From 9c03280ca699dbf9837cdedbc0d93d2c11cc9412 Mon Sep 17 00:00:00 2001 From: xiongxinlei Date: Tue, 19 Apr 2022 21:01:13 +0800 Subject: [PATCH] remove debug info, test=doc --- paddlespeech/s2t/models/u2/u2.py | 7 +------ 1 file changed, 1 insertion(+), 6 deletions(-) diff --git a/paddlespeech/s2t/models/u2/u2.py b/paddlespeech/s2t/models/u2/u2.py index f0d2711d..9b66126e 100644 --- a/paddlespeech/s2t/models/u2/u2.py +++ b/paddlespeech/s2t/models/u2/u2.py @@ -213,14 +213,12 @@ class U2BaseModel(ASRInterface, nn.Layer): num_decoding_left_chunks=num_decoding_left_chunks ) # (B, maxlen, encoder_dim) else: - print("offline decode from the asr") encoder_out, encoder_mask = self.encoder( speech, speech_lengths, decoding_chunk_size=decoding_chunk_size, num_decoding_left_chunks=num_decoding_left_chunks ) # (B, maxlen, encoder_dim) - print("offline decode success") return encoder_out, encoder_mask def recognize( @@ -281,14 +279,13 @@ class U2BaseModel(ASRInterface, nn.Layer): # TODO(Hui Zhang): if end_flag.sum() == running_size: if end_flag.cast(paddle.int64).sum() == running_size: break - + # 2.1 Forward decoder step hyps_mask = subsequent_mask(i).unsqueeze(0).repeat( running_size, 1, 1).to(device) # (B*N, i, i) # logp: (B*N, vocab) logp, cache = self.decoder.forward_one_step( encoder_out, encoder_mask, hyps, hyps_mask, cache) - # 2.2 First beam prune: select topk best prob at current time top_k_logp, top_k_index = logp.topk(beam_size) # (B*N, N) top_k_logp = mask_finished_scores(top_k_logp, end_flag) @@ -708,7 +705,6 @@ class U2BaseModel(ASRInterface, nn.Layer): List[List[int]]: transcripts. """ batch_size = feats.shape[0] - print("start to decode the audio feat") if decoding_method in ['ctc_prefix_beam_search', 'attention_rescoring'] and batch_size > 1: logger.error( @@ -716,7 +712,6 @@ class U2BaseModel(ASRInterface, nn.Layer): ) logger.error(f"current batch_size is {batch_size}") sys.exit(1) - print(f"use the {decoding_method} to decode the audio feat") if decoding_method == 'attention': hyps = self.recognize( feats,