From 4c0c2ee3e4725526e2f86855f7da674992e702ac Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Andreas=20S=C3=B8gaard?= Date: Wed, 28 Feb 2024 15:53:01 +0000 Subject: [PATCH] =?UTF-8?q?Deploying=20to=20gh-pages=20from=20@=20graphnet?= =?UTF-8?q?-team/graphnet@e572efcccb0bc95d490f10965ae0c16c7b771e69=20?= =?UTF-8?q?=F0=9F=9A=80?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- _modules/graphnet/data/dataclasses.html | 15 +- _modules/graphnet/deployment/deployer.html | 497 +++++++++++++++ .../deployment/deployment_module.html | 459 ++++++++++++++ .../cleaning_module.html} | 279 +-------- .../deployment/icecube/inference_module.html | 568 ++++++++++++++++++ _modules/index.html | 5 +- ...t => graphnet.deployment.deployer.rst.txt} | 2 +- ...phnet.deployment.deployment_module.rst.txt | 8 + ...yment.i3modules.deprecated_methods.rst.txt | 8 + ...ployment.i3modules.graphnet_module.rst.txt | 8 - .../api/graphnet.deployment.i3modules.rst.txt | 3 +- ...deployment.icecube.cleaning_module.rst.txt | 8 + ...hnet.deployment.icecube.i3deployer.rst.txt | 8 + ...eployment.icecube.inference_module.rst.txt | 8 + .../api/graphnet.deployment.icecube.rst.txt | 38 ++ _sources/api/graphnet.deployment.rst.txt | 11 + api/graphnet.data.dataclasses.html | 91 +++ api/graphnet.data.html | 1 + api/graphnet.deployment.deployer.html | 551 +++++++++++++++++ ...graphnet.deployment.deployment_module.html | 518 ++++++++++++++++ api/graphnet.deployment.html | 43 +- ...loyment.i3modules.deprecated_methods.html} | 38 +- api/graphnet.deployment.i3modules.html | 34 +- ...t.deployment.icecube.cleaning_module.html} | 140 ++--- api/graphnet.deployment.icecube.html | 511 ++++++++++++++++ ...raphnet.deployment.icecube.i3deployer.html | 498 +++++++++++++++ ...t.deployment.icecube.inference_module.html | 549 +++++++++++++++++ api/graphnet.html | 3 + api/graphnet.models.html | 6 +- genindex.html | 67 ++- objects.inv | Bin 7379 -> 7529 bytes py-modindex.html | 17 +- searchindex.js | 2 +- sitemap.xml | 2 +- 34 files changed, 4591 insertions(+), 405 deletions(-) create mode 100644 _modules/graphnet/deployment/deployer.html create mode 100644 _modules/graphnet/deployment/deployment_module.html rename _modules/graphnet/deployment/{i3modules/graphnet_module.html => icecube/cleaning_module.html} (54%) create mode 100644 _modules/graphnet/deployment/icecube/inference_module.html rename _sources/api/{graphnet.deployment.i3modules.deployer.rst.txt => graphnet.deployment.deployer.rst.txt} (57%) create mode 100644 _sources/api/graphnet.deployment.deployment_module.rst.txt create mode 100644 _sources/api/graphnet.deployment.i3modules.deprecated_methods.rst.txt delete mode 100644 _sources/api/graphnet.deployment.i3modules.graphnet_module.rst.txt create mode 100644 _sources/api/graphnet.deployment.icecube.cleaning_module.rst.txt create mode 100644 _sources/api/graphnet.deployment.icecube.i3deployer.rst.txt create mode 100644 _sources/api/graphnet.deployment.icecube.inference_module.rst.txt create mode 100644 _sources/api/graphnet.deployment.icecube.rst.txt create mode 100644 api/graphnet.deployment.deployer.html create mode 100644 api/graphnet.deployment.deployment_module.html rename api/{graphnet.deployment.i3modules.deployer.html => graphnet.deployment.i3modules.deprecated_methods.html} (92%) rename api/{graphnet.deployment.i3modules.graphnet_module.html => graphnet.deployment.icecube.cleaning_module.html} (55%) create mode 100644 api/graphnet.deployment.icecube.html create mode 100644 api/graphnet.deployment.icecube.i3deployer.html create mode 100644 api/graphnet.deployment.icecube.inference_module.html diff --git a/_modules/graphnet/data/dataclasses.html b/_modules/graphnet/data/dataclasses.html index 20c423cf1..a93a3e455 100644 --- a/_modules/graphnet/data/dataclasses.html +++ b/_modules/graphnet/data/dataclasses.html @@ -324,7 +324,7 @@

Source code for graphnet.data.dataclasses

 """Module containing experiment-specific dataclasses."""
 
-
+from typing import List, Any
 from dataclasses import dataclass
 
 
@@ -335,6 +335,19 @@ 
Source code for graphnet.d
     i3_file: str
     gcd_file: str
+ + +
+[docs] +@dataclass +class Settings: + """Dataclass for workers in I3Deployer.""" + + i3_files: List[str] + gcd_file: str + output_folder: str + modules: List[Any]
+ diff --git a/_modules/graphnet/deployment/deployer.html b/_modules/graphnet/deployment/deployer.html new file mode 100644 index 000000000..ea737ce89 --- /dev/null +++ b/_modules/graphnet/deployment/deployer.html @@ -0,0 +1,497 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + graphnet.deployment.deployer — graphnet documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Skip to content +
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Source code for graphnet.deployment.deployer

+"""Contains the graphnet deployment module."""
+import random
+from abc import abstractmethod, ABC
+import multiprocessing
+from typing import TYPE_CHECKING, List, Union, Sequence, Any
+import time
+
+from graphnet.utilities.imports import has_torch_package
+from .deployment_module import DeploymentModule
+from graphnet.utilities.logging import Logger
+
+if has_torch_package or TYPE_CHECKING:
+    import torch
+
+
+

+[docs]
+class Deployer(ABC, Logger):
+    """A generic baseclass for applying `DeploymentModules` to analysis files.
+
+    Modules are applied in the order that they appear in `modules`.
+    """
+
+    @abstractmethod
+    def _process_files(
+        self,
+        settings: Any,
+    ) -> None:
+        """Process a single file.
+
+        If n_workers > 1, this function is run in parallel n_worker times. Each
+        worker will loop over an allocated set of files.
+        """
+        raise NotImplementedError
+
+    @abstractmethod
+    def _prepare_settings(
+        self, input_files: List[str], output_folder: str
+    ) -> List[Any]:
+        """Produce a list of inputs for each worker.
+
+        This function must produce and return a list of arguments to each
+        worker.
+        """
+        raise NotImplementedError
+
+    def __init__(
+        self,
+        modules: Union[DeploymentModule, Sequence[DeploymentModule]],
+        n_workers: int = 1,
+    ) -> None:
+        """Initialize `Deployer`.
+
+        Will apply `DeploymentModules` to files in the order in which they
+        appear in `modules`. Each module is run independently.
+
+        Args:
+            modules: List of `DeploymentModules`.
+                              Order of appearence in the list determines order
+                              of deployment.
+            n_workers: Number of workers. The deployer will divide the number
+                       of input files across workers. Defaults to 1.
+        """
+        super().__init__(name=__name__, class_name=self.__class__.__name__)
+        # This makes sure that one worker cannot access more
+        # than 1 core's worth of compute.
+
+        if torch.get_num_interop_threads() > 1:
+            torch.set_num_interop_threads(1)
+        if torch.get_num_threads() > 1:
+            torch.set_num_threads(1)
+
+        # Check
+        if isinstance(modules, list):
+            self._modules = modules
+        else:
+            self._modules = [modules]
+
+        # Member Variables
+        self._n_workers = n_workers
+
+    def _launch_jobs(self, settings: List[Any]) -> None:
+        """Will launch jobs in parallel if n_workers > 1, else run on main."""
+        if self._n_workers > 1:
+            processes = []
+            for i in range(self._n_workers):
+                processes.append(
+                    multiprocessing.Process(
+                        target=self._process_files,
+                        args=[settings[i]],  # type: ignore
+                    )
+                )
+
+            for process in processes:
+                process.start()
+
+            for process in processes:
+                process.join()
+        else:
+            self._process_files(settings[0])
+
+

+[docs]
+    def run(
+        self,
+        input_files: Union[List[str], str],
+        output_folder: str,
+    ) -> None:
+        """Apply `modules` to input files.
+
+        Args:
+            input_files: Path(s) to i3 file(s) that you wish to
+                         apply the graphnet modules to.
+            output_folder: The output folder to which the i3 files are written.
+        """
+        start_time = time.time()
+        if isinstance(input_files, list):
+            random.shuffle(input_files)
+        else:
+            input_files = [input_files]
+        settings = self._prepare_settings(
+            input_files=input_files, output_folder=output_folder
+        )
+
+        assert len(settings) == self._n_workers
+
+        self.info(
+            f"""processing {len(input_files)} files \n
+                using {self._n_workers} workers"""
+        )
+        self._launch_jobs(settings)
+        self.info(
+            f"""Processing {len(input_files)} files was completed in \n
+         {time.time() - start_time} seconds using {self._n_workers} cores."""
+        )

+

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+ + + + + \ No newline at end of file diff --git a/_modules/graphnet/deployment/deployment_module.html b/_modules/graphnet/deployment/deployment_module.html new file mode 100644 index 000000000..812e10b3c --- /dev/null +++ b/_modules/graphnet/deployment/deployment_module.html @@ -0,0 +1,459 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + graphnet.deployment.deployment_module — graphnet documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Skip to content +
+ +
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Source code for graphnet.deployment.deployment_module

+"""Class(es) for deploying GraphNeT models in icetray as I3Modules."""
+from abc import abstractmethod
+from typing import Any, List, Union, Dict
+
+import numpy as np
+from torch import Tensor
+from torch_geometric.data import Data, Batch
+
+from graphnet.models import Model
+from graphnet.utilities.config import ModelConfig
+from graphnet.utilities.logging import Logger
+
+
+

+[docs]
+class DeploymentModule(Logger):
+    """Base DeploymentModule for GraphNeT.
+
+    Contains standard methods for loading models doing inference with them.
+    Experiment-specific implementations may overwrite methods and should define
+    `__call__`.
+    """
+
+    def __init__(
+        self,
+        model_config: Union[ModelConfig, str],
+        state_dict: Union[Dict[str, Tensor], str],
+        device: str = "cpu",
+        prediction_columns: Union[List[str], None] = None,
+    ):
+        """Construct DeploymentModule.
+
+        Arguments:
+            model_config: A model configuration file.
+            state_dict: A state dict for the model.
+            device: The computational device to use. Defaults to "cpu".
+            prediction_columns: Column names for each column in model output.
+        """
+        super().__init__(name=__name__, class_name=self.__class__.__name__)
+        # Set Member Variables
+        self.model = self._load_model(
+            model_config=model_config, state_dict=state_dict
+        )
+
+        self.prediction_columns = self._resolve_prediction_columns(
+            prediction_columns
+        )
+
+        # Set model to inference mode.
+        self.model.inference()
+
+        # Move model to device
+        self.model.to(device)
+
+    @abstractmethod
+    def __call__(self, input_data: Any) -> Any:
+        """Define here how the module acts on a file/data stream."""
+
+    def _load_model(
+        self,
+        model_config: Union[ModelConfig, str],
+        state_dict: Union[Dict[str, Tensor], str],
+    ) -> Model:
+        """Load `Model` from config and insert learned weights."""
+        model = Model.from_config(model_config, trust=True)
+        model.load_state_dict(state_dict)
+        return model
+
+    def _resolve_prediction_columns(
+        self, prediction_columns: Union[List[str], None]
+    ) -> List[str]:
+        if prediction_columns is not None:
+            if isinstance(prediction_columns, str):
+                prediction_columns = [prediction_columns]
+            else:
+                prediction_columns = prediction_columns
+        else:
+            prediction_columns = self.model.prediction_labels
+        return prediction_columns
+
+    def _inference(self, data: Union[Data, Batch]) -> List[np.ndarray]:
+        """Apply model to a single event or batch of events `data`.
+
+        Args:
+            data: A `Data` or ``Batch` object -
+                  either a single output of a `GraphDefinition` or a batch of
+                  them.
+
+        Returns:
+            A List of numpy arrays, each representing the output from the
+            `Task`s that the model contains.
+        """
+        # Perform inference
+        output = self.model(data=data)
+        # Loop over tasks in model and transform to numpy
+        for k in range(len(output)):
+            output[k] = output[k].detach().numpy()
+        return output

+
+
+ +
+
+
+
+
+ + + + + \ No newline at end of file diff --git a/_modules/graphnet/deployment/i3modules/graphnet_module.html b/_modules/graphnet/deployment/icecube/cleaning_module.html similarity index 54% rename from _modules/graphnet/deployment/i3modules/graphnet_module.html rename to _modules/graphnet/deployment/icecube/cleaning_module.html index 5bb5c0a0e..90cb9682f 100644 --- a/_modules/graphnet/deployment/i3modules/graphnet_module.html +++ b/_modules/graphnet/deployment/icecube/cleaning_module.html @@ -60,7 +60,7 @@ - graphnet.deployment.i3modules.graphnet_module — graphnet documentation + graphnet.deployment.icecube.cleaning_module — graphnet documentation + + + + + + + + + + + + + + + + graphnet.deployment.icecube.inference_module — graphnet documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Skip to content +
+ +
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+ + + + +
+
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+
+
+ +
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+
+
+
+ + +
+
+
+ +
+
+ +

Source code for graphnet.deployment.icecube.inference_module

+"""IceCube I3InferenceModule.
+
+Contains functionality for writing model predictions to i3 files.
+"""
+from typing import List, Union, Optional, TYPE_CHECKING, Dict, Any
+
+import numpy as np
+from torch_geometric.data import Data, Batch
+
+from graphnet.utilities.config import ModelConfig
+from graphnet.deployment import DeploymentModule
+from graphnet.data.extractors.icecube import I3FeatureExtractor
+from graphnet.utilities.imports import has_icecube_package
+
+if has_icecube_package() or TYPE_CHECKING:
+    from icecube.icetray import (
+        I3Frame,
+    )  # pyright: reportMissingImports=false
+    from icecube.dataclasses import (
+        I3Double,
+    )  # pyright: reportMissingImports=false
+
+
+

+[docs]
+class I3InferenceModule(DeploymentModule):
+    """General class for inference on i3 frames."""
+
+    def __init__(
+        self,
+        pulsemap_extractor: Union[
+            List[I3FeatureExtractor], I3FeatureExtractor
+        ],
+        model_config: Union[ModelConfig, str],
+        state_dict: str,
+        model_name: str,
+        gcd_file: str,
+        features: Optional[List[str]] = None,
+        prediction_columns: Optional[Union[List[str], None]] = None,
+        pulsemap: Optional[str] = None,
+    ):
+        """General class for inference on I3Frames (physics).
+
+        Arguments:
+            pulsemap_extractor: The extractor used to extract the pulsemap.
+            model_config: The ModelConfig (or path to it) that summarizes the
+                            model used for inference.
+            state_dict: Path to state_dict containing the learned weights.
+            model_name: The name used for the model. Will help define the
+                        named entry in the I3Frame. E.g. "dynedge".
+            gcd_file: path to associated gcd file.
+            features: the features of the pulsemap that the model is expecting.
+            prediction_columns: column names for the predictions of the model.
+                               Will help define the named entry in the I3Frame.
+                                E.g. ['energy_reco']. Optional.
+            pulsemap: the pulsmap that the model is expecting as input.
+        """
+        super().__init__(
+            model_config=model_config,
+            state_dict=state_dict,
+            prediction_columns=prediction_columns,
+        )
+        # Checks
+        assert isinstance(gcd_file, str), "gcd_file must be string"
+
+        # Set Member Variables
+        if isinstance(pulsemap_extractor, list):
+            self._i3_extractors = pulsemap_extractor
+        else:
+            self._i3_extractors = [pulsemap_extractor]
+        if features is None:
+            features = self.model._graph_definition._input_feature_names
+        self._graph_definition = self.model._graph_definition
+        self._pulsemap = pulsemap
+        self._gcd_file = gcd_file
+        self.model_name = model_name
+        self._features = features
+
+        # Set GCD file for pulsemap extractor
+        for i3_extractor in self._i3_extractors:
+            i3_extractor.set_gcd(i3_file="", gcd_file=self._gcd_file)
+
+    def __call__(self, frame: I3Frame) -> bool:
+        """Write predictions from model to frame."""
+        # inference
+        data = self._create_data_representation(frame=frame)
+        predictions = self._apply_model(data=data)
+
+        # Check dimensions of predictions and prediction columns
+        dim = self._check_dimensions(predictions=predictions)
+
+        # Build Dictionary from predictions
+        data = self._create_dictionary(dim=dim, predictions=predictions)
+
+        # Submit Dictionary to frame
+        frame = self._add_to_frame(frame=frame, data=data)
+        return True
+
+    def _check_dimensions(self, predictions: np.ndarray) -> int:
+        if len(predictions.shape) > 1:
+            dim = predictions.shape[1]
+        else:
+            dim = len(predictions)
+        try:
+            assert dim == len(self.prediction_columns)
+        except AssertionError as e:
+            self.error(
+                f"predictions have shape {dim} but"
+                f"prediction columns have [{self.prediction_columns}]"
+            )
+            raise e
+
+        assert predictions.shape[0] == 1
+        return dim
+
+    def _create_dictionary(
+        self, dim: int, predictions: np.ndarray
+    ) -> Dict[str, Any]:
+        """Transform predictions into a dictionary."""
+        data = {}
+        for i in range(dim):
+            try:
+                assert len(predictions[:, i]) == 1
+                data[
+                    self.model_name + "_" + self.prediction_columns[i]
+                ] = I3Double(float(predictions[:, i][0]))
+            except IndexError:
+                data[
+                    self.model_name + "_" + self.prediction_columns[i]
+                ] = I3Double(predictions[0])
+        return data
+
+    def _apply_model(self, data: Data) -> np.ndarray:
+        """Apply model to `Data` and case-handling."""
+        if data is not None:
+            predictions = self._inference(data)
+            if isinstance(predictions, list):
+                predictions = predictions[0]
+                self.warning(
+                    f"{self.__class__.__name__} assumes one Task "
+                    f"but got {len(predictions)}. Only the first will"
+                    " be used."
+                )
+        else:
+            self.warning(
+                "At least one event has no pulses "
+                " - padding {self.prediction_columns} with NaN."
+            )
+            predictions = np.repeat(
+                [np.nan], len(self.prediction_columns)
+            ).reshape(-1, len(self.prediction_columns))
+        return predictions
+
+    def _create_data_representation(self, frame: I3Frame) -> Data:
+        """Process Physics I3Frame into graph."""
+        # Extract features
+        input_features = self._extract_feature_array_from_frame(frame)
+        # Prepare graph data
+        if len(input_features) > 0:
+            data = self._graph_definition(
+                input_features=input_features,
+                input_feature_names=self._features,
+            )
+            return Batch.from_data_list([data])
+        else:
+            return None
+
+    def _extract_feature_array_from_frame(self, frame: I3Frame) -> np.array:
+        """Apply the I3FeatureExtractors to the I3Frame.
+
+        Arguments:
+            frame: Physics I3Frame (PFrame)
+
+        Returns:
+            array with pulsemap
+        """
+        features = None
+        for i3extractor in self._i3_extractors:
+            feature_dict = i3extractor(frame)
+            features_pulsemap = np.array(
+                [feature_dict[key] for key in self._features]
+            ).T
+            if features is None:
+                features = features_pulsemap
+            else:
+                features = np.concatenate(
+                    (features, features_pulsemap), axis=0
+                )
+        return features
+
+    def _add_to_frame(self, frame: I3Frame, data: Dict[str, Any]) -> I3Frame:
+        """Add every field in data to I3Frame.
+
+        Arguments:
+            frame: I3Frame (physics)
+            data: Dictionary containing content that will be written to frame.
+
+        Returns:
+            frame: Same I3Frame as input, but with the new entries
+        """
+        assert isinstance(
+            data, dict
+        ), f"data must be of type dict. Got {type(data)}"
+        for key in data.keys():
+            if key not in frame:
+                frame.Put(key, data[key])
+        return frame

+
+
+ +
+
+
+
+
+ + + + + \ No newline at end of file diff --git a/_modules/index.html b/_modules/index.html index c89560423..a12dd2724 100644 --- a/_modules/index.html +++ b/_modules/index.html @@ -359,7 +359,10 @@

All modules for which code is available

  • graphnet.data.writers.graphnet_writer
  • graphnet.data.writers.parquet_writer
  • graphnet.data.writers.sqlite_writer
    • -
  • graphnet.deployment.i3modules.graphnet_module
    • +
  • graphnet.deployment.deployer
    • +
  • graphnet.deployment.deployment_module
    • +
  • graphnet.deployment.icecube.cleaning_module
    • +
  • graphnet.deployment.icecube.inference_module
  • graphnet.models.coarsening
  • graphnet.models.components.embedding
  • graphnet.models.components.layers
    • diff --git a/_sources/api/graphnet.deployment.i3modules.deployer.rst.txt b/_sources/api/graphnet.deployment.deployer.rst.txt similarity index 57% rename from _sources/api/graphnet.deployment.i3modules.deployer.rst.txt rename to _sources/api/graphnet.deployment.deployer.rst.txt index e5266caa3..518251334 100644 --- a/_sources/api/graphnet.deployment.i3modules.deployer.rst.txt +++ b/_sources/api/graphnet.deployment.deployer.rst.txt @@ -2,7 +2,7 @@ deployer ======== -.. automodule:: graphnet.deployment.i3modules.deployer +.. automodule:: graphnet.deployment.deployer :members: :undoc-members: :show-inheritance: diff --git a/_sources/api/graphnet.deployment.deployment_module.rst.txt b/_sources/api/graphnet.deployment.deployment_module.rst.txt new file mode 100644 index 000000000..8b0692591 --- /dev/null +++ b/_sources/api/graphnet.deployment.deployment_module.rst.txt @@ -0,0 +1,8 @@ + +deployment\_module +================== + +.. automodule:: graphnet.deployment.deployment_module + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/api/graphnet.deployment.i3modules.deprecated_methods.rst.txt b/_sources/api/graphnet.deployment.i3modules.deprecated_methods.rst.txt new file mode 100644 index 000000000..064f4af69 --- /dev/null +++ b/_sources/api/graphnet.deployment.i3modules.deprecated_methods.rst.txt @@ -0,0 +1,8 @@ + +deprecated\_methods +=================== + +.. automodule:: graphnet.deployment.i3modules.deprecated_methods + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/api/graphnet.deployment.i3modules.graphnet_module.rst.txt b/_sources/api/graphnet.deployment.i3modules.graphnet_module.rst.txt deleted file mode 100644 index 45e2e93f3..000000000 --- a/_sources/api/graphnet.deployment.i3modules.graphnet_module.rst.txt +++ /dev/null @@ -1,8 +0,0 @@ - -graphnet\_module -================ - -.. automodule:: graphnet.deployment.i3modules.graphnet_module - :members: - :undoc-members: - :show-inheritance: diff --git a/_sources/api/graphnet.deployment.i3modules.rst.txt b/_sources/api/graphnet.deployment.i3modules.rst.txt index e7e2c8f33..11d13bcb3 100644 --- a/_sources/api/graphnet.deployment.i3modules.rst.txt +++ b/_sources/api/graphnet.deployment.i3modules.rst.txt @@ -15,8 +15,7 @@ i3modules .. toctree:: :maxdepth: 2 - graphnet.deployment.i3modules.deployer - graphnet.deployment.i3modules.graphnet_module + graphnet.deployment.i3modules.deprecated_methods diff --git a/_sources/api/graphnet.deployment.icecube.cleaning_module.rst.txt b/_sources/api/graphnet.deployment.icecube.cleaning_module.rst.txt new file mode 100644 index 000000000..f86925081 --- /dev/null +++ b/_sources/api/graphnet.deployment.icecube.cleaning_module.rst.txt @@ -0,0 +1,8 @@ + +cleaning\_module +================ + +.. automodule:: graphnet.deployment.icecube.cleaning_module + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/api/graphnet.deployment.icecube.i3deployer.rst.txt b/_sources/api/graphnet.deployment.icecube.i3deployer.rst.txt new file mode 100644 index 000000000..d7a08b69d --- /dev/null +++ b/_sources/api/graphnet.deployment.icecube.i3deployer.rst.txt @@ -0,0 +1,8 @@ + +i3deployer +========== + +.. automodule:: graphnet.deployment.icecube.i3deployer + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/api/graphnet.deployment.icecube.inference_module.rst.txt b/_sources/api/graphnet.deployment.icecube.inference_module.rst.txt new file mode 100644 index 000000000..cc8948488 --- /dev/null +++ b/_sources/api/graphnet.deployment.icecube.inference_module.rst.txt @@ -0,0 +1,8 @@ + +inference\_module +================= + +.. automodule:: graphnet.deployment.icecube.inference_module + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/api/graphnet.deployment.icecube.rst.txt b/_sources/api/graphnet.deployment.icecube.rst.txt new file mode 100644 index 000000000..cd2519bf2 --- /dev/null +++ b/_sources/api/graphnet.deployment.icecube.rst.txt @@ -0,0 +1,38 @@ + +icecube +======= + + +.. automodule:: graphnet.deployment.icecube + :members: + :undoc-members: + :show-inheritance: + + +|start-h2| Submodules |end-h2| + + +.. toctree:: + :maxdepth: 2 + + graphnet.deployment.icecube.cleaning_module + graphnet.deployment.icecube.i3deployer + graphnet.deployment.icecube.inference_module + + + +.. |start-h2| raw:: html + +

    + +.. |end-h2| raw:: html + +

    + +.. |start-h3| raw:: html + +

    + +.. |end-h3| raw:: html + +

    \ No newline at end of file diff --git a/_sources/api/graphnet.deployment.rst.txt b/_sources/api/graphnet.deployment.rst.txt index ed0dbc80e..7f3273ef4 100644 --- a/_sources/api/graphnet.deployment.rst.txt +++ b/_sources/api/graphnet.deployment.rst.txt @@ -15,6 +15,17 @@ deployment :maxdepth: 2 graphnet.deployment.i3modules + graphnet.deployment.icecube + +|start-h2| Submodules |end-h2| + + +.. toctree:: + :maxdepth: 2 + + graphnet.deployment.deployer + graphnet.deployment.deployment_module + .. |start-h2| raw:: html diff --git a/api/graphnet.data.dataclasses.html b/api/graphnet.data.dataclasses.html index 522ebf923..9a0ff4708 100644 --- a/api/graphnet.data.dataclasses.html +++ b/api/graphnet.data.dataclasses.html @@ -388,6 +388,18 @@
  • i3_file
  • gcd_file +
    • + + +
  • Settings
    • @@ -414,6 +426,41 @@ gcd_file + + + +
  • + + + Settings +
    • @@ -514,6 +561,18 @@
  • i3_file
  • gcd_file +
    • + + +
  • Settings
    • @@ -552,6 +611,38 @@ gcd_file: str
    +
    +
    +class graphnet.data.dataclasses.Settings(i3_files, gcd_file, output_folder, modules)[source]
    +

    Bases: object

    +

    Dataclass for workers in I3Deployer.

    +
    +
    Parameters:
    +
      +

    • i3_files (List[str]) –

      • +

    • gcd_file (str) –

      • +

    • output_folder (str) –

      • +

    • modules (List[Any]) –

      • +
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    +i3_files: List[str]
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    +gcd_file: str
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    +output_folder: str
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    +modules: List[Any]
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    diff --git a/api/graphnet.data.html b/api/graphnet.data.html index 2f19625ef..ea5ca2d92 100644 --- a/api/graphnet.data.html +++ b/api/graphnet.data.html @@ -541,6 +541,7 @@
  • dataclasses
  • dataconverter
    • @@ -398,8 +419,26 @@
    +
    +

    Submodules

    +
    + diff --git a/api/graphnet.deployment.i3modules.deployer.html b/api/graphnet.deployment.i3modules.deprecated_methods.html similarity index 92% rename from api/graphnet.deployment.i3modules.deployer.html rename to api/graphnet.deployment.i3modules.deprecated_methods.html index 9ebe17073..e4a56ae6a 100644 --- a/api/graphnet.deployment.i3modules.deployer.html +++ b/api/graphnet.deployment.i3modules.deprecated_methods.html @@ -61,7 +61,7 @@ - deployer — graphnet documentation + deprecated_methods — graphnet documentation + + + + + + + + + + + + + + + + icecube — graphnet documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Skip to content +
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    + + + + + \ No newline at end of file diff --git a/api/graphnet.deployment.icecube.i3deployer.html b/api/graphnet.deployment.icecube.i3deployer.html new file mode 100644 index 000000000..ef9795a2c --- /dev/null +++ b/api/graphnet.deployment.icecube.i3deployer.html @@ -0,0 +1,498 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + i3deployer — graphnet documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Skip to content +
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    i3deployer

    +
    + + +
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    + + + + + \ No newline at end of file diff --git a/api/graphnet.deployment.icecube.inference_module.html b/api/graphnet.deployment.icecube.inference_module.html new file mode 100644 index 000000000..b9937cf35 --- /dev/null +++ b/api/graphnet.deployment.icecube.inference_module.html @@ -0,0 +1,549 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + inference_module — graphnet documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Skip to content +
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    inference_module

    +

    IceCube I3InferenceModule.

    +

    Contains functionality for writing model predictions to i3 files.

    +
    +
    +class graphnet.deployment.icecube.inference_module.I3InferenceModule(pulsemap_extractor, model_config, state_dict, model_name, gcd_file, features, prediction_columns, pulsemap)[source]
    +

    Bases: DeploymentModule

    +

    General class for inference on i3 frames.

    +

    General class for inference on I3Frames (physics).

    +
    +
    Parameters:
    +
      +

    • pulsemap_extractor (Union[List[I3FeatureExtractor], I3FeatureExtractor]) – The extractor used to extract the pulsemap.

      • +

    • model_config (Union[ModelConfig, str]) – The ModelConfig (or path to it) that summarizes the +model used for inference.

      • +

    • state_dict (str) – Path to state_dict containing the learned weights.

      • +

    • model_name (str) – The name used for the model. Will help define the +named entry in the I3Frame. E.g. “dynedge”.

      • +

    • gcd_file (str) – path to associated gcd file.

      • +

    • features (Optional[List[str]], default: None) – the features of the pulsemap that the model is expecting.

      • +

    • prediction_columns (Optional[List[str]], default: None) –

      column names for the predictions of the model. +Will help define the named entry in the I3Frame.

      +
      +

      E.g. [‘energy_reco’]. Optional.

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    • pulsemap (Optional[str], default: None) – the pulsmap that the model is expecting as input.

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    + + + + + \ No newline at end of file diff --git a/api/graphnet.html b/api/graphnet.html index f7cc7c801..44d85abf5 100644 --- a/api/graphnet.html +++ b/api/graphnet.html @@ -433,6 +433,9 @@
  • deployment
  • models
    • - - + @@ -2389,6 +2432,8 @@

    S

  • set_verbose_print_recursively() (graphnet.models.model.Model method)
  • setLevel() (graphnet.utilities.logging.Logger method) +
    • +
  • Settings (class in graphnet.data.dataclasses)