch-article ol {
+ padding-left: 1.875rem;
+ margin: 0;
+}
+article.pytorch-article ul li,
+article.pytorch-article ol li {
+ margin: 0;
+ line-height: 1.75rem;
+}
+article.pytorch-article ul p,
+article.pytorch-article ol p {
+ line-height: 1.75rem;
+ margin-bottom: 0;
+}
+article.pytorch-article ul ul,
+article.pytorch-article ul ol,
+article.pytorch-article ol ul,
+article.pytorch-article ol ol {
+ margin: 0;
+}
+article.pytorch-article h1 {
+ font-weight: 600;
+ word-wrap: break-word;
+}
+article.pytorch-article h2,
+article.pytorch-article h3,
+article.pytorch-article h4,
+article.pytorch-article h5,
+article.pytorch-article h6 {
+ font-weight: normal;
+}
+article.pytorch-article h1 a,
+article.pytorch-article h2 a,
+article.pytorch-article h3 a,
+article.pytorch-article h4 a,
+article.pytorch-article h5 a,
+article.pytorch-article h6 a {
+ color: #262626;
+}
+article.pytorch-article p.caption {
+ margin-top: 1.25rem;
+}
+
+article.pytorch-article .section:first-of-type h1:first-of-type {
+ margin-top: 0;
+}
+
+article.pytorch-article .sphx-glr-thumbcontainer {
+ margin: 0;
+ border: 1px solid #d6d7d8;
+ border-radius: 0;
+ width: 45%;
+ text-align: center;
+ margin-bottom: 5%;
+}
+@media screen and (max-width: 1200px) {
+ article.pytorch-article .sphx-glr-thumbcontainer:nth-child(odd) {
+ margin-left: 0;
+ margin-right: 2.5%;
+ }
+ article.pytorch-article .sphx-glr-thumbcontainer:nth-child(even) {
+ margin-right: 0;
+ margin-left: 2.5%;
+ }
+ article.pytorch-article .sphx-glr-thumbcontainer .figure {
+ width: 40%;
+ }
+}
+@media screen and (min-width: 1201px) {
+ article.pytorch-article .sphx-glr-thumbcontainer {
+ margin-right: 3%;
+ margin-bottom: 3%;
+ width: 30%;
+ }
+}
+article.pytorch-article .sphx-glr-thumbcontainer .caption-text a {
+ font-size: 1rem;
+ color: #262626;
+ letter-spacing: 0;
+ line-height: 1.5rem;
+ text-decoration: none;
+}
+article.pytorch-article .sphx-glr-thumbcontainer:hover {
+ -webkit-box-shadow: none;
+ box-shadow: none;
+ border-bottom-color: #ffffff;
+}
+article.pytorch-article .sphx-glr-thumbcontainer:hover .figure:before {
+ bottom: 100%;
+}
+article.pytorch-article .sphx-glr-thumbcontainer .figure {
+ width: 80%;
+}
+article.pytorch-article .sphx-glr-thumbcontainer .figure:before {
+ content: "";
+ display: block;
+ position: absolute;
+ top: 0;
+ bottom: 35%;
+ left: 0;
+ right: 0;
+ background: #8A94B3;
+ opacity: 0.10;
+}
+article.pytorch-article .sphx-glr-thumbcontainer .figure a.reference.internal {
+ text-align: left;
+}
+@media screen and (min-width: 768px) {
+ article.pytorch-article .sphx-glr-thumbcontainer:after {
+ content: "";
+ display: block;
+ width: 0;
+ height: 1px;
+ position: absolute;
+ bottom: 0;
+ left: 0;
+ background-color: #e44c2c;
+ -webkit-transition: width .250s ease-in-out;
+ transition: width .250s ease-in-out;
+ }
+ article.pytorch-article .sphx-glr-thumbcontainer:hover:after {
+ width: 100%;
+ }
+}
+@media screen and (min-width: 768px) {
+ article.pytorch-article .sphx-glr-thumbcontainer:after {
+ background-color: #ee4c2c;
+ }
+}
+
+article.pytorch-article .section :not(dt) > code {
+ color: #262626;
+ border-top: solid 2px #ffffff;
+ background-color: #ffffff;
+ border-bottom: solid 2px #ffffff;
+ padding: 0px 3px;
+ -webkit-box-decoration-break: clone;
+ box-decoration-break: clone;
+}
+article.pytorch-article .section :not(dt) > code .pre {
+ outline: 0px;
+ padding: 0px;
+}
+article.pytorch-article .function dt, article.pytorch-article .attribute dt, article.pytorch-article .class .attribute dt, article.pytorch-article .class dt {
+ position: relative;
+ background: #f3f4f7;
+ padding: 0.5rem;
+ border-left: 3px solid #ee4c2c;
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+article.pytorch-article .math {
+ color: #262626;
+ width: auto;
+ text-align: center;
+}
+article.pytorch-article .math img {
+ width: auto;
+}
+
+.pytorch-breadcrumbs-wrapper {
+ width: 100%;
+}
+@media screen and (min-width: 1201px) {
+ .pytorch-breadcrumbs-wrapper {
+ float: left;
+ margin-left: 3%;
+ width: 75%;
+ }
+}
+@media screen and (min-width: 1600px) {
+ .pytorch-breadcrumbs-wrapper {
+ width: 850px;
+ margin-left: 1.875rem;
+ }
+}
+.pytorch-breadcrumbs-wrapper .pytorch-breadcrumbs-aside {
+ float: right;
+}
+.pytorch-breadcrumbs-wrapper .pytorch-breadcrumbs-aside .fa.fa-github {
+ margin-top: 5px;
+ display: block;
+}
+
+.pytorch-article .container {
+ padding-left: 0;
+ padding-right: 0;
+ max-width: none;
+}
+
+a:link,
+a:visited,
+a:hover {
+ color: #ee4c2c;
+}
+
+::-webkit-input-placeholder {
+ color: #ee4c2c;
+}
+
+::-moz-placeholder {
+ color: #ee4c2c;
+}
+
+:-ms-input-placeholder {
+ color: #ee4c2c;
+}
+
+:-moz-placeholder {
+ color: #ee4c2c;
+}
+
+@media screen and (min-width: 768px) {
+ .site-footer a:hover {
+ color: #ee4c2c;
+ }
+}
+
+.docs-tutorials-resources a {
+ color: #ee4c2c;
+}
+
+.header-holder {
+ position: relative;
+ z-index: 201;
+}
+
+.header-holder .main-menu ul li.active:after {
+ color: #ee4c2c;
+}
+.header-holder .main-menu ul li.active a {
+ color: #ee4c2c;
+}
+@media screen and (min-width: 1200px) {
+ .header-holder .main-menu ul li a:hover {
+ color: #ee4c2c;
+ }
+}
+
+.mobile-main-menu.open ul li.active a {
+ color: #ee4c2c;
+}
+
+.version {
+ padding-bottom: 1rem;
+}
+
+.pytorch-call-to-action-links {
+ padding-top: 0;
+ display: -webkit-box;
+ display: -ms-flexbox;
+ display: flex;
+}
+@media screen and (min-width: 768px) {
+ .pytorch-call-to-action-links {
+ padding-top: 2.5rem;
+ }
+}
+@media (min-width: 768px) and (max-width: 1239px) {
+ .pytorch-call-to-action-links {
+ padding-top: 0;
+ }
+}
+@media (min-width: 1200px) and (max-width: 1239px) {
+ .pytorch-call-to-action-links {
+ padding-top: 2.5rem;
+ }
+}
+.pytorch-call-to-action-links #tutorial-type {
+ display: none;
+}
+.pytorch-call-to-action-links .call-to-action-img, .pytorch-call-to-action-links .call-to-action-notebook-img {
+ height: 1.375rem;
+ width: 1.375rem;
+ margin-right: 10px;
+}
+.pytorch-call-to-action-links .call-to-action-notebook-img {
+ height: 1rem;
+}
+.pytorch-call-to-action-links a {
+ padding-right: 1.25rem;
+ color: #000000;
+ cursor: pointer;
+}
+.pytorch-call-to-action-links a:hover {
+ color: #e44c2c;
+}
+.pytorch-call-to-action-links a .call-to-action-desktop-view {
+ display: none;
+}
+@media screen and (min-width: 768px) {
+ .pytorch-call-to-action-links a .call-to-action-desktop-view {
+ display: block;
+ }
+}
+.pytorch-call-to-action-links a .call-to-action-mobile-view {
+ display: block;
+}
+@media screen and (min-width: 768px) {
+ .pytorch-call-to-action-links a .call-to-action-mobile-view {
+ display: none;
+ }
+}
+.pytorch-call-to-action-links a #google-colab-link, .pytorch-call-to-action-links a #download-notebook-link,
+.pytorch-call-to-action-links a #github-view-link {
+ padding-bottom: 0.625rem;
+ border-bottom: 1px solid #f3f4f7;
+ padding-right: 2.5rem;
+ display: -webkit-box;
+ display: -ms-flexbox;
+ display: flex;
+ -webkit-box-align: center;
+ -ms-flex-align: center;
+ align-items: center;
+}
+.pytorch-call-to-action-links a #google-colab-link:hover, .pytorch-call-to-action-links a #download-notebook-link:hover,
+.pytorch-call-to-action-links a #github-view-link:hover {
+ border-bottom-color: #e44c2c;
+ color: #e44c2c;
+}
+
+#tutorial-cards-container #tutorial-cards {
+ width: 100%;
+}
+#tutorial-cards-container .tutorials-nav {
+ padding-left: 0;
+ padding-right: 0;
+ padding-bottom: 0;
+}
+#tutorial-cards-container .tutorials-hr {
+ margin-top: 1rem;
+ margin-bottom: 1rem;
+}
+#tutorial-cards-container .card.tutorials-card {
+ border-radius: 0;
+ border-color: #f3f4f7;
+ height: 98px;
+ margin-bottom: 1.25rem;
+ margin-bottom: 1.875rem;
+ overflow: scroll;
+ background-color: #f3f4f7;
+ cursor: pointer;
+}
+@media screen and (min-width: 1240px) {
+ #tutorial-cards-container .card.tutorials-card {
+ height: 200px;
+ overflow: inherit;
+ }
+}
+@media (min-width: 768px) and (max-width: 1239px) {
+ #tutorial-cards-container .card.tutorials-card {
+ height: 200px;
+ overflow: scroll;
+ }
+}
+#tutorial-cards-container .card.tutorials-card .tutorials-image {
+ position: absolute;
+ top: 0px;
+ right: 0px;
+ height: 96px;
+ width: 96px;
+ opacity: 0.5;
+}
+#tutorial-cards-container .card.tutorials-card .tutorials-image img {
+ height: 100%;
+ width: 100%;
+}
+@media screen and (min-width: 768px) {
+ #tutorial-cards-container .card.tutorials-card .tutorials-image {
+ height: 100%;
+ width: 25%;
+ }
+}
+@media (min-width: 768px) and (max-width: 1239px) {
+ #tutorial-cards-container .card.tutorials-card .tutorials-image {
+ height: 100%;
+ width: 198px;
+ }
+}
+#tutorial-cards-container .card.tutorials-card .tutorials-image:before {
+ content: '';
+ position: absolute;
+ top: 0;
+ left: 0;
+ bottom: 0;
+ right: 0;
+ z-index: 1;
+ background: #000000;
+ opacity: .075;
+}
+#tutorial-cards-container .card.tutorials-card .card-title-container {
+ width: 70%;
+ display: -webkit-inline-box;
+ display: -ms-inline-flexbox;
+ display: inline-flex;
+}
+@media screen and (min-width: 768px) {
+ #tutorial-cards-container .card.tutorials-card .card-title-container {
+ width: 75%;
+ }
+}
+@media (min-width: 768px) and (max-width: 1239px) {
+ #tutorial-cards-container .card.tutorials-card .card-title-container {
+ width: 70%;
+ }
+}
+#tutorial-cards-container .card.tutorials-card .card-title-container h4 {
+ margin-bottom: 1.125rem;
+ margin-top: 0;
+ font-size: 1.5rem;
+}
+#tutorial-cards-container .card.tutorials-card p.card-summary, #tutorial-cards-container .card.tutorials-card p.tags {
+ font-size: 0.9375rem;
+ line-height: 1.5rem;
+ margin-bottom: 0;
+ color: #6c6c6d;
+ font-weight: 400;
+ width: 70%;
+}
+@media screen and (min-width: 768px) {
+ #tutorial-cards-container .card.tutorials-card p.card-summary, #tutorial-cards-container .card.tutorials-card p.tags {
+ width: 75%;
+ }
+}
+@media (min-width: 768px) and (max-width: 1239px) {
+ #tutorial-cards-container .card.tutorials-card p.card-summary, #tutorial-cards-container .card.tutorials-card p.tags {
+ width: 70%;
+ }
+}
+#tutorial-cards-container .card.tutorials-card p.tags {
+ margin-top: 30px;
+ text-overflow: ellipsis;
+ white-space: nowrap;
+ overflow: hidden;
+}
+#tutorial-cards-container .card.tutorials-card h4 {
+ color: #262626;
+ margin-bottom: 1.125rem;
+}
+#tutorial-cards-container .card.tutorials-card a {
+ height: 100%;
+}
+@media screen and (min-width: 768px) {
+ #tutorial-cards-container .card.tutorials-card a {
+ min-height: 190px;
+ }
+}
+@media (min-width: 768px) and (max-width: 1239px) {
+ #tutorial-cards-container .card.tutorials-card a {
+ min-height: 234px;
+ }
+}
+@media screen and (min-width: 768px) {
+ #tutorial-cards-container .card.tutorials-card:after {
+ content: "";
+ display: block;
+ width: 0;
+ height: 1px;
+ position: absolute;
+ bottom: 0;
+ left: 0;
+ background-color: #e44c2c;
+ -webkit-transition: width .250s ease-in-out;
+ transition: width .250s ease-in-out;
+ }
+ #tutorial-cards-container .card.tutorials-card:hover:after {
+ width: 100%;
+ }
+}
+#tutorial-cards-container .card.tutorials-card:hover {
+ background-color: #ffffff;
+ border: 1px solid #e2e2e2;
+ border-bottom: none;
+}
+#tutorial-cards-container .card.tutorials-card:hover p.card-summary {
+ color: #262626;
+}
+#tutorial-cards-container .card.tutorials-card:hover .tutorials-image {
+ opacity: unset;
+}
+#tutorial-cards-container .tutorial-tags-container {
+ width: 75%;
+}
+#tutorial-cards-container .tutorial-tags-container.active {
+ width: 0;
+}
+#tutorial-cards-container .tutorial-filter-menu ul {
+ list-style-type: none;
+ padding-left: 1.25rem;
+}
+#tutorial-cards-container .tutorial-filter-menu ul li {
+ padding-right: 1.25rem;
+ word-break: break-all;
+}
+#tutorial-cards-container .tutorial-filter-menu ul li a {
+ color: #979797;
+}
+#tutorial-cards-container .tutorial-filter-menu ul li a:hover {
+ color: #e44c2c;
+}
+#tutorial-cards-container .tutorial-filter {
+ cursor: pointer;
+}
+#tutorial-cards-container .filter-btn {
+ color: #979797;
+ border: 1px solid #979797;
+ display: inline-block;
+ text-align: center;
+ white-space: nowrap;
+ vertical-align: middle;
+ padding: 0.375rem 0.75rem;
+ font-size: 1rem;
+ line-height: 1.5;
+ margin-bottom: 5px;
+}
+#tutorial-cards-container .filter-btn:hover {
+ border: 1px solid #e44c2c;
+ color: #e44c2c;
+}
+#tutorial-cards-container .filter-btn.selected {
+ background-color: #e44c2c;
+ border: 1px solid #e44c2c;
+ color: #ffffff;
+}
+#tutorial-cards-container .all-tag-selected {
+ background-color: #979797;
+ color: #ffffff;
+}
+#tutorial-cards-container .all-tag-selected:hover {
+ border-color: #979797;
+ color: #ffffff;
+}
+#tutorial-cards-container .pagination .page {
+ border: 1px solid #dee2e6;
+ padding: 0.5rem 0.75rem;
+}
+#tutorial-cards-container .pagination .active .page {
+ background-color: #dee2e6;
+}
+
+article.pytorch-article .tutorials-callout-container {
+ padding-bottom: 50px;
+}
+article.pytorch-article .tutorials-callout-container .col-md-6 {
+ padding-bottom: 10px;
+}
+article.pytorch-article .tutorials-callout-container .text-container {
+ padding: 10px 0px 30px 0px;
+ padding-bottom: 10px;
+}
+article.pytorch-article .tutorials-callout-container .text-container .body-paragraph {
+ color: #666666;
+ font-weight: 300;
+ font-size: 1.125rem;
+ line-height: 1.875rem;
+}
+article.pytorch-article .tutorials-callout-container .btn.callout-button {
+ font-size: 1.125rem;
+ border-radius: 0;
+ border: none;
+ background-color: #f3f4f7;
+ color: #6c6c6d;
+ font-weight: 400;
+ position: relative;
+ letter-spacing: 0.25px;
+}
+@media screen and (min-width: 768px) {
+ article.pytorch-article .tutorials-callout-container .btn.callout-button:after {
+ content: "";
+ display: block;
+ width: 0;
+ height: 1px;
+ position: absolute;
+ bottom: 0;
+ left: 0;
+ background-color: #e44c2c;
+ -webkit-transition: width .250s ease-in-out;
+ transition: width .250s ease-in-out;
+ }
+ article.pytorch-article .tutorials-callout-container .btn.callout-button:hover:after {
+ width: 100%;
+ }
+}
+article.pytorch-article .tutorials-callout-container .btn.callout-button a {
+ color: inherit;
+}
+
+.pytorch-container {
+ margin: 0 auto;
+ padding: 0 1.875rem;
+ width: auto;
+ position: relative;
+}
+@media screen and (min-width: 1201px) {
+ .pytorch-container {
+ padding: 0;
+ }
+}
+@media screen and (min-width: 1200px) {
+ .pytorch-container {
+ margin-left: 25%;
+ }
+}
+@media screen and (min-width: 1600px) {
+ .pytorch-container {
+ margin-left: 350px;
+ }
+}
+.pytorch-container:before, .pytorch-container:after {
+ content: "";
+ display: table;
+}
+.pytorch-container:after {
+ clear: both;
+}
+.pytorch-container {
+ *zoom: 1;
+}
+
+.pytorch-content-wrap {
+ background-color: #ffffff;
+ display: -webkit-box;
+ display: -ms-flexbox;
+ display: flex;
+ position: relative;
+ padding-top: 0;
+}
+.pytorch-content-wrap:before, .pytorch-content-wrap:after {
+ content: "";
+ display: table;
+}
+.pytorch-content-wrap:after {
+ clear: both;
+}
+.pytorch-content-wrap {
+ *zoom: 1;
+}
+@media screen and (min-width: 1201px) {
+ .pytorch-content-wrap {
+ padding-top: 45px;
+ float: left;
+ width: 100%;
+ display: block;
+ }
+}
+@media screen and (min-width: 1600px) {
+ .pytorch-content-wrap {
+ width: 100%;
+ }
+}
+
+.pytorch-content {
+ background: #ffffff;
+ width: 100%;
+ max-width: 700px;
+ position: relative;
+}
+
+.pytorch-content-left {
+ min-height: 100vh;
+ margin-top: 2.5rem;
+ width: 100%;
+}
+@media screen and (min-width: 1201px) {
+ .pytorch-content-left {
+ margin-top: 0;
+ margin-left: 3%;
+ width: 75%;
+ float: left;
+ }
+}
+@media screen and (min-width: 1600px) {
+ .pytorch-content-left {
+ width: 850px;
+ margin-left: 30px;
+ }
+}
+.pytorch-content-left .main-content {
+ padding-top: 0.9375rem;
+}
+.pytorch-content-left .main-content ul.simple {
+ padding-bottom: 1.25rem;
+}
+.pytorch-content-left .main-content .note:nth-child(1), .pytorch-content-left .main-content .warning:nth-child(1) {
+ margin-top: 0;
+}
+
+.pytorch-content-right {
+ display: none;
+ position: relative;
+ overflow-x: hidden;
+ overflow-y: hidden;
+}
+@media screen and (min-width: 1201px) {
+ .pytorch-content-right {
+ display: block;
+ margin-left: 0;
+ width: 19%;
+ float: left;
+ height: 100%;
+ }
+}
+@media screen and (min-width: 1600px) {
+ .pytorch-content-right {
+ width: 280px;
+ }
+}
+
+@media screen and (min-width: 1201px) {
+ .pytorch-side-scroll {
+ position: relative;
+ overflow-x: hidden;
+ overflow-n: scroll;
+ height: 100%;
+ }
+}
+
+.pytorch-menu-vertical {
+ padding: 1.25rem 1.875rem 2.5rem 1.875rem;
+}
+@media screen and (min-width: 1201px) {
+ .pytorch-menu-vertical {
+ display: block;
+ padding-top: 0;
+ padding-right: 13.5%;
+ padding-bottom: 5.625rem;
+ }
+}
+@media screen and (min-width: 1600px) {
+ .pytorch-menu-vertical {
+ padding-left: 0;
+ padding-right: 1.5625rem;
+ }
+}
+
+.pytorch-left-menu {
+ display: none;
+ background-color: #f3f4f7;
+ color: #262626;
+ overflow: scroll;
+}
+@media screen and (min-width: 1201px) {
+ .pytorch-left-menu {
+ display: block;
+ overflow-x: hidden;
+ overflow-y: hidden;
+ padding-bottom: 110px;
+ padding: 0 1.875rem 0 0;
+ width: 25%;
+ z-index: 200;
+ float: left;
+ }
+ .pytorch-left-menu.make-fixed {
+ position: fixed;
+ top: 0;
+ bottom: 0;
+ left: 0;
+ float: none;
+ }
+}
+@media screen and (min-width: 1600px) {
+ .pytorch-left-menu {
+ padding: 0 0 0 1.875rem;
+ width: 350px;
+ }
+}
+
+.expand-menu, .hide-menu {
+ color: #6c6c6d;
+ padding-left: 10px;
+ cursor: pointer;
+}
+
+.collapse {
+ display: none;
+}
+
+.left-nav-top-caption {
+ padding-top: 1rem;
+}
+
+.pytorch-left-menu p.caption {
+ color: #262626;
+ display: block;
+ font-size: 1rem;
+ line-height: 1.375rem;
+ margin-bottom: 1rem;
+ text-transform: none;
+ white-space: normal;
+}
+
+.pytorch-left-menu-search {
+ margin-bottom: 2.5rem;
+}
+@media screen and (min-width: 1201px) {
+ .pytorch-left-menu-search {
+ margin: 1.25rem 0.625rem 1.875rem 0;
+ }
+}
+
+.pytorch-left-menu-search ::-webkit-input-placeholder {
+ color: #262626;
+}
+.pytorch-left-menu-search ::-moz-placeholder {
+ color: #262626;
+}
+.pytorch-left-menu-search :-ms-input-placeholder {
+ color: #262626;
+}
+.pytorch-left-menu-search ::-ms-input-placeholder {
+ color: #262626;
+}
+.pytorch-left-menu-search ::placeholder {
+ color: #262626;
+}
+
+.pytorch-left-menu-search :focus::-webkit-input-placeholder {
+ color: transparent;
+}
+.pytorch-left-menu-search :focus::-moz-placeholder {
+ color: transparent;
+}
+.pytorch-left-menu-search :focus:-ms-input-placeholder {
+ color: transparent;
+}
+.pytorch-left-menu-search :focus::-ms-input-placeholder {
+ color: transparent;
+}
+.pytorch-left-menu-search :focus::placeholder {
+ color: transparent;
+}
+
+.pytorch-left-menu-search input[type=text] {
+ border-radius: 0;
+ padding: 0.5rem 0.75rem;
+ border-color: #ffffff;
+ color: #262626;
+ border-style: solid;
+ font-size: 1rem;
+ width: 100%;
+ background-color: #f3f4f7;
+ background-image: url("../images/search-icon.svg");
+ background-repeat: no-repeat;
+ background-size: 18px 18px;
+ background-position: 12px 10px;
+ padding-left: 40px;
+ background-color: #ffffff;
+}
+.pytorch-left-menu-search input[type=text]:focus {
+ outline: 0;
+}
+
+@media screen and (min-width: 1201px) {
+ .pytorch-left-menu .pytorch-side-scroll {
+ width: 120%;
+ }
+}
+@media screen and (min-width: 1600px) {
+ .pytorch-left-menu .pytorch-side-scroll {
+ width: 340px;
+ }
+}
+
+.pytorch-right-menu {
+ min-height: 100px;
+ overflow-x: hidden;
+ overflow-y: hidden;
+ left: 0;
+ z-index: 200;
+ padding-top: 0;
+ position: relative;
+}
+@media screen and (min-width: 1201px) {
+ .pytorch-right-menu {
+ width: 100%;
+ }
+ .pytorch-right-menu.scrolling-fixed {
+ position: fixed;
+ top: 45px;
+ left: 83.5%;
+ width: 14%;
+ }
+ .pytorch-right-menu.scrolling-absolute {
+ position: absolute;
+ left: 0;
+ }
+}
+@media screen and (min-width: 1600px) {
+ .pytorch-right-menu {
+ left: 0;
+ width: 380px;
+ }
+ .pytorch-right-menu.scrolling-fixed {
+ position: fixed;
+ top: 45px;
+ left: 1230px;
+ }
+ .pytorch-right-menu.scrolling-absolute {
+ position: absolute;
+ left: 0;
+ }
+}
+
+.pytorch-left-menu ul,
+.pytorch-right-menu ul {
+ list-style-type: none;
+ padding-left: 0;
+ margin-bottom: 2.5rem;
+}
+.pytorch-left-menu > ul,
+.pytorch-right-menu > ul {
+ margin-bottom: 2.5rem;
+}
+.pytorch-left-menu a:link,
+.pytorch-left-menu a:visited,
+.pytorch-left-menu a:hover,
+.pytorch-right-menu a:link,
+.pytorch-right-menu a:visited,
+.pytorch-right-menu a:hover {
+ color: #6c6c6d;
+ font-size: 0.875rem;
+ line-height: 1rem;
+ padding: 0;
+ text-decoration: none;
+}
+.pytorch-left-menu a:link.reference.internal,
+.pytorch-left-menu a:visited.reference.internal,
+.pytorch-left-menu a:hover.reference.internal,
+.pytorch-right-menu a:link.reference.internal,
+.pytorch-right-menu a:visited.reference.internal,
+.pytorch-right-menu a:hover.reference.internal {
+ margin-bottom: 0.3125rem;
+ position: relative;
+}
+.pytorch-left-menu li code,
+.pytorch-right-menu li code {
+ border: none;
+ background: inherit;
+ color: inherit;
+ padding-left: 0;
+ padding-right: 0;
+}
+.pytorch-left-menu li span.toctree-expand,
+.pytorch-right-menu li span.toctree-expand {
+ display: block;
+ float: left;
+ margin-left: -1.2em;
+ font-size: 0.8em;
+ line-height: 1.6em;
+}
+.pytorch-left-menu li.on a, .pytorch-left-menu li.current > a,
+.pytorch-right-menu li.on a,
+.pytorch-right-menu li.current > a {
+ position: relative;
+ border: none;
+}
+.pytorch-left-menu li.on a span.toctree-expand, .pytorch-left-menu li.current > a span.toctree-expand,
+.pytorch-right-menu li.on a span.toctree-expand,
+.pytorch-right-menu li.current > a span.toctree-expand {
+ display: block;
+ font-size: 0.8em;
+ line-height: 1.6em;
+}
+.pytorch-left-menu li.toctree-l1.current > a,
+.pytorch-right-menu li.toctree-l1.current > a {
+ color: #ee4c2c;
+}
+.pytorch-left-menu li.toctree-l1.current > a:before,
+.pytorch-right-menu li.toctree-l1.current > a:before {
+ content: "\2022";
+ display: inline-block;
+ position: absolute;
+ left: -15px;
+ top: -10%;
+ font-size: 1.375rem;
+ color: #ee4c2c;
+}
+@media screen and (min-width: 1201px) {
+ .pytorch-left-menu li.toctree-l1.current > a:before,
+ .pytorch-right-menu li.toctree-l1.current > a:before {
+ left: -20px;
+ }
+}
+.pytorch-left-menu li.toctree-l1.current li.toctree-l2 > ul, .pytorch-left-menu li.toctree-l2.current li.toctree-l3 > ul,
+.pytorch-right-menu li.toctree-l1.current li.toctree-l2 > ul,
+.pytorch-right-menu li.toctree-l2.current li.toctree-l3 > ul {
+ display: none;
+}
+.pytorch-left-menu li.toctree-l1.current li.toctree-l2.current > ul, .pytorch-left-menu li.toctree-l2.current li.toctree-l3.current > ul,
+.pytorch-right-menu li.toctree-l1.current li.toctree-l2.current > ul,
+.pytorch-right-menu li.toctree-l2.current li.toctree-l3.current > ul {
+ display: block;
+}
+.pytorch-left-menu li.toctree-l2.current li.toctree-l3 > a,
+.pytorch-right-menu li.toctree-l2.current li.toctree-l3 > a {
+ display: block;
+}
+.pytorch-left-menu li.toctree-l3,
+.pytorch-right-menu li.toctree-l3 {
+ font-size: 0.9em;
+}
+.pytorch-left-menu li.toctree-l3.current li.toctree-l4 > a,
+.pytorch-right-menu li.toctree-l3.current li.toctree-l4 > a {
+ display: block;
+}
+.pytorch-left-menu li.toctree-l4,
+.pytorch-right-menu li.toctree-l4 {
+ font-size: 0.9em;
+}
+.pytorch-left-menu li.current ul,
+.pytorch-right-menu li.current ul {
+ display: block;
+}
+.pytorch-left-menu li ul,
+.pytorch-right-menu li ul {
+ margin-bottom: 0;
+ display: none;
+}
+.pytorch-left-menu li ul li a,
+.pytorch-right-menu li ul li a {
+ margin-bottom: 0;
+}
+.pytorch-left-menu a,
+.pytorch-right-menu a {
+ display: inline-block;
+ position: relative;
+}
+.pytorch-left-menu a:hover,
+.pytorch-right-menu a:hover {
+ cursor: pointer;
+}
+.pytorch-left-menu a:active,
+.pytorch-right-menu a:active {
+ cursor: pointer;
+}
+
+.pytorch-left-menu ul {
+ padding-left: 0;
+}
+
+.pytorch-right-menu a:link,
+.pytorch-right-menu a:visited,
+.pytorch-right-menu a:hover {
+ color: #6c6c6d;
+}
+.pytorch-right-menu a:link span.pre,
+.pytorch-right-menu a:visited span.pre,
+.pytorch-right-menu a:hover span.pre {
+ color: #6c6c6d;
+}
+.pytorch-right-menu a.reference.internal.expanded:before {
+ content: "-";
+ font-family: monospace;
+ position: absolute;
+ left: -12px;
+}
+.pytorch-right-menu a.reference.internal.not-expanded:before {
+ content: "+";
+ font-family: monospace;
+ position: absolute;
+ left: -12px;
+}
+.pytorch-right-menu li.active > a {
+ color: #ee4c2c;
+}
+.pytorch-right-menu li.active > a span.pre, .pytorch-right-menu li.active > a:before {
+ color: #ee4c2c;
+}
+.pytorch-right-menu li.active > a:after {
+ content: "\2022";
+ color: #e44c2c;
+ display: inline-block;
+ font-size: 1.375rem;
+ left: -17px;
+ position: absolute;
+ top: 1px;
+}
+.pytorch-right-menu .pytorch-side-scroll > ul > li > ul > li {
+ margin-bottom: 0;
+}
+.pytorch-right-menu ul ul {
+ padding-left: 0;
+}
+.pytorch-right-menu ul ul li {
+ padding-left: 0px;
+}
+.pytorch-right-menu ul ul li a.reference.internal {
+ padding-left: 0;
+}
+.pytorch-right-menu ul ul li ul {
+ display: none;
+ padding-left: 10px;
+}
+.pytorch-right-menu ul ul li li a.reference.internal {
+ padding-left: 0;
+}
+.pytorch-right-menu li ul {
+ display: block;
+}
+
+.pytorch-right-menu .pytorch-side-scroll {
+ padding-top: 20px;
+}
+@media screen and (min-width: 1201px) {
+ .pytorch-right-menu .pytorch-side-scroll {
+ width: 120%;
+ }
+}
+@media screen and (min-width: 1600px) {
+ .pytorch-right-menu .pytorch-side-scroll {
+ width: 400px;
+ }
+}
+.pytorch-right-menu .pytorch-side-scroll > ul {
+ padding-left: 10%;
+ padding-right: 10%;
+ margin-bottom: 0;
+}
+@media screen and (min-width: 1600px) {
+ .pytorch-right-menu .pytorch-side-scroll > ul {
+ padding-left: 25px;
+ }
+}
+.pytorch-right-menu .pytorch-side-scroll > ul > li > a.reference.internal {
+ color: #262626;
+ font-weight: 500;
+}
+.pytorch-right-menu .pytorch-side-scroll ul li {
+ position: relative;
+}
+
+#pytorch-right-menu .side-scroll-highlight {
+ color: #ee4c2c;
+}
+
+.header-container {
+ max-width: none;
+ margin-top: 4px;
+}
+@media screen and (min-width: 1201px) {
+ .header-container {
+ margin-top: 0;
+ }
+}
+@media screen and (min-width: 1600px) {
+ .header-container {
+ margin-top: 0;
+ }
+}
+
+.container-fluid.header-holder {
+ padding-right: 0;
+ padding-left: 0;
+}
+
+.header-holder .container {
+ max-width: none;
+ padding-right: 1.875rem;
+ padding-left: 1.875rem;
+}
+@media screen and (min-width: 1201px) {
+ .header-holder .container {
+ padding-right: 1.875rem;
+ padding-left: 1.875rem;
+ }
+}
+
+.header-holder .main-menu {
+ -webkit-box-pack: unset;
+ -ms-flex-pack: unset;
+ justify-content: unset;
+ position: relative;
+}
+
+.header-holder .main-menu .github-icon {
+ background-image: url("../images/pytorch-github.svg");
+ color: white;
+ display: block;
+ width: 33px;
+ height: 33px;
+ position: relative;
+ background-size: 23px 23px;
+ background-position: 5px 4px;
+ background-repeat: no-repeat;
+ border-radius: 25px;
+}
+
+.header-holder .main-menu .github-icon:hover {
+ background-color:#88888833;
+}
+
+@media screen (min-width: 1201px) {
+ .header-holder .main-menu .github-icon {
+ background-image: url("../images/pytorch-github.svg");
+ color: white;
+ display: block;
+ width: 33px;
+ height: 33px;
+ position: relative;
+ background-size: 23px 23px;
+ background-position: 5px 4px;
+ background-repeat: no-repeat;
+ border-radius: 25px;
+ }
+}
+
+@media screen (min-width: 1201px) {
+ .header-holder .main-menu .github-icon:hover {
+ background-color:#88888833;
+ }
+}
+
+.header-holder .main-menu .search-icon {
+ background-image: url("../images/search-icon-black.svg");
+ color: transparent;
+ display: block;
+ width: 33px;
+ height: 33px;
+ position: relative;
+ background-size: 21px 21px;
+ background-position: 6px 5px;
+ background-repeat: no-repeat;
+ border-radius: 25px;
+ cursor pointer
+}
+
+.header-holder .main-menu .search-icon:hover {
+ background-color:#88888833;
+}
+
+
+@media screen and (min-width: 1201px) {
+ .header-holder .main-menu ul {
+ padding-left: 0;
+ margin-left: 26%;
+ }
+}
+@media screen and (min-width: 1600px) {
+ .header-holder .main-menu ul {
+ padding-left: 38px;
+ margin-left: 310px;
+ }
+}
+
+.pytorch-page-level-bar {
+ display: none;
+ -webkit-box-align: center;
+ -ms-flex-align: center;
+ align-items: center;
+ background-color: #ffffff;
+ border-bottom: 1px solid #e2e2e2;
+ width: 100%;
+ z-index: 201;
+}
+@media screen and (min-width: 1201px) {
+ .pytorch-page-level-bar {
+ left: 0;
+ display: -webkit-box;
+ display: -ms-flexbox;
+ display: flex;
+ height: 45px;
+ padding-left: 0;
+ width: 100%;
+ position: absolute;
+ z-index: 1;
+ }
+ .pytorch-page-level-bar.left-menu-is-fixed {
+ position: fixed;
+ top: 0;
+ left: 25%;
+ padding-left: 0;
+ right: 0;
+ width: 75%;
+ }
+}
+@media screen and (min-width: 1600px) {
+ .pytorch-page-level-bar {
+ left: 0;
+ right: 0;
+ width: auto;
+ z-index: 1;
+ }
+ .pytorch-page-level-bar.left-menu-is-fixed {
+ left: 350px;
+ right: 0;
+ width: auto;
+ }
+}
+.pytorch-page-level-bar ul, .pytorch-page-level-bar li {
+ margin: 0;
+}
+
+.pytorch-shortcuts-wrapper {
+ display: none;
+}
+@media screen and (min-width: 1201px) {
+ .pytorch-shortcuts-wrapper {
+ font-size: 0.875rem;
+ float: left;
+ margin-left: 2%;
+ }
+}
+@media screen and (min-width: 1600px) {
+ .pytorch-shortcuts-wrapper {
+ margin-left: 1.875rem;
+ }
+}
+
+.cookie-banner-wrapper {
+ display: none;
+}
+.cookie-banner-wrapper .container {
+ padding-left: 1.875rem;
+ padding-right: 1.875rem;
+ max-width: 1240px;
+}
+.cookie-banner-wrapper.is-visible {
+ display: block;
+ position: fixed;
+ bottom: 0;
+ background-color: #f3f4f7;
+ min-height: 100px;
+ width: 100%;
+ z-index: 401;
+ border-top: 3px solid #ededee;
+}
+.cookie-banner-wrapper .gdpr-notice {
+ color: #6c6c6d;
+ margin-top: 1.5625rem;
+ text-align: left;
+ max-width: 1440px;
+}
+@media screen and (min-width: 768px) {
+ .cookie-banner-wrapper .gdpr-notice {
+ width: 77%;
+ }
+}
+@media (min-width: 768px) and (max-width: 1239px) {
+ .cookie-banner-wrapper .gdpr-notice {
+ width: inherit;
+ }
+}
+.cookie-banner-wrapper .gdpr-notice .cookie-policy-link {
+ color: #343434;
+}
+.cookie-banner-wrapper .close-button {
+ -webkit-appearance: none;
+ -moz-appearance: none;
+ appearance: none;
+ background: transparent;
+ border: 1px solid #f3f4f7;
+ height: 1.3125rem;
+ position: absolute;
+ bottom: 42px;
+ right: 0;
+ top: 0;
+ cursor: pointer;
+ outline: none;
+}
+@media screen and (min-width: 768px) {
+ .cookie-banner-wrapper .close-button {
+ right: 20%;
+ top: inherit;
+ }
+}
+@media (min-width: 768px) and (max-width: 1239px) {
+ .cookie-banner-wrapper .close-button {
+ right: 0;
+ top: 0;
+ }
+}
+
+.main-menu ul li .resources-dropdown a {
+ cursor: default;
+}
+.main-menu ul li .dropdown-menu {
+ border-radius: 0;
+ padding: 0;
+}
+.main-menu ul li .dropdown-menu .dropdown-item {
+ color: #6c6c6d;
+ border-bottom: 1px solid #e2e2e2;
+}
+.main-menu ul li .dropdown-menu .dropdown-item:last-of-type {
+ border-bottom-color: transparent;
+}
+.main-menu ul li .dropdown-menu .dropdown-item:hover {
+ background-color: #e44c2c;
+}
+.main-menu ul li .dropdown-menu .dropdown-item p {
+ font-size: 1rem;
+ color: #979797;
+}
+.main-menu ul li .dropdown-menu a.dropdown-item:hover {
+ color: #ffffff;
+}
+.main-menu ul li .dropdown-menu a.dropdown-item:hover p {
+ color: #ffffff;
+}
+
+.resources-dropdown-menu {
+ left: -75px;
+ width: 300px;
+ display: none;
+ position: absolute;
+ z-index: 1000;
+ display: none;
+ float: left;
+ min-width: 10rem;
+ padding: 0.5rem 0;
+ font-size: 1rem;
+ color: #212529;
+ text-align: left;
+ list-style: none;
+ background-color: #ffffff;
+ background-clip: padding-box;
+ border: 1px solid rgba(0, 0, 0, 0.15);
+ border-radius: 0.25rem;
+}
+
+.resources-dropdown:hover .resources-dropdown-menu {
+ display: block;
+}
+
+.main-menu ul li .resources-dropdown-menu {
+ border-radius: 0;
+ padding: 0;
+}
+.main-menu ul li.active:hover .resources-dropdown-menu {
+ display: block;
+}
+
+.main-menu ul li .resources-dropdown-menu .dropdown-item {
+ color: #262626;
+ border-bottom: 1px solid #e2e2e2;
+}
+
+.resources-dropdown .with-down-orange-arrow {
+ padding-right: 2rem;
+ position: relative;
+ background: url("../images/chevron-down-orange.svg");
+ background-size: 14px 18px;
+ background-position: top 7px right 10px;
+ background-repeat: no-repeat;
+}
+
+.with-down-arrow {
+ padding-right: 2rem;
+ position: relative;
+ background-image: url("../images/chevron-down-black.svg");
+ background-size: 14px 18px;
+ background-position: top 7px right 10px;
+ background-repeat: no-repeat;
+
+}
+
+
+.with-down-arrow a {
+ color: #262626;
+}
+
+.main-menu ul li a.with-down-arrow:hover {
+ color: #262626;
+}
+
+.with-down-arrow:hover {
+ background-repeat: no-repeat;
+}
+
+.header-holder .main-menu ul li .resources-dropdown .doc-dropdown-option {
+ padding-top: 1rem;
+}
+
+.header-holder .main-menu ul li a.nav-dropdown-item {
+ display: block;
+ font-size: 1rem;
+ line-height: 1.3125rem;
+ width: 100%;
+ padding: 0.25rem 1.5rem;
+ clear: both;
+ font-weight: 400;
+ color: #757575;
+ text-align: left;
+ background-color: transparent;
+ border-bottom: 1px solid #e2e2e2;
+ cursor: pointer;
+}
+
+.header-holder .main-menu ul li a.nav-dropdown-item p {
+ margin-bottom: .5rem;
+}
+
+.header-holder .main-menu ul li a.nav-dropdown-item:last-of-type {
+ border-bottom-color: transparent;
+}
+.header-holder .main-menu ul li a.nav-dropdown-item:hover {
+ background-color: #e44c2c;
+ color: white;
+}
+.header-holder .main-menu ul li a.nav-dropdown-item .dropdown-title {
+ font-size: 1.125rem;
+ color: #212529;
+ letter-spacing: 0;
+ line-height: 34px;
+}
+
+.header-holder .main-menu ul li a.nav-dropdown-item:hover .dropdown-title {
+ background-color: #e44c2c;
+ color: white;
+}
+
+/*# sourceMappingURL=theme.css.map */
diff --git a/release/2.5/_static/doctools.js b/release/2.5/_static/doctools.js
new file mode 100644
index 00000000000..527b876ca63
--- /dev/null
+++ b/release/2.5/_static/doctools.js
@@ -0,0 +1,156 @@
+/*
+ * doctools.js
+ * ~~~~~~~~~~~
+ *
+ * Base JavaScript utilities for all Sphinx HTML documentation.
+ *
+ * :copyright: Copyright 2007-2022 by the Sphinx team, see AUTHORS.
+ * :license: BSD, see LICENSE for details.
+ *
+ */
+"use strict";
+
+const BLACKLISTED_KEY_CONTROL_ELEMENTS = new Set([
+ "TEXTAREA",
+ "INPUT",
+ "SELECT",
+ "BUTTON",
+]);
+
+const _ready = (callback) => {
+ if (document.readyState !== "loading") {
+ callback();
+ } else {
+ document.addEventListener("DOMContentLoaded", callback);
+ }
+};
+
+/**
+ * Small JavaScript module for the documentation.
+ */
+const Documentation = {
+ init: () => {
+ Documentation.initDomainIndexTable();
+ Documentation.initOnKeyListeners();
+ },
+
+ /**
+ * i18n support
+ */
+ TRANSLATIONS: {},
+ PLURAL_EXPR: (n) => (n === 1 ? 0 : 1),
+ LOCALE: "unknown",
+
+ // gettext and ngettext don't access this so that the functions
+ // can safely bound to a different name (_ = Documentation.gettext)
+ gettext: (string) => {
+ const translated = Documentation.TRANSLATIONS[string];
+ switch (typeof translated) {
+ case "undefined":
+ return string; // no translation
+ case "string":
+ return translated; // translation exists
+ default:
+ return translated[0]; // (singular, plural) translation tuple exists
+ }
+ },
+
+ ngettext: (singular, plural, n) => {
+ const translated = Documentation.TRANSLATIONS[singular];
+ if (typeof translated !== "undefined")
+ return translated[Documentation.PLURAL_EXPR(n)];
+ return n === 1 ? singular : plural;
+ },
+
+ addTranslations: (catalog) => {
+ Object.assign(Documentation.TRANSLATIONS, catalog.messages);
+ Documentation.PLURAL_EXPR = new Function(
+ "n",
+ `return (${catalog.plural_expr})`
+ );
+ Documentation.LOCALE = catalog.locale;
+ },
+
+ /**
+ * helper function to focus on search bar
+ */
+ focusSearchBar: () => {
+ document.querySelectorAll("input[name=q]")[0]?.focus();
+ },
+
+ /**
+ * Initialise the domain index toggle buttons
+ */
+ initDomainIndexTable: () => {
+ const toggler = (el) => {
+ const idNumber = el.id.substr(7);
+ const toggledRows = document.querySelectorAll(`tr.cg-${idNumber}`);
+ if (el.src.substr(-9) === "minus.png") {
+ el.src = `${el.src.substr(0, el.src.length - 9)}plus.png`;
+ toggledRows.forEach((el) => (el.style.display = "none"));
+ } else {
+ el.src = `${el.src.substr(0, el.src.length - 8)}minus.png`;
+ toggledRows.forEach((el) => (el.style.display = ""));
+ }
+ };
+
+ const togglerElements = document.querySelectorAll("img.toggler");
+ togglerElements.forEach((el) =>
+ el.addEventListener("click", (event) => toggler(event.currentTarget))
+ );
+ togglerElements.forEach((el) => (el.style.display = ""));
+ if (DOCUMENTATION_OPTIONS.COLLAPSE_INDEX) togglerElements.forEach(toggler);
+ },
+
+ initOnKeyListeners: () => {
+ // only install a listener if it is really needed
+ if (
+ !DOCUMENTATION_OPTIONS.NAVIGATION_WITH_KEYS &&
+ !DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS
+ )
+ return;
+
+ document.addEventListener("keydown", (event) => {
+ // bail for input elements
+ if (BLACKLISTED_KEY_CONTROL_ELEMENTS.has(document.activeElement.tagName)) return;
+ // bail with special keys
+ if (event.altKey || event.ctrlKey || event.metaKey) return;
+
+ if (!event.shiftKey) {
+ switch (event.key) {
+ case "ArrowLeft":
+ if (!DOCUMENTATION_OPTIONS.NAVIGATION_WITH_KEYS) break;
+
+ const prevLink = document.querySelector('link[rel="prev"]');
+ if (prevLink && prevLink.href) {
+ window.location.href = prevLink.href;
+ event.preventDefault();
+ }
+ break;
+ case "ArrowRight":
+ if (!DOCUMENTATION_OPTIONS.NAVIGATION_WITH_KEYS) break;
+
+ const nextLink = document.querySelector('link[rel="next"]');
+ if (nextLink && nextLink.href) {
+ window.location.href = nextLink.href;
+ event.preventDefault();
+ }
+ break;
+ }
+ }
+
+ // some keyboard layouts may need Shift to get /
+ switch (event.key) {
+ case "/":
+ if (!DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS) break;
+ Documentation.focusSearchBar();
+ event.preventDefault();
+ }
+ });
+ },
+};
+
+// quick alias for translations
+const _ = Documentation.gettext;
+
+_ready(Documentation.init);
diff --git a/release/2.5/_static/documentation_options.js b/release/2.5/_static/documentation_options.js
new file mode 100644
index 00000000000..ac1f83182f2
--- /dev/null
+++ b/release/2.5/_static/documentation_options.js
@@ -0,0 +1,14 @@
+var DOCUMENTATION_OPTIONS = {
+ URL_ROOT: document.getElementById("documentation_options").getAttribute('data-url_root'),
+ VERSION: 'master',
+ LANGUAGE: 'en',
+ COLLAPSE_INDEX: false,
+ BUILDER: 'html',
+ FILE_SUFFIX: '.html',
+ LINK_SUFFIX: '.html',
+ HAS_SOURCE: true,
+ SOURCELINK_SUFFIX: '.txt',
+ NAVIGATION_WITH_KEYS: false,
+ SHOW_SEARCH_SUMMARY: true,
+ ENABLE_SEARCH_SHORTCUTS: true,
+};
\ No newline at end of file
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+ * https://jquery.com/
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+ * Includes Sizzle.js
+ * https://sizzlejs.com/
+ *
+ * Copyright OpenJS Foundation and other contributors
+ * Released under the MIT license
+ * https://jquery.org/license
+ *
+ * Date: 2021-03-02T17:08Z
+ */
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+
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+ // For environments that do not have a `window` with a `document`
+ // (such as Node.js), expose a factory as module.exports.
+ // This accentuates the need for the creation of a real `window`.
+ // e.g. var jQuery = require("jquery")(window);
+ // See ticket #14549 for more info.
+ module.exports = global.document ?
+ factory( global, true ) :
+ function( w ) {
+ if ( !w.document ) {
+ throw new Error( "jQuery requires a window with a document" );
+ }
+ return factory( w );
+ };
+ } else {
+ factory( global );
+ }
+
+// Pass this if window is not defined yet
+} )( typeof window !== "undefined" ? window : this, function( window, noGlobal ) {
+
+// Edge <= 12 - 13+, Firefox <=18 - 45+, IE 10 - 11, Safari 5.1 - 9+, iOS 6 - 9.1
+// throw exceptions when non-strict code (e.g., ASP.NET 4.5) accesses strict mode
+// arguments.callee.caller (trac-13335). But as of jQuery 3.0 (2016), strict mode should be common
+// enough that all such attempts are guarded in a try block.
+"use strict";
+
+var arr = [];
+
+var getProto = Object.getPrototypeOf;
+
+var slice = arr.slice;
+
+var flat = arr.flat ? function( array ) {
+ return arr.flat.call( array );
+} : function( array ) {
+ return arr.concat.apply( [], array );
+};
+
+
+var push = arr.push;
+
+var indexOf = arr.indexOf;
+
+var class2type = {};
+
+var toString = class2type.toString;
+
+var hasOwn = class2type.hasOwnProperty;
+
+var fnToString = hasOwn.toString;
+
+var ObjectFunctionString = fnToString.call( Object );
+
+var support = {};
+
+var isFunction = function isFunction( obj ) {
+
+ // Support: Chrome <=57, Firefox <=52
+ // In some browsers, typeof returns "function" for HTML
+
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+
+ Source code for torch_xla.torch_xla
+import sys
+import collections
+import contextlib
+import functools
+import uuid
+from typing import Any, Callable, List, Optional, Tuple
+import weakref
+
+import torch
+import torch.distributed as dist
+import torch_xla
+import torch_xla.core.xla_model as xm
+import torch_xla.core.xla_env_vars as xenv
+import torch_xla.distributed.xla_multiprocessing as xmp
+import torch_xla.runtime as xr
+import torch_xla.utils.utils as xu
+
+
+[docs]def device(index: int = None) -> torch.device:
+ """Returns a given instance of an XLA device.
+
+ If SPMD enables, returns a virtual device that wraps all devices available
+ to this process.
+
+ Args:
+ index: index of the XLA device to be returned. Corresponds to index in
+ `torch_xla.devices()`.
+
+ Returns:
+ An XLA `torch.device`.
+ """
+
+ return xm.xla_device(index)
+
+
+[docs]def devices() -> List[torch.device]:
+ """Returns all devices available in the current process.
+
+ Returns:
+ A list of XLA `torch.devices`.
+ """
+
+ return [torch.device(d) for d in xm.get_xla_supported_devices()]
+
+
+def real_devices() -> List[str]:
+ """Returns local XLA device types and indices.
+
+ Returns:
+ A list strings representing the XLA devices available in the current
+ process, e.g. `['TPU:0', 'TPU:1', ...]`.
+ """
+
+ return torch_xla._XLAC._xla_real_devices()
+
+
+[docs]def device_count() -> int:
+ """Returns number of addressable devices in the current process."""
+ return len(real_devices())
+
+
+[docs]def sync(wait: bool = False):
+ """Launches all pending graph operations.
+
+ Args:
+ wait (bool): whether to block the current process until the execution finished.
+
+ """
+ torch_xla._XLAC._xla_step_marker(
+ torch_xla._XLAC._xla_get_default_device(),
+ [],
+ wait=wait,
+ )
+ devctx = xm._run_step_closures()
+ torch_xla._XLAC._set_all_reduce_token(devctx.device, None)
+
+
+def step():
+ """Wraps code that should be dispatched to the runtime.
+
+ Experimental: `xla.step` is still a work in progress. Some code that currently
+ works with `xla.step` but does not follow best practices will become errors in
+ future releases. See https://github.com/pytorch/xla/issues/6751 for context.
+ """
+ return compile()
+
+
+# Keeps track of the alive functions. This allow us to remove session entries in the
+# C++ side for functions that are no longer alive.
+_compiled_id_to_functions_ref = weakref.WeakValueDictionary()
+
+
+[docs]def compile(
+ f: Optional[Callable] = None,
+ full_graph: Optional[bool] = False,
+ name: Optional[str] = None,
+ num_different_graphs_allowed: Optional[int] = None,
+):
+ """
+ Optimizes given model/function using torch_xla's LazyTensor tracing mode.
+ PyTorch/XLA will trace the given function with given inputs and then generate
+ graphs to represent the pytorch operations happens within this function. This
+ graph will be compiled by the XLA and executed on the accelerator(decided by the
+ tensor's device). Eager mode will be disabled for the compiled region of the funciton.
+
+ Args:
+ model (Callable): Module/function to optimize, if not passed this function will
+ act as a context manager.
+ full_graph (Optional[bool]): Whether this compile should generate a single graph. If set to True
+ and multiple graphs will be generated torch_xla will throw an error with debug info
+ and exit.
+ name (Optional[name]): Name of the compiled program. The name of the function `f` will be used
+ if not specified. This name will be used in the `PT_XLA_DEBUG` messages as well as HLO/IR dump
+ file.
+ num_different_graphs_allowed (Optional[int]): number of different traced graphs of the given
+ model/function that we are allowed to have. An error will be raised in case this limit
+ is exceeded.
+
+ Example::
+
+ # usage 1
+ @torch_xla.compile()
+ def foo(x):
+ return torch.sin(x) + torch.cos(x)
+
+ def foo2(x):
+ return torch.sin(x) + torch.cos(x)
+ # usage 2
+ compiled_foo2 = torch_xla.compile(foo2)
+
+ # usage 3
+ with torch_xla.compile():
+ res = foo2(x)
+ """
+ if name is None and f is not None:
+ if hasattr(f, '__name__'):
+ name = f.__name__
+ elif hasattr(f, '__str__'):
+ name = f.__str__()
+
+ if f is not None:
+ current_id = f"{name}_{id(f)}"
+ else:
+ current_id = str(uuid.uuid4())
+
+ # Check whether the function/module that corresponds with current_id is still alive. If it's not,
+ # we can remove it from the session's map in the C++ side, so we can start a fresh session.
+ #
+ # This solves the issue where there are 2 different local-scoped functions with the same name.
+ # Since they are local-scoped, they might end-up with the same id. And, since they have the same
+ # name, their current_id will be the same, even though they are different functions.
+ #
+ # This issue was observed when running test_dynamic_shape_detector.py.
+ if current_id not in _compiled_id_to_functions_ref:
+ torch_xla._XLAC._dynamic_shape_detector_remove_session(current_id)
+
+ if f is not None:
+ _compiled_id_to_functions_ref[current_id] = f
+
+ def _clear_pending_ops_before_compile():
+ sync()
+
+ @contextlib.contextmanager
+ def _compile():
+ saved_eager_mode_status = torch_xla._XLAC._get_use_eager_mode()
+ saved_allow_execution = torch_xla._XLAC._get_allow_execution()
+ saved_current_graph_name = torch_xla._XLAC._get_current_graph_name()
+ torch_xla._XLAC._set_use_eager_mode(False)
+ if name is not None:
+ torch_xla._XLAC._set_current_graph_name(name + '_clear_pending')
+ # Clear pending operations
+ _clear_pending_ops_before_compile()
+
+ if name is not None:
+ torch_xla._XLAC._set_current_graph_name(name)
+
+ # if full_graph sets to true execution can not happen before the sync below
+ torch_xla._XLAC._set_allow_execution(not full_graph)
+
+ if num_different_graphs_allowed is not None:
+ torch_xla._XLAC._dynamic_shape_detector_set_max_num_different_graphs_allowed(
+ num_different_graphs_allowed)
+ torch_xla._XLAC._dynamic_shape_detector_start_session(current_id)
+
+ try:
+ yield
+ finally:
+ torch_xla._XLAC._set_allow_execution(saved_allow_execution)
+ if num_different_graphs_allowed is not None:
+ torch_xla._XLAC._dynamic_shape_detector_end_session()
+ # Collect the traced graph after running the target function and
+ # execute the graph.
+ sync()
+ torch_xla._XLAC._set_use_eager_mode(saved_eager_mode_status)
+ torch_xla._XLAC._set_current_graph_name(saved_current_graph_name)
+
+ return _compile() if f is None else _compile()(f)
+
+
+[docs]def manual_seed(seed, device=None):
+ """Set the seed for generating random numbers for the current XLA device.
+
+ Args:
+ seed (integer): The state to be set.
+ device (torch.device, optional): The device where the RNG state needs to be set.
+ If missing the default device seed will be set.
+ """
+ xm.set_rng_state(seed, device)
+
+
+# TODO(wcromar): Update args to type ParamSpec.
+def launch(
+ fn: Callable,
+ args: Tuple = (),
+ start_method: str = 'spawn',
+ debug_single_process: bool = False,
+):
+ """ Entry to launch multiprocess.
+
+ Raises:
+ NotImplementedError: SPMD is not supported yet.
+ """
+ if xr.is_spmd():
+ # TODO(piz): SPMD is specified differently from mp. Skip for now.
+ raise NotImplementedError(
+ 'launch function does not support SPMD at this time')
+
+ nprocs = 1 if debug_single_process else None
+
+ if dist.is_torchelastic_launched():
+ fn(xu.getenv_as(xenv.LOCAL_RANK, int), *args)
+ else:
+ xmp.spawn(fn, args=args, nprocs=nprocs, start_method=start_method)
+
+
+
+
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\ No newline at end of file
diff --git a/release/2.5/_sources/debug.rst.txt b/release/2.5/_sources/debug.rst.txt
new file mode 100644
index 00000000000..7c6a6eee671
--- /dev/null
+++ b/release/2.5/_sources/debug.rst.txt
@@ -0,0 +1 @@
+.. mdinclude:: ../../TROUBLESHOOTING.md
\ No newline at end of file
diff --git a/release/2.5/_sources/eager_mode.rst.txt b/release/2.5/_sources/eager_mode.rst.txt
new file mode 100644
index 00000000000..05e7d359e1d
--- /dev/null
+++ b/release/2.5/_sources/eager_mode.rst.txt
@@ -0,0 +1 @@
+.. mdinclude:: ../eager.md
\ No newline at end of file
diff --git a/release/2.5/_sources/gpu.rst.txt b/release/2.5/_sources/gpu.rst.txt
new file mode 100644
index 00000000000..79d8385467a
--- /dev/null
+++ b/release/2.5/_sources/gpu.rst.txt
@@ -0,0 +1 @@
+.. mdinclude:: ../gpu.md
\ No newline at end of file
diff --git a/release/2.5/_sources/index.rst.txt b/release/2.5/_sources/index.rst.txt
new file mode 100644
index 00000000000..edd6bcc5372
--- /dev/null
+++ b/release/2.5/_sources/index.rst.txt
@@ -0,0 +1,108 @@
+:github_url: https://github.com/pytorch/xla
+
+PyTorch/XLA documentation
+===================================
+PyTorch/XLA is a Python package that uses the XLA deep learning compiler to connect the PyTorch deep learning framework and Cloud TPUs.
+
+.. toctree::
+ :hidden:
+
+ self
+
+.. toctree::
+ :glob:
+ :maxdepth: 1
+ :caption: Docs
+
+ *
+
+.. mdinclude:: ../../API_GUIDE.md
+
+PyTorch/XLA API
+==================================
+
+torch_xla
+----------------------------------
+.. automodule:: torch_xla
+.. autofunction:: device
+.. autofunction:: devices
+.. autofunction:: device_count
+.. autofunction:: sync
+.. autofunction:: compile
+.. autofunction:: manual_seed
+
+runtime
+----------------------------------
+.. automodule:: torch_xla.runtime
+.. autofunction:: device_type
+.. autofunction:: local_process_count
+.. autofunction:: local_device_count
+.. autofunction:: addressable_device_count
+.. autofunction:: global_device_count
+.. autofunction:: global_runtime_device_count
+.. autofunction:: world_size
+.. autofunction:: global_ordinal
+.. autofunction:: local_ordinal
+.. autofunction:: get_master_ip
+.. autofunction:: use_spmd
+.. autofunction:: is_spmd
+.. autofunction:: initialize_cache
+
+
+xla_model
+----------------------------------
+
+.. automodule:: torch_xla.core.xla_model
+.. autofunction:: xla_device
+.. autofunction:: xla_device_hw
+.. autofunction:: is_master_ordinal
+.. autofunction:: all_reduce
+.. autofunction:: all_gather
+.. autofunction:: all_to_all
+.. autofunction:: add_step_closure
+.. autofunction:: wait_device_ops
+.. autofunction:: optimizer_step
+.. autofunction:: save
+.. autofunction:: rendezvous
+.. autofunction:: mesh_reduce
+.. autofunction:: set_rng_state
+.. autofunction:: get_rng_state
+.. autofunction:: get_memory_info
+.. autofunction:: get_stablehlo
+.. autofunction:: get_stablehlo_bytecode
+
+distributed
+----------------------------------
+
+.. automodule:: torch_xla.distributed.parallel_loader
+.. autoclass:: MpDeviceLoader
+
+.. automodule:: torch_xla.distributed.xla_multiprocessing
+.. autofunction:: spawn
+
+spmd
+----------------------------------
+.. automodule:: torch_xla.distributed.spmd
+.. autofunction:: mark_sharding
+.. autofunction:: clear_sharding
+.. autofunction:: set_global_mesh
+.. autofunction:: get_global_mesh
+.. autofunction:: get_1d_mesh
+.. autoclass:: Mesh
+.. autoclass:: HybridMesh
+
+experimental
+----------------------------------
+.. automodule:: torch_xla.experimental
+.. autofunction:: eager_mode
+
+debug
+----------------------------------
+
+.. automodule:: torch_xla.debug.metrics
+.. autofunction:: metrics_report
+.. autofunction:: short_metrics_report
+.. autofunction:: counter_names
+.. autofunction:: counter_value
+.. autofunction:: metric_names
+.. autofunction:: metric_data
diff --git a/release/2.5/_sources/multi_process_distributed.rst.txt b/release/2.5/_sources/multi_process_distributed.rst.txt
new file mode 100644
index 00000000000..f8f25e5c05a
--- /dev/null
+++ b/release/2.5/_sources/multi_process_distributed.rst.txt
@@ -0,0 +1,2 @@
+.. mdinclude:: ../ddp.md
+.. mdinclude:: ../fsdp.md
\ No newline at end of file
diff --git a/release/2.5/_sources/notes/source_of_recompilation.md.txt b/release/2.5/_sources/notes/source_of_recompilation.md.txt
new file mode 100644
index 00000000000..bb253cb5fc4
--- /dev/null
+++ b/release/2.5/_sources/notes/source_of_recompilation.md.txt
@@ -0,0 +1,176 @@
+# Source of recompilations in torch_xla
+
+## Let’s first start with some facts/constraints:
+
+1. Graph compilations in XLA are pretty expensive.
+2. XLA handles static shape only. In other words, even for the same IR graph, XLA recompiles when input shape changes.
+3. Recompilations hurts torch_xla perf a lot when it happens, and it’s hard to understand and debug from a normal python user POV.
+
+Often when recompilation happens we say we just need dynamic shape support and then rest assured that when dynamic shape is supported in the future, all the recompilations will be magically gone. But this is not true, XLA now has pretty good bounded dynamic shapes coverage already, but we still see recompilations and they are expected.
+
+***This doc aims to provide a detailed explanation of a few common sources of recompilations, and what do we need to get rid of them. It will mainly focus on explaining the problem to beginners without any context. To make it easy to understand, the “solutions” proposed here may rely on impractical assumptions.* **
+
+## #1. From input dataset.
+
+Yes it’s pretty common that input dataset contains examples with different shapes, e.g. sentences with varying length or images with different sizes. Without normalization, it’ll cause recompilation for every new input shape.
+
+Tensorflow graph mode users are more used to do padding/bucketization (`tf.pad`) to normalize input shapes to one or a few buckets. But this is kinda anti-pattern for PyTorch eager frontend users (which is the same user lazy tensor frontend is trying to target) since different input shapes just doesn’t matter for eager CPU/CUDA backend.
+
+**Proposed workaround:** okay now let’s say we can work around this problem by teaching our users to do padding/bucketization (it’s hard in practice :P). What’s next?
+
+## #2. From operator output
+
+There are certain operators semantically are data-dependent and produce dynamic shape outputs: e.g. `torch.nonzero` returns indices of nonzero elements in its input tensor. So even your input tensors to this operator always have the same shape, it might produce different shape outputs and cause recompilations.
+
+### 2.1 Bounded dynamic shape can fix the case when you use the tensor with dynamic shape as a Tensor, without querying its real dimension.
+
+**Proposed workaround:** let’s say now XLA supports bounded dynamic shape for all operators, is it good enough?
+
+* by bounded dynamic shape it means we can pad the tensor to a theoretical max, trading more memory usage for less recompilation/faster speed.
+
+Well, sort of. Let’s see the following example:
+
+
+```
+a = torch.tensor([1, 2, 0, 1, 3], device='xla')
+b = torch.nonzero(a)
+c = b * 2
+d = c + 1
+print(torch_xla._XLAC._get_xla_tensors_text([d]))
+```
+
+In the example above every node below `b` in the graph (namely `c, d` and everything depend on them) will have dynamic shape, it’s pretty obvious that `b` has dynamic shape in dimension 0 as shown below:
+
+
+```
+ %9 = (s64[<=5,1]{1,0}, s64[]) aten::nonzero(%8), num_outputs=2 # b
+ %10 = s64[5,1]{1,0} aten::mul(%9.0, %3) # c
+ %11 = s64[5,1]{1,0} aten::add(%10, %2), ROOT=0 # d
+```
+
+Although it's not shown directly in the graph, `c & d` indeed also have dynamic shape (in other words, [5, 1] is just padded shape and it's masked).
+
+```
+print(torch_xla._XLAC._get_xla_tensor_dimension_size(d, 0)) # prints 4 instead of 5
+```
+
+You can see that in this case as long as the input tensor `a` has shape `[5]` we only compile the graph once. Bounded dynamic shape support helped!
+
+### 2.2 what if real dimension is queried on a tensor with dynamic shape?
+
+This is actually pretty commonly used since not all PyTorch computation are done in the form of Tensors.
+
+For example, `tensor.size()` in PyTorch returns a tuple of ints instead of a Tensor of dtype=int. When `tensor` is a dynamic shape tensor, this op basically forces XLA to cut the graph and evaluate so that we can return the correct scalar (otherwise it’ll just return the padded shape which is wrong).
+
+What’s made it worse is that many PyTorch takes scalar inputs as well. After you do `s = tensor.size(0)` and use `s` in other operators it also becomes a dynamic source. In this case we probably know how to pad it and its upper bound, but we cannot do it since it’s not even a Tensor!
+
+
+```
+ a = torch.tensor([1, 2, 0, 1, 3], device='xla')
+ b = torch.nonzero(a)
+ s = a.size(0) # evaluation happens! nit: we use size() for simplicity, the actual API is _get_xla_tensor_dimension_size.
+ c = torch.rand(s, device='xla') # c can be of any shape between [0, 5] which causes more recompilations!
+ d = c + 1
+```
+
+So this one is actually hard to solve without PyTorch frontend’s help. What do we need?
+
+In short, we need a Tensor world!
+
+For example,
+
+* `tensor.size()` should return a Tensor so that it can be a Tensor with dynamic shape and kept in the graph without early evaluation.
+* Tensor accessor, e.g. for 2D tensor, `tensor[0][0]` now returns a value but this need to return a tensor as well.
+* Implicitly this means all operators currently taking int/float/double as input need a Tensor overload as well. THIS IS A BIG ASK as it can easily explode our operator set.
+ * It’s easier if we can make scalar to Tensor conversion really cheap so that we can only care about the Tensor overload.
+ * In practice not all ops takes scalars from previous computation, so we’ve been adding Tensor variants by ad-hoc requests.
+ * This is also a common ask from tracing base approaches I think.
+
+Okay now that we assume every op in PyTorch has a Tensor verison we need, are we done?
+
+## #3. From control flow
+
+No! We actually only solved the problem without data dependent control flow...
+
+See the example below:
+
+```
+if x[0][0] == 3:
+ bla
+else:
+ blabla
+```
+
+Even if `x[0][0]` was a Tensor, we need to execute/materialize its value for python interpreter to proceed. And different branch choices in multiple control flows combined means we have a lot of graph to compile as well!
+
+For now we just have no way to fix this. To fix it we need to lower the control flow from python to graph! Without too much thinking in implementation we can do this in two ways:
+
+* ask users to explicitly use a control flow op instead of python if/else/while/for. This is currently supported as [customized API in torch_xla](https://github.com/pytorch/xla/blob/master/torch_xla/core/xla_builder.py#L563-L574) but not widely adopted in users’ code. (python users are used to if/else/for and it’s hard to switch them to a uglier API unless there’s a huge perf win).
+* parse python source. code to get the control flow statement automatically. This is like Torchscript and somehow merge the torchscripted graph into the lazily trace graph properly (including shape info etc). I haven’t thought through the steps of how to implement this indeed :P
+
+But either solution above requires non-trivial amount of effort, either on user side or on the framework side. That’s why we currently just take the hit of early evaluation & multiple compilations as a short term solution given the bandwidth we have.
+
+Okay so now we assume that also have control flow lowered in the graph automagically, are we gold?
+
+YES! Now you have your whole computation represented in a graph of Tensor operations, including control flow so that compilers can now consume and do their smart tricks! But tbh at this point your program is no longer very PyTorch-y.
+
+
+## Conclusion:
+
+There’re actually multiple sources of recompilation and bounded dynamic shape support cannot solve all of them. The proposed workarounds in this doc are definitely sometimes impractical, and there might be better ways to fix each source properly that I’m totally unaware of. But I hope as we keep smashing our way to an ideal lazy tensor stack in this doc, it’s now easier for you understand what’re the remaining blockers ahead of us.
+
+
+## Appendix:
+
+1. NNC uses symbolic shapes, does that help?
+
+Yes but partially. By having symbolic shape, your compilation optimization no longer requires concrete shape values. In other words your generated kernel are more general than XLA’s static shape ones.
+
+And which exactly problem does it help?
+
+It helps with cases like #1 and #2.1.
+
+
+```
+shape [3, 5] -> add -> transpose -> ... -> mul
+shape [6, 2] -> add -> transpose -> ... -> mul
+
+# with symbolic shape
+shape [x, y] -> add -> transpose -> ... -> mul
+```
+
+With symbolic shape your generated kernel doesn’t recompile as XLA does with static shapes.
+
+XLA solves this problem in the other way, by using padding/bucketization (for #1) and bounded dynamic shape (for #2.1).
+
+Brian Hirsh(@bdhirsh) asked some really good questions in the comment, moving here to make them more visible:
+
+2. Is it worth sticking a TORCH_WARN in the XLA kernels of ops that produce data-dependent output shapes?
+
+Yea torch_warn is useful in telling users "hey your program won't run blazing fast". But for these data dependent ops, there isn't an easy rewrite for them unless users change the logic in their model. (another example is torch.unique())
+
+3. How ops like nonzero impact our ability to devirtualize sizes()? If we want to devirtualize sizes(), we’ll need to be able to eagerly compute sizes for each op - won’t that mean we’re forced to evaluate the graph every time we hit an op like nonzero? Vs. right now, it sounds like we don't actually force an evaluation when a user calls nonzero()?
+
+Yea great question! So in the current form it’s not a hard blocker since size() on XLA Tensors doesn’t carry source of truth size information. As shown in the example, the source of truth lives in IRValue and can be retrieved by `_get_xla_tensor_dimension_size` only. So if we decide to devirtualize size it’ll just enforce this discrepancy.
+
+As a followup if we have `size()` return Tensor instead of values as mentioned in the proposed workarounds above. In that case size() won’t be able to devirtualize since it becomes an operator (taking in Tensor and produce Tensor, have different implementations for different backends.)
+
+4. If I, e.g. call `torch.add(input, 1)` in a loop, where input varies in size from 1-1000, normally we would have to compile 1000 different graphs - but with dynamic shapes, it sounds like XLA will internally be able to generate a single graph where it says “use this graph if the input size is <=1000”. My question is: is “dynamic shape” a property of just the graph? Or of both the graph and the input. I.e. if my code were instead calling `x = torch.add(input, 1); x.sizes()` in a loop, does x have a dynamic shape at this point, meaning we’d need to run the graph to get the sizes? Or are we able to make it an eagerly computed property even in the presence of graphs with dynamic shapes.
+
+Yea in this case you'll compile 1000 different graphs. Dynamic shapes means its input has dynamic dimension in it. So when you query `x.sizes()` (currently need use get_dimention_size to get the correct size) it'll trigger *execution* (since the size didn't change it doesn't trigger recompilation). Without the line accessing size, it won't trigger any recompilation/execution when input has dynamic dimension.
+
+5. Would an alternative of making control flow available in the graph be just to come up with a way to ensure that XLA graphs don't include control flow? i.e. if we have a model with a single conditional in the middle, then get XLA to produce 3 graphs: 1 for everything before the conditional, 1 for the if branch, and 1 for the else branch. That would mean you don't get the exponential blowup of new graphs for every combination of paths taken, but (a) the graphs are smaller and provide fewer optimization opportunities, and (b) it would probably be pretty non-trivial to get XLA to recognize where a conditional path is taken.
+
+Great point! So if we could break them up into smaller graphs it's indeed feasible. But in practice this pattern is annoying:
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+```
+y =
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