Fix nv_tacotron_dataset bug which incorrectly mapped filenames
dammit..
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@ -98,9 +98,11 @@ class TextMelCollate():
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text_padded = torch.LongTensor(len(batch), max_input_len)
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text_padded.zero_()
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filenames = []
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for i in range(len(ids_sorted_decreasing)):
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text = batch[ids_sorted_decreasing[i]][0]
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text_padded[i, :text.size(0)] = text
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filenames.append(batch[ids_sorted_decreasing[i]][2])
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# Right zero-pad mel-spec
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num_mels = batch[0][1].size(0)
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@ -121,7 +123,6 @@ class TextMelCollate():
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gate_padded[i, mel.size(1)-1:] = 1
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output_lengths[i] = mel.size(1)
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filenames = [j[2] for j in batch]
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return {
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'padded_text': text_padded,
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@ -97,6 +97,9 @@ class GptTts(nn.Module):
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return mel_seq
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def inference_beam(self, text_inputs):
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pass
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@register_model
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def register_gpt_tts(opt_net, opt):
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@ -63,6 +63,6 @@ if __name__ == "__main__":
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wavfiles = data['filenames']
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quantized = model.eval_state[opt['eval']['quantized_mels']][0]
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for i, wavfile in enumerate(wavfiles):
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qmelfile = wavfile.replace('wavs/', 'quantized_mels/') + '.pth'
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for i, filename in enumerate(wavfiles):
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qmelfile = filename.replace('wavs/', 'quantized_mels/') + '.pth'
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torch.save(quantized[i], os.path.join(outpath, qmelfile))
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