diff --git a/egs/reazonspeech/ASR/zipformer/streaming_decode.py b/egs/reazonspeech/ASR/zipformer/streaming_decode.py index 0b58853a30..693c8db1c5 100755 --- a/egs/reazonspeech/ASR/zipformer/streaming_decode.py +++ b/egs/reazonspeech/ASR/zipformer/streaming_decode.py @@ -19,6 +19,7 @@ """ Usage: ./zipformer/streaming_decode.py--epoch 28 --avg 15 --causal 1 --chunk-size 32 --left-context-frames 256 --exp-dir ./zipformer/exp-large --lang data/lang_char --num-encoder-layers 2,2,4,5,4,2 --feedforward-dim 512,768,1536,2048,1536,768 --encoder-dim 192,256,512,768,512,256 --encoder-unmasked-dim 192,192,256,320,256,192 + """ import pdb @@ -456,9 +457,7 @@ def decode_one_chunk( states.append(stream.states) processed_lens.append(stream.done_frames) - print(feature_lens) feature_lens = torch.tensor(feature_lens, device=model.device) - print(feature_lens) features = pad_sequence(features, batch_first=True, padding_value=LOG_EPS) # Make sure the length after encoder_embed is at least 1. @@ -522,7 +521,6 @@ def decode_one_chunk( # finished_streams.append(i) finished_streams.append(i) - print(finished_streams) return finished_streams @@ -618,8 +616,6 @@ def decode_dataset( if num % log_interval == 0: logging.info(f"Cuts processed until now is {num}.") - print("cuts processed finished") - print(len(decode_streams)) # decode final chunks of last sequences while len(decode_streams): # print("INSIDE LEN DECODE STREAMS") @@ -691,9 +687,6 @@ def save_results( params.res_dir / f"errs-{test_set_name}-{key}-{params.suffix}.txt" ) with open(errs_filename, "w") as f: - print("error stats") - print("results") - print(results) wer = write_error_stats( f, f"{test_set_name}-{key}", results, enable_log=True ) @@ -871,8 +864,6 @@ def main(): test_sets = ["valid", "test"] test_cuts = [valid_cuts, test_cuts] - print('test cuts') - print(test_cuts) for test_set, test_cut in zip(test_sets, test_cuts): results_dict = decode_dataset( @@ -882,8 +873,6 @@ def main(): sp=sp, decoding_graph=decoding_graph, ) - print(r"esults_dict") - print(results_dict) save_results( params=params, test_set_name=test_set,