forked from mrq/tortoise-tts
updates chunk size to the chunked tensor length, just in case
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@ -364,6 +364,7 @@ class TextToSpeech:
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print(f"Using method 1: size of best fit: {chunk_size}")
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print(f"Using method 1: size of best fit: {chunk_size}")
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chunks = torch.chunk(concat, int(concat.shape[-1] / chunk_size), dim=1)
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chunks = torch.chunk(concat, int(concat.shape[-1] / chunk_size), dim=1)
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chunk_size = chunks[0].shape[-1]
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# old new behavior:
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# old new behavior:
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# if chunkning tensors: use the smallest voice sample as a common size of best fit
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# if chunkning tensors: use the smallest voice sample as a common size of best fit
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@ -388,6 +389,7 @@ class TextToSpeech:
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chunks.append(s)
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chunks.append(s)
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else:
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else:
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chunks = samples
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chunks = samples
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chunk_size = chunks[0].shape[-1]
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# expand / truncate samples to match the common size
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# expand / truncate samples to match the common size
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# required, as tensors need to be of the same length
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# required, as tensors need to be of the same length
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