40 lines
1.5 KiB
Python
40 lines
1.5 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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"""Helper functions to detect NaN/Inf values. """
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import logging
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import torch
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import torch.nn as nn
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log = logging.getLogger(__name__)
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def print_nan_gradients(model: nn.Module) -> None:
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""" Iterates over model parameters and prints out parameter + gradient information if NaN. """
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for param in model.parameters():
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if (param.grad is not None) and torch.isnan(param.grad.float()).any():
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log.info(param, param.grad)
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def detect_nan_parameters(model: nn.Module) -> None:
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""" Iterates over model parameters and prints gradients if any parameter is not finite. """
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for name, param in model.named_parameters():
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if not torch.isfinite(param).all():
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print_nan_gradients(model)
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raise ValueError(
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f'Detected nan and/or inf values in `{name}`.'
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' Check your forward pass for numerically unstable operations.'
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)
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