57 lines
1.8 KiB
Python
57 lines
1.8 KiB
Python
# 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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import contextlib
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import torch
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class Plugin(object):
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"""Basic Plugin class to derive precision and training type plugins from."""
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def connect(self, model: torch.nn.Module, *args, **kwargs):
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"""Connects the plugin with the accelerator (and thereby with trainer and model).
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Will be called by the accelerator.
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"""
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pass
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def pre_optimizer_step(self, optimizer: torch.optim.Optimizer, optimizer_idx: int):
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"""Hook to do something before each optimizer step."""
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pass
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def post_optimizer_step(self, optimizer: torch.optim.Optimizer, optimizer_idx: int):
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"""Hook to do something after each optimizer step."""
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pass
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def pre_training(self):
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"""Hook to do something before the training starts."""
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pass
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def post_training(self):
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"""Hook to do something after the training finishes."""
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pass
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@contextlib.contextmanager
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def train_step_context(self):
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"""A contextmanager for the trainstep"""
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yield
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@contextlib.contextmanager
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def val_step_context(self):
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"""A contextmanager for the validation step"""
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yield
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@contextlib.contextmanager
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def test_step_context(self):
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"""A contextmanager for the teststep"""
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yield |