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78 lines
2.0 KiB
Python
78 lines
2.0 KiB
Python
# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
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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 contextlib import contextmanager
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from torch.nn import Module
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from nemo.core.classes.common import FileIO, Serialization, Typing
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__all__ = ['NeuralModule']
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class NeuralModule(Module, Typing, Serialization, FileIO):
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"""
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Abstract class offering interface shared between all PyTorch Neural Modules.
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"""
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@property
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def num_weights(self):
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"""
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Utility property that returns the total number of parameters of NeuralModule.
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"""
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num: int = 0
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for p in self.parameters():
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if p.requires_grad:
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num += p.numel()
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return num
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def input_example(self):
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"""
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Override this method if random inputs won't work
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Returns:
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A tuple sample of valid input data.
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"""
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return
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def freeze(self) -> None:
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r"""
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Freeze all params for inference.
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"""
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for param in self.parameters():
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param.requires_grad = False
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self.eval()
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def unfreeze(self) -> None:
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"""
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Unfreeze all parameters for training.
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"""
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for param in self.parameters():
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param.requires_grad = True
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self.train()
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@contextmanager
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def as_frozen(self):
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"""
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Context manager which temporarily freezes a module, yields control and finally unfreezes the module.
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"""
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self.freeze()
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try:
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yield
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finally:
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self.unfreeze()
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