2020-08-20 02:03:22 +00:00
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# Copyright The PyTorch Lightning team.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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2021-05-04 10:50:56 +00:00
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from dataclasses import dataclass
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from typing import Optional
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2020-08-20 02:03:22 +00:00
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2021-01-12 13:56:07 +00:00
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from pytorch_lightning.utilities import LightningEnum
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2020-08-09 10:24:09 +00:00
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2021-05-04 10:50:56 +00:00
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class TrainerStatus(LightningEnum):
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"""Enum for the status of the :class:`~pytorch_lightning.trainer.trainer.Trainer`"""
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2021-07-26 11:37:35 +00:00
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INITIALIZING = "initializing" # trainer creation
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RUNNING = "running"
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FINISHED = "finished"
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INTERRUPTED = "interrupted"
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2020-08-09 10:24:09 +00:00
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2021-03-06 12:40:19 +00:00
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@property
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def stopped(self) -> bool:
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return self in (self.FINISHED, self.INTERRUPTED)
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2021-05-04 10:50:56 +00:00
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class TrainerFn(LightningEnum):
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"""
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Enum for the user-facing functions of the :class:`~pytorch_lightning.trainer.trainer.Trainer`
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such as :meth:`~pytorch_lightning.trainer.trainer.Trainer.fit` and
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:meth:`~pytorch_lightning.trainer.trainer.Trainer.test`.
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"""
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FITTING = "fit"
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VALIDATING = "validate"
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TESTING = "test"
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PREDICTING = "predict"
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TUNING = "tune"
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2021-03-06 12:40:19 +00:00
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@property
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def _setup_fn(self) -> "TrainerFn":
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"""
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``FITTING`` is used instead of ``TUNING`` as there are no "tune" dataloaders.
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This is used for the ``setup()`` and ``teardown()`` hooks
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"""
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return TrainerFn.FITTING if self == TrainerFn.TUNING else self
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2020-08-09 10:24:09 +00:00
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2021-01-13 01:33:39 +00:00
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class RunningStage(LightningEnum):
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"""
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Enum for the current running stage.
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This stage complements :class:`TrainerFn` by specifying the current running stage for each function.
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More than one running stage value can be set while a :class:`TrainerFn` is running:
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- ``TrainerFn.FITTING`` - ``RunningStage.{SANITY_CHECKING,TRAINING,VALIDATING}``
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- ``TrainerFn.VALIDATING`` - ``RunningStage.VALIDATING``
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- ``TrainerFn.TESTING`` - ``RunningStage.TESTING``
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- ``TrainerFn.PREDICTING`` - ``RunningStage.PREDICTING``
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- ``TrainerFn.TUNING`` - ``RunningStage.{TUNING,SANITY_CHECKING,TRAINING,VALIDATING}``
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2021-01-13 01:33:39 +00:00
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"""
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2021-07-26 11:37:35 +00:00
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TRAINING = "train"
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SANITY_CHECKING = "sanity_check"
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VALIDATING = "validate"
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TESTING = "test"
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PREDICTING = "predict"
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TUNING = "tune"
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2021-01-13 01:33:39 +00:00
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2021-03-06 12:40:19 +00:00
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@property
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def evaluating(self) -> bool:
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return self in (self.VALIDATING, self.TESTING)
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2021-05-04 10:50:56 +00:00
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@dataclass
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class TrainerState:
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"""Dataclass to encapsulate the current :class:`~pytorch_lightning.trainer.trainer.Trainer` state"""
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2021-05-04 10:50:56 +00:00
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status: TrainerStatus = TrainerStatus.INITIALIZING
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fn: Optional[TrainerFn] = None
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stage: Optional[RunningStage] = None
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@property
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def finished(self) -> bool:
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return self.status == TrainerStatus.FINISHED
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@property
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def stopped(self) -> bool:
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return self.status.stopped
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