Traceback (most recent call last):


 "preprocess_jb.py", line 59, in <module>

main()


 "preprocess_jb.py", line 34, in main

preprocess_ljspeech(path)


 "preprocess_jb.py", line 19, in preprocess_ljspeech

metadata = ljspeech.build_from_path(in_dir, out_dir)


 "C:\Users\b\Documents\FastSpeech-master\data\ljspeech.py", line 15, in build_from_path

out.append(_process_utterance(out_dir, index, wav_path, text))


 "C:\Users\b\Documents\FastSpeech-master\data\ljspeech.py", line 26, in _process_utterance

mel_spectrogram = Audio.tools.get_mel(wav_path).numpy().astype(np.float32)


 "C:\Users\b\Documents\FastSpeech-master\Audio\tools.py", line 29, in get_mel

melspec = _stft.mel_spectrogram(audio_norm)


 "C:\Users\b\Documents\FastSpeech-master\Audio\stft.py", line 155, in mel_spectrogram

magnitudes, phases = self.stft_fn.transform(y)


 "C:\Users\b\Documents\FastSpeech-master\Audio\stft.py", line 59, in transform

input_data = input_data.view(num_batches, 1, num_samples)
RuntimeError: shape '[1, 1, 47937]' is invalid for input of size 95874

Traceback (most recent call last):


 "scripts/train_model.py", line 490, in <module>

main(args)


 "scripts/train_model.py", line 151, in main

train_loop(args, train_loader, val_loader)


 "scripts/train_model.py", line 239, in train_loop

programs_pred = program_generator.reinforce_sample(questions_var)


 "/home/lxp/CodeBase/VisualReasoning/clevr-iep/iep/models/seq2seq.py", line 182, in reinforce_sample

y[:, t][not_done] = cur_output_data[not_done]
RuntimeError: inconsistent tensor size, expected src [64 x 1] and mask [64 x 64] to have the same number of elements, but got 64 and 4096 elements respectively at /opt/conda/conda-bld/pytorch_1513368888240/work/torch/lib/TH/generic/THTensorMath.c:197
