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Reformatting
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@ -607,19 +607,31 @@ def run(rank, world_size, args):
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valid_dl = librispeech.valid_dataloaders()
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valid_dl = librispeech.valid_dataloaders()
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from lhotse.dataset import find_pessimistic_batches
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from lhotse.dataset import find_pessimistic_batches
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logging.info('Sanity check -- see if any of the batches in epoch 0 would cause OOM.')
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logging.info(
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"Sanity check -- see if any of the batches in epoch 0 would cause OOM."
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)
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batches, crit_values = find_pessimistic_batches(train_dl.sampler)
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batches, crit_values = find_pessimistic_batches(train_dl.sampler)
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for criterion, cuts in batches.items():
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for criterion, cuts in batches.items():
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logging.info(f'* criterion: {criterion} (={crit_values[criterion]}) ...')
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logging.info(
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f"* criterion: {criterion} (={crit_values[criterion]}) ..."
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)
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batch = train_dl.dataset[cuts]
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batch = train_dl.dataset[cuts]
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try:
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try:
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compute_loss(params=params, model=model, batch=batch, graph_compiler=graph_compiler, is_training=True)
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compute_loss(
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logging.info('OK!')
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params=params,
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model=model,
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batch=batch,
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graph_compiler=graph_compiler,
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is_training=True,
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)
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logging.info("OK!")
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except RuntimeError as e:
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except RuntimeError as e:
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if 'CUDA out of memory' in str(e):
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if "CUDA out of memory" in str(e):
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logging.error(
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logging.error(
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'Your GPU ran out of memory with the current max_duration setting. '
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"Your GPU ran out of memory with the current "
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'We recommend decreasing max_duration and trying again.'
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"max_duration setting. We recommend decreasing "
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"max_duration and trying again."
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)
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)
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raise
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raise
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