41 lines
1.4 KiB
Python
41 lines
1.4 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 operate on metric values. """
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import torch
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from pytorch_lightning.utilities.exceptions import MisconfigurationException
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def metrics_to_scalars(metrics: dict) -> dict:
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""" Recursively walk through a dictionary of metrics and convert single-item tensors to scalar values. """
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# TODO: this is duplicated in MetricsHolder. should be unified
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new_metrics = {}
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for k, v in metrics.items():
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if isinstance(v, torch.Tensor):
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if v.numel() != 1:
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raise MisconfigurationException(
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f"The metric `{k}` does not contain a single element"
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f" thus it cannot be converted to float. Found `{v}`"
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)
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v = v.item()
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if isinstance(v, dict):
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v = metrics_to_scalars(v)
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new_metrics[k] = v
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return new_metrics
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