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normaliza att_loss with symbols numbers

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yaozengwei 2023-01-15 20:51:18 +08:00
parent 2fc7535de9
commit 2fc4ce2751
2 changed files with 16 additions and 6 deletions
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1
egs/librispeech/ASR/zipformer_ctc_attn/train.py
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@ -711,6 +711,7 @@ def compute_loss(
info["frames"] = (feature_lens // params.subsampling_factor).sum().item() info["frames"] = (feature_lens // params.subsampling_factor).sum().item()
# Note: We use reduction=sum while computing the loss. # Note: We use reduction=sum while computing the loss.
info["symbols"] = sum([len(t) for t in token_ids]) # used to normalize att_loss
info["loss"] = loss.detach().cpu().item() info["loss"] = loss.detach().cpu().item()
info["ctc_loss"] = ctc_loss.detach().cpu().item() info["ctc_loss"] = ctc_loss.detach().cpu().item()
info["att_loss"] = att_loss.detach().cpu().item() info["att_loss"] = att_loss.detach().cpu().item()

21
icefall/utils.py
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@ -844,10 +844,13 @@ class MetricsTracker(collections.defaultdict):
def __str__(self) -> str: def __str__(self) -> str:
ans_frames = "" ans_frames = ""
ans_symbols = ""
ans_utterances = "" ans_utterances = ""
for k, v in self.norm_items(): for k, v in self.norm_items():
norm_value = "%.4g" % v norm_value = "%.4g" % v
if "utt_" not in k: if k == "att_loss":
ans_symbols += str(k) + "=" + str(norm_value) + ", "
elif "utt_" not in k:
ans_frames += str(k) + "=" + str(norm_value) + ", " ans_frames += str(k) + "=" + str(norm_value) + ", "
else: else:
ans_utterances += str(k) + "=" + str(norm_value) ans_utterances += str(k) + "=" + str(norm_value)
@ -859,11 +862,13 @@ class MetricsTracker(collections.defaultdict):
raise ValueError(f"Unexpected key: {k}") raise ValueError(f"Unexpected key: {k}")
frames = "%.2f" % self["frames"] frames = "%.2f" % self["frames"]
ans_frames += "over " + str(frames) + " frames. " ans_frames += "over " + str(frames) + " frames. "
symbols = "%.2f" % self["symbols"]
ans_symbols += "over " + str(symbols) + " symbols. "
if ans_utterances != "": if ans_utterances != "":
utterances = "%.2f" % self["utterances"] utterances = "%.2f" % self["utterances"]
ans_utterances += "over " + str(utterances) + " utterances." ans_utterances += "over " + str(utterances) + " utterances."
return ans_frames + ans_utterances return ans_frames + ans_symbols + ans_utterances
def norm_items(self) -> List[Tuple[str, float]]: def norm_items(self) -> List[Tuple[str, float]]:
""" """
@ -871,14 +876,18 @@ class MetricsTracker(collections.defaultdict):
[('ctc_loss', 0.1), ('att_loss', 0.07)] [('ctc_loss', 0.1), ('att_loss', 0.07)]
""" """
num_frames = self["frames"] if "frames" in self else 1 num_frames = self["frames"] if "frames" in self else 1
num_symbols = self["symbols"] if "symbols" in self else 1
num_utterances = self["utterances"] if "utterances" in self else 1 num_utterances = self["utterances"] if "utterances" in self else 1
ans = [] ans = []
for k, v in self.items(): for k, v in self.items():
if k == "frames" or k == "utterances": if k == "frames" or k == "symbols" or k == "utterances":
continue continue
norm_value = ( if k == "att_loss":
float(v) / num_frames if "utt_" not in k else float(v) / num_utterances norm_value = float(v) / num_symbols
) elif "utt_" in k:
norm_value = float(v) / num_utterances
else:
norm_value = float(v) / num_frames
ans.append((k, norm_value)) ans.append((k, norm_value))
return ans return ans