40 lines
1.3 KiB
Python
40 lines
1.3 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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from typing import Union
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from torch.optim import Optimizer
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from pytorch_lightning.plugins.plugin import LightningPlugin
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class PrecisionPlugin(LightningPlugin):
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"""
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Abstract class to extend for precision support (32/16 etc).
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This is extended to cover any specific logic required for precision support such as AMP/APEX or sharded
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training.
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"""
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def connect(self, model, optimizers):
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raise NotImplementedError
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def training_step(self, fx, args):
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raise NotImplementedError
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def backward(self, closure_loss, optimizer, opt_idx, *args, **kwargs):
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raise NotImplementedError
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def clip_gradients(self, grad_clip_val: Union[int, float], optimizer: Optimizer, norm_type: float):
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raise NotImplementedError
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