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语帆 2024-02-28 16:56:58 +08:00
parent 12d8bd77a6
commit e59ec16e6a
2 changed files with 1 additions and 9 deletions
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2
funasr/auto/auto_model.py
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@ -234,11 +234,9 @@ class AutoModel:
time1 = time.perf_counter()
with torch.no_grad():
pdb.set_trace()
results, meta_data = model.inference(**batch, **kwargs)
time2 = time.perf_counter()
pdb.set_trace()
asr_result_list.extend(results)
# batch_data_time = time_per_frame_s * data_batch_i["speech_lengths"].sum().item()

8
funasr/models/lcbnet/model.py
View File

@ -181,8 +181,7 @@ class LCBNet(nn.Module):
text: (Batch, Length)
text_lengths: (Batch,)
"""
# import pdb;
# pdb.set_trace()
if len(text_lengths.size()) > 1:
text_lengths = text_lengths[:, 0]
if len(speech_lengths.size()) > 1:
@ -449,7 +448,6 @@ class LCBNet(nn.Module):
ocr, ocr_lens, _ = self.text_encoder(ocr, ocr_lengths)
fusion_out, _, _, _ = self.fusion_encoder(encoder_out,None, ocr, None)
encoder_out = encoder_out + fusion_out
pdb.set_trace()
# c. Passed the encoder result and the beam search
nbest_hyps = self.beam_search(
x=encoder_out[0], maxlenratio=kwargs.get("maxlenratio", 0.0), minlenratio=kwargs.get("minlenratio", 0.0)
@ -457,7 +455,6 @@ class LCBNet(nn.Module):
nbest_hyps = nbest_hyps[: self.nbest]
pdb.set_trace()
results = []
b, n, d = encoder_out.size()
for i in range(b):
@ -479,12 +476,9 @@ class LCBNet(nn.Module):
# remove blank symbol id, which is assumed to be 0
token_int = list(filter(lambda x: x != self.eos and x != self.sos and x != self.blank_id, token_int))
pdb.set_trace()
# Change integer-ids to tokens
token = tokenizer.ids2tokens(token_int)
pdb.set_trace()
text = tokenizer.tokens2text(token)
pdb.set_trace()
text_postprocessed, _ = postprocess_utils.sentence_postprocess(token)
result_i = {"key": key[i], "token": token, "text": text_postprocessed}