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Remove memory-allocated printouts

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This commit is contained in:
Daniel Povey 2023-01-12 22:14:52 +08:00
parent bac72718f0
commit 5958f1ee11
1 changed files with 3 additions and 3 deletions
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6
egs/librispeech/ASR/pruned_transducer_stateless7/zipformer.py
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@ -328,11 +328,11 @@ class Zipformer(EncoderInterface):
- lengths, a tensor of shape (batch_size,) containing the number
of frames in `embeddings` before padding.
"""
logging.info(f"Memory allocated at entry: {torch.cuda.memory_allocated() // 1000000}M")
# logging.info(f"Memory allocated at entry: {torch.cuda.memory_allocated() // 1000000}M")
x = self.encoder_embed(x)
logging.info(f"Memory allocated after encoder_embed: {torch.cuda.memory_allocated() // 1000000}M")
# logging.info(f"Memory allocated after encoder_embed: {torch.cuda.memory_allocated() // 1000000}M")
x = x.permute(1, 0, 2) # (N, T, C) -> (T, N, C)
@ -363,7 +363,7 @@ class Zipformer(EncoderInterface):
feature_mask=feature_masks[i],
src_key_padding_mask=None if mask is None else mask[...,::ds])
outputs.append(x)
logging.info(f"Memory allocated after stack {i}: {torch.cuda.memory_allocated() // 1000000}M")
# logging.info(f"Memory allocated after stack {i}: {torch.cuda.memory_allocated() // 1000000}M")
x = self.downsample_output(x)
# class Downsample has this rounding behavior..