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@ -834,6 +834,7 @@ def compute_loss(
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texts = batch["supervisions"]["text"]
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print(texts)
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#texts = batch["greedy pseudo text"]
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token_ids = sp.encode(texts, out_type=int)
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y = k2.RaggedTensor(token_ids).to(device)
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@ -1582,6 +1583,14 @@ def run_adapter(rank, world_size, args, wb=None):
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#train_cuts = librispeech.train_clean_10_cuts(option='male')
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train_cuts = librispeech.test_clean_user(option='big')
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pl_texts = open('/workspace/icefall/egs/librispeech/ASR/tc_big.pl', 'r').readlines()
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pl = {}
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for text in pl_texts:
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text = text.strip().split()
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pl[text[0]] = ' '.join(text[1:])
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print(pl)
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exit()
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def remove_short_and_long_utt(c: Cut):
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return 1.0 <= c.duration <= 20.0
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