| | |
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| | | import logging |
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| | | from dataclasses import dataclass |
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| | | from typing import Dict |
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| | | from typing import Iterable, Optional |
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| | |
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| | | if len(speech_lengths.size()) > 1: |
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| | | speech_lengths = speech_lengths[:, 0] |
|---|
| | | |
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| | | batch_size = speech.shape[0] |
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| | | batch_size, frames, _ = speech.shape |
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| | | |
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| | | if self.activation_checkpoint: |
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| | | from torch.utils.checkpoint import checkpoint |
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| | |
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| | | stats["acc"] = acc_att |
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| | | stats["loss"] = torch.clone(loss.detach()) |
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| | | stats["batch_size"] = batch_size |
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| | | stats["batch_size_x_frames"] = frames * batch_size |
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| | | stats["batch_size_real_frames"] = speech_lengths.sum().item() |
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| | | stats["padding_frames"] = stats["batch_size_x_frames"] - stats["batch_size_real_frames"] |
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| | | |
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| | | # force_gatherable: to-device and to-tensor if scalar for DataParallel |
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| | | if self.length_normalized_loss: |
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