From 060117a9ff3eed59d96c1bfa4f0ad3e2082fdac8 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Piotr=20=C5=BBelasko?= Date: Thu, 14 Oct 2021 21:40:14 -0400 Subject: [PATCH] Reformatting --- egs/librispeech/ASR/conformer_ctc/train.py | 26 ++++++++++++++++------ 1 file changed, 19 insertions(+), 7 deletions(-) diff --git a/egs/librispeech/ASR/conformer_ctc/train.py b/egs/librispeech/ASR/conformer_ctc/train.py index 267316691..9d3de020e 100755 --- a/egs/librispeech/ASR/conformer_ctc/train.py +++ b/egs/librispeech/ASR/conformer_ctc/train.py @@ -607,19 +607,31 @@ def run(rank, world_size, args): valid_dl = librispeech.valid_dataloaders() from lhotse.dataset import find_pessimistic_batches - logging.info('Sanity check -- see if any of the batches in epoch 0 would cause OOM.') + + logging.info( + "Sanity check -- see if any of the batches in epoch 0 would cause OOM." + ) batches, crit_values = find_pessimistic_batches(train_dl.sampler) for criterion, cuts in batches.items(): - logging.info(f'* criterion: {criterion} (={crit_values[criterion]}) ...') + logging.info( + f"* criterion: {criterion} (={crit_values[criterion]}) ..." + ) batch = train_dl.dataset[cuts] try: - compute_loss(params=params, model=model, batch=batch, graph_compiler=graph_compiler, is_training=True) - logging.info('OK!') + compute_loss( + params=params, + model=model, + batch=batch, + graph_compiler=graph_compiler, + is_training=True, + ) + logging.info("OK!") except RuntimeError as e: - if 'CUDA out of memory' in str(e): + if "CUDA out of memory" in str(e): logging.error( - 'Your GPU ran out of memory with the current max_duration setting. ' - 'We recommend decreasing max_duration and trying again.' + "Your GPU ran out of memory with the current " + "max_duration setting. We recommend decreasing " + "max_duration and trying again." ) raise