Bump version to 0.21

composer/_version.py

@@ -3,4 +3,4 @@
 
 """The Composer Version."""
 
-__version__ = '0.20.1'
+__version__ = '0.21.0'

composer/core/state.py

@@ -44,7 +44,6 @@
     is_model_deepspeed,
     reproducibility,
 )
-from composer.utils.warnings import VersionedDeprecationWarning
 
 if TYPE_CHECKING:
     import deepspeed
@@ -790,16 +789,6 @@ def fsdp_state_dict_type(self):
     def fsdp_sharded_state_dict_enabled(self):
         return self.fsdp_config is not None and self.fsdp_enabled and self.fsdp_state_dict_type == 'sharded'
 
-    @property
-    def fsdp_elastic_sharded_enabled(self):
-        warnings.warn(
-            VersionedDeprecationWarning(
-                'state.fsdp_elastic_sharded_enabled is deprecated.',
-                remove_version='0.21.0',
-            ),
-        )
-        return self.fsdp_sharded_state_dict_enabled
-
     @property
     def fsdp_device_mesh(self):
         if self.fsdp_enabled:

composer/core/time.py

@@ -19,12 +19,10 @@
 
 import datetime
 import re
-import warnings
 from typing import Any, Dict, Generic, Optional, TypeVar, Union, cast
 
 from composer.core.serializable import Serializable
 from composer.utils import StringEnum
-from composer.utils.warnings import VersionedDeprecationWarning
 
 __all__ = ['TimeUnit', 'Time', 'Timestamp', 'ensure_time']
 
@@ -540,18 +538,6 @@ def state_dict(self) -> Dict[str, Any]:
             'batch_wct': self.batch_wct,
         }
 
-    def get_state(self) -> Dict[str, Union[Time[int], datetime.timedelta]]:
-        """Returns all values of the timestamp object in a dictionary.
-
-        Returns:
-            Dict[str, Union[Time[int], datetime.timedelta]]: All values of the timestamp object.
-        """
-        warnings.warn(
-            VersionedDeprecationWarning('core.time.Timestamp.get_state is deprecated.', remove_version='0.21.0'),
-        )
-
-        return self.state_dict()
-
     def load_state_dict(self, state: Dict[str, Any]) -> None:
         self._epoch = Time(state['epoch'], TimeUnit.EPOCH)
         self._batch = Time(state['batch'], TimeUnit.BATCH)

composer/metrics/nlp.py

@@ -247,14 +247,15 @@ def update(
     ):
         """Abstract interface for computing an in-context learning metrics.
 
-        The `output_logits` argument is deprecated and will be removed in v0.21 while it's functionality will
+        The `output_logits` argument is deprecated and will be removed in v0.22 while it's functionality will
         be moved to `outputs`.
 
         Args:
             batch (dict): Batch must consist minimally of `input_ids` as well as any other structure needed
                 to compute the metric.
             output_logits (torch.Tensor): The model outputs evaluated on the batch `input_ids`
             labels (torch.Tensor): The correct outputs.
+            outputs (torch.Tensor): The model outputs evaluated on the batch `input_ids`.
 
         Raises:
             NotImplementedError: Abstract method must be implemented by subclasses

composer/models/huggingface.py

@@ -513,7 +513,7 @@ def eval_forward(self, batch, outputs: Optional[Any] = None):
                 warnings.warn(
                     VersionedDeprecationWarning(
                         '`generation_length` has been deprecated in favor of passing `max_new_tokens` directly into `generation_kwargs`.',
-                        remove_version='0.21.0',
+                        remove_version='0.22.0',
                     ),
                 )
                 if 'generation_kwargs' in batch:

docker/README.md

@@ -15,8 +15,8 @@ all dependencies for both NLP and Vision models. They are built on top of the
 <!-- BEGIN_COMPOSER_BUILD_MATRIX -->
 | Composer Version   | CUDA Support   | Docker Tag                                                     |
 |--------------------|----------------|----------------------------------------------------------------|
-| 0.20.1             | Yes            | `mosaicml/composer:latest`, `mosaicml/composer:0.20.1`         |
-| 0.20.1             | No             | `mosaicml/composer:latest_cpu`, `mosaicml/composer:0.20.1_cpu` |
+| 0.21.0             | Yes            | `mosaicml/composer:latest`, `mosaicml/composer:0.21.0`         |
+| 0.21.0             | No             | `mosaicml/composer:latest_cpu`, `mosaicml/composer:0.21.0_cpu` |
 <!-- END_COMPOSER_BUILD_MATRIX -->
 
 **Note**: For a lightweight installation, we recommended using a [MosaicML PyTorch Image](#pytorch-images) and manually
@@ -30,8 +30,6 @@ To install composer, once inside the image, run `pip install mosaicml`.
 <!-- BEGIN_PYTORCH_BUILD_MATRIX -->
 | Linux Distro   | Flavor   | PyTorch Version   | CUDA Version        | Python Version   | Docker Tags                                                                              |
 |----------------|----------|-------------------|---------------------|------------------|------------------------------------------------------------------------------------------|
-| Ubuntu 20.04   | Base     | 2.3.0             | 12.1.1 (Infiniband) | 3.11             | `mosaicml/pytorch:2.3.0_cu121-nightly20240110-python3.11-ubuntu20.04`                    |
-| Ubuntu 20.04   | Base     | 2.3.0             | 12.1.1 (EFA)        | 3.11             | `mosaicml/pytorch:2.3.0_cu121-nightly20240110-python3.11-ubuntu20.04-aws`                |
 | Ubuntu 20.04   | Base     | 2.2.1             | 12.1.1 (Infiniband) | 3.11             | `mosaicml/pytorch:2.2.1_cu121-python3.11-ubuntu20.04`                                    |
 | Ubuntu 20.04   | Base     | 2.2.1             | 12.1.1 (EFA)        | 3.11             | `mosaicml/pytorch:2.2.1_cu121-python3.11-ubuntu20.04-aws`                                |
 | Ubuntu 20.04   | Base     | 2.2.1             | cpu                 | 3.11             | `mosaicml/pytorch:2.2.1_cpu-python3.11-ubuntu20.04`                                      |

docker/build_matrix.yaml

@@ -190,65 +190,11 @@
   - mosaicml/pytorch:2.0.1_cpu-python3.10-ubuntu20.04
   TARGET: pytorch_stage
   TORCHVISION_VERSION: 0.15.2
-- AWS_OFI_NCCL_VERSION: v1.7.4-aws
-  BASE_IMAGE: nvidia/cuda:12.1.1-cudnn8-devel-ubuntu20.04
-  CUDA_VERSION: 12.1.1
-  IMAGE_NAME: torch-nightly-2-3-0-20240110-cu121-python3-11-aws
-  MOFED_VERSION: ''
-  NVIDIA_REQUIRE_CUDA_OVERRIDE: cuda>=12.1 brand=tesla,driver>=450,driver<451 brand=tesla,driver>=470,driver<471
-    brand=unknown,driver>=470,driver<471 brand=nvidia,driver>=470,driver<471 brand=nvidiartx,driver>=470,driver<471
-    brand=geforce,driver>=470,driver<471 brand=geforcertx,driver>=470,driver<471 brand=quadro,driver>=470,driver<471
-    brand=quadrortx,driver>=470,driver<471 brand=titan,driver>=470,driver<471 brand=titanrtx,driver>=470,driver<471
-    brand=tesla,driver>=510,driver<511 brand=unknown,driver>=510,driver<511 brand=nvidia,driver>=510,driver<511
-    brand=nvidiartx,driver>=510,driver<511 brand=geforce,driver>=510,driver<511 brand=geforcertx,driver>=510,driver<511
-    brand=quadro,driver>=510,driver<511 brand=quadrortx,driver>=510,driver<511 brand=titan,driver>=510,driver<511
-    brand=titanrtx,driver>=510,driver<511 brand=tesla,driver>=515,driver<516 brand=unknown,driver>=515,driver<516
-    brand=nvidia,driver>=515,driver<516 brand=nvidiartx,driver>=515,driver<516 brand=geforce,driver>=515,driver<516
-    brand=geforcertx,driver>=515,driver<516 brand=quadro,driver>=515,driver<516 brand=quadrortx,driver>=515,driver<516
-    brand=titan,driver>=515,driver<516 brand=titanrtx,driver>=515,driver<516 brand=tesla,driver>=525,driver<526
-    brand=unknown,driver>=525,driver<526 brand=nvidia,driver>=525,driver<526 brand=nvidiartx,driver>=525,driver<526
-    brand=geforce,driver>=525,driver<526 brand=geforcertx,driver>=525,driver<526 brand=quadro,driver>=525,driver<526
-    brand=quadrortx,driver>=525,driver<526 brand=titan,driver>=525,driver<526 brand=titanrtx,driver>=525,driver<526
-  PYTHON_VERSION: '3.11'
-  PYTORCH_NIGHTLY_URL: https://download.pytorch.org/whl/nightly/cu121
-  PYTORCH_NIGHTLY_VERSION: dev20240110+cu121
-  PYTORCH_VERSION: 2.3.0
-  TAGS:
-  - mosaicml/pytorch:2.3.0_cu121-nightly20240110-python3.11-ubuntu20.04-aws
-  TARGET: pytorch_stage
-  TORCHVISION_VERSION: 0.18.0
-- AWS_OFI_NCCL_VERSION: ''
-  BASE_IMAGE: nvidia/cuda:12.1.1-cudnn8-devel-ubuntu20.04
-  CUDA_VERSION: 12.1.1
-  IMAGE_NAME: torch-nightly-2-3-0-20240110-cu121-python3-11
-  MOFED_VERSION: 5.5-1.0.3.2
-  NVIDIA_REQUIRE_CUDA_OVERRIDE: cuda>=12.1 brand=tesla,driver>=450,driver<451 brand=tesla,driver>=470,driver<471
-    brand=unknown,driver>=470,driver<471 brand=nvidia,driver>=470,driver<471 brand=nvidiartx,driver>=470,driver<471
-    brand=geforce,driver>=470,driver<471 brand=geforcertx,driver>=470,driver<471 brand=quadro,driver>=470,driver<471
-    brand=quadrortx,driver>=470,driver<471 brand=titan,driver>=470,driver<471 brand=titanrtx,driver>=470,driver<471
-    brand=tesla,driver>=510,driver<511 brand=unknown,driver>=510,driver<511 brand=nvidia,driver>=510,driver<511
-    brand=nvidiartx,driver>=510,driver<511 brand=geforce,driver>=510,driver<511 brand=geforcertx,driver>=510,driver<511
-    brand=quadro,driver>=510,driver<511 brand=quadrortx,driver>=510,driver<511 brand=titan,driver>=510,driver<511
-    brand=titanrtx,driver>=510,driver<511 brand=tesla,driver>=515,driver<516 brand=unknown,driver>=515,driver<516
-    brand=nvidia,driver>=515,driver<516 brand=nvidiartx,driver>=515,driver<516 brand=geforce,driver>=515,driver<516
-    brand=geforcertx,driver>=515,driver<516 brand=quadro,driver>=515,driver<516 brand=quadrortx,driver>=515,driver<516
-    brand=titan,driver>=515,driver<516 brand=titanrtx,driver>=515,driver<516 brand=tesla,driver>=525,driver<526
-    brand=unknown,driver>=525,driver<526 brand=nvidia,driver>=525,driver<526 brand=nvidiartx,driver>=525,driver<526
-    brand=geforce,driver>=525,driver<526 brand=geforcertx,driver>=525,driver<526 brand=quadro,driver>=525,driver<526
-    brand=quadrortx,driver>=525,driver<526 brand=titan,driver>=525,driver<526 brand=titanrtx,driver>=525,driver<526
-  PYTHON_VERSION: '3.11'
-  PYTORCH_NIGHTLY_URL: https://download.pytorch.org/whl/nightly/cu121
-  PYTORCH_NIGHTLY_VERSION: dev20240110+cu121
-  PYTORCH_VERSION: 2.3.0
-  TAGS:
-  - mosaicml/pytorch:2.3.0_cu121-nightly20240110-python3.11-ubuntu20.04
-  TARGET: pytorch_stage
-  TORCHVISION_VERSION: 0.18.0
 - AWS_OFI_NCCL_VERSION: ''
   BASE_IMAGE: nvidia/cuda:12.1.1-cudnn8-devel-ubuntu20.04
-  COMPOSER_INSTALL_COMMAND: mosaicml[all]==0.20.1
+  COMPOSER_INSTALL_COMMAND: mosaicml[all]==0.21.0
   CUDA_VERSION: 12.1.1
-  IMAGE_NAME: composer-0-20-1
+  IMAGE_NAME: composer-0-21-0
   MOFED_VERSION: 5.5-1.0.3.2
   NVIDIA_REQUIRE_CUDA_OVERRIDE: cuda>=12.1 brand=tesla,driver>=450,driver<451 brand=tesla,driver>=470,driver<471
     brand=unknown,driver>=470,driver<471 brand=nvidia,driver>=470,driver<471 brand=nvidiartx,driver>=470,driver<471
@@ -269,23 +215,23 @@
   PYTORCH_NIGHTLY_VERSION: ''
   PYTORCH_VERSION: 2.1.2
   TAGS:
-  - mosaicml/composer:0.20.1
+  - mosaicml/composer:0.21.0
   - mosaicml/composer:latest
   TARGET: composer_stage
   TORCHVISION_VERSION: 0.16.2
 - AWS_OFI_NCCL_VERSION: ''
   BASE_IMAGE: ubuntu:20.04
-  COMPOSER_INSTALL_COMMAND: mosaicml[all]==0.20.1
+  COMPOSER_INSTALL_COMMAND: mosaicml[all]==0.21.0
   CUDA_VERSION: ''
-  IMAGE_NAME: composer-0-20-1-cpu
+  IMAGE_NAME: composer-0-21-0-cpu
   MOFED_VERSION: 5.5-1.0.3.2
   NVIDIA_REQUIRE_CUDA_OVERRIDE: ''
   PYTHON_VERSION: '3.10'
   PYTORCH_NIGHTLY_URL: ''
   PYTORCH_NIGHTLY_VERSION: ''
   PYTORCH_VERSION: 2.1.2
   TAGS:
-  - mosaicml/composer:0.20.1_cpu
+  - mosaicml/composer:0.21.0_cpu
   - mosaicml/composer:latest_cpu
   TARGET: composer_stage
   TORCHVISION_VERSION: 0.16.2

docker/generate_build_matrix.py

@@ -228,44 +228,10 @@ def _main():
 
         pytorch_entries.append(entry)
 
-    nightly_entry_311_aws = {
-        'AWS_OFI_NCCL_VERSION': 'v1.7.4-aws',
-        'BASE_IMAGE': 'nvidia/cuda:12.1.1-cudnn8-devel-ubuntu20.04',
-        'CUDA_VERSION': '12.1.1',
-        'IMAGE_NAME': 'torch-nightly-2-3-0-20240110-cu121-python3-11-aws',
-        'MOFED_VERSION': '',
-        'NVIDIA_REQUIRE_CUDA_OVERRIDE': _get_cuda_override('12.1.1'),
-        'PYTHON_VERSION': '3.11',
-        'PYTORCH_VERSION': '2.3.0',
-        'PYTORCH_NIGHTLY_URL': 'https://download.pytorch.org/whl/nightly/cu121',
-        'PYTORCH_NIGHTLY_VERSION': 'dev20240110+cu121',
-        'TAGS': ['mosaicml/pytorch:2.3.0_cu121-nightly20240110-python3.11-ubuntu20.04-aws'],
-        'TARGET': 'pytorch_stage',
-        'TORCHVISION_VERSION': '0.18.0',
-    }
-    pytorch_entries.append(nightly_entry_311_aws)
-
-    nightly_entry_311 = {
-        'AWS_OFI_NCCL_VERSION': '',
-        'BASE_IMAGE': 'nvidia/cuda:12.1.1-cudnn8-devel-ubuntu20.04',
-        'CUDA_VERSION': '12.1.1',
-        'IMAGE_NAME': 'torch-nightly-2-3-0-20240110-cu121-python3-11',
-        'MOFED_VERSION': '5.5-1.0.3.2',
-        'NVIDIA_REQUIRE_CUDA_OVERRIDE': _get_cuda_override('12.1.1'),
-        'PYTHON_VERSION': '3.11',
-        'PYTORCH_VERSION': '2.3.0',
-        'PYTORCH_NIGHTLY_URL': 'https://download.pytorch.org/whl/nightly/cu121',
-        'PYTORCH_NIGHTLY_VERSION': 'dev20240110+cu121',
-        'TAGS': ['mosaicml/pytorch:2.3.0_cu121-nightly20240110-python3.11-ubuntu20.04'],
-        'TARGET': 'pytorch_stage',
-        'TORCHVISION_VERSION': '0.18.0',
-    }
-    pytorch_entries.append(nightly_entry_311)
-
     composer_entries = []
 
     # The `GIT_COMMIT` is a placeholder and Jenkins will substitute it with the actual git commit for the `composer_staging` images
-    composer_versions = ['0.20.1']  # Only build images for the latest composer version
+    composer_versions = ['0.21.0']  # Only build images for the latest composer version
     composer_python_versions = [PRODUCTION_PYTHON_VERSION]  # just build composer against the latest
 
     for product in itertools.product(composer_python_versions, composer_versions, cuda_options):

docs/source/notes/distributed_training.rst

@@ -395,18 +395,14 @@ It does this by gathering the model state to the global rank 0 device, unflatten
 If `load_monolith_rank0_only=True`, then when loading checkpoints the global rank 0 device will load in the checkpoint file and scatter the
 model and optimizer state to the other ranks, which will will dramatically reduce the memory usage on system. Otherwise, all ranks will separately load in the checkpoint file.
 
-2. :code:`state_dict_type='local'`
-For save: each rank saves out the flattened model state shard they are
-responsibile for to a distinct checkpoint file. For load, each rank loads in the checkpoint file
-corresponding to their shard. **Note: state_dict_type='local' is deprecated in Composer for torch versions 2.0.0 or higher.**
-
-3. :code:`state_dict_type='sharded'`
-Each rank saves out an unflattened shard. For loading, similar to ``state_dict_type='local'``, each rank
-loads in the checkpoint file corresponding to their unflattened shard. **Note: state_dict_type='sharded' is the recommended setting for sharded checkpointing in Composer for torch versions 2.0.0 or higher.**
+2. :code:`state_dict_type='sharded'`
+Each rank saves out an unflattened shard. For loading, each rank loads in the checkpoint file
+corresponding to their unflattened shard.
+**Note: state_dict_type='sharded' is the recommended setting for sharded checkpointing in Composer for torch versions 2.0.0 or higher.**
 
 See `The FSDP docs <https://pytorch.org/docs/stable/fsdp.html#torch.distributed.fsdp.FullyShardedDataParallel.state_dict>`__ for more info.
 
-If you use sharded checkpoints (`state_dict_type='sharded'` or `state_dict_type='local'`), your run will save as many files as you have
+If you use sharded checkpoints (`state_dict_type='sharded'`), your run will save as many files as you have
 ranks at each checkpointing event (plus one metadata file for torch versions 2.0.0 or higher). This can quicky pollute your `save_folder` with a lot of files after a couple checkpointing events.
 To help keep your checkpoint shard files organized, Composer will save each set of shards in it's own prefix directory, which you can configure
 by using `'sharded_ckpt_prefix_dir'` (default value `sharded_ckpt_prefix_dir='ep{epoch}-ba{batch}'`). Checkpoint shards will be saved to