param improvements from investigation
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@ -7,7 +7,7 @@ from utils.audio import load_audio
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if __name__ == '__main__':
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if __name__ == '__main__':
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fname = 'Y:\\libritts\\test-clean\\transcribed-brief-w2v.tsv'
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fname = 'Y:\\libritts\\test-clean\\transcribed-brief-w2v.tsv'
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outpath = 'D:\\tmp\\tortoise-tts-eval\\redo_outlier'
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outpath = 'D:\\tmp\\tortoise-tts-eval\\attempt_best'
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outpath_real = 'D:\\tmp\\tortoise-tts-eval\\real'
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outpath_real = 'D:\\tmp\\tortoise-tts-eval\\real'
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os.makedirs(outpath, exist_ok=True)
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os.makedirs(outpath, exist_ok=True)
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@ -24,8 +24,9 @@ if __name__ == '__main__':
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path = os.path.join(os.path.dirname(fname), line[1])
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path = os.path.join(os.path.dirname(fname), line[1])
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cond_audio = load_audio(path, 22050)
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cond_audio = load_audio(path, 22050)
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torchaudio.save(os.path.join(outpath_real, os.path.basename(line[1])), cond_audio, 22050)
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torchaudio.save(os.path.join(outpath_real, os.path.basename(line[1])), cond_audio, 22050)
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sample = tts.tts(transcript, [cond_audio, cond_audio], num_autoregressive_samples=256, k=1, diffusion_iterations=200, cond_free=False,
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sample = tts.tts(transcript, [cond_audio, cond_audio], num_autoregressive_samples=512, k=1,
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top_k=None, top_p=.95, typical_sampling=False, temperature=.7, length_penalty=.5, repetition_penalty=1)
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repetition_penalty=2.0, length_penalty=2, temperature=.5, top_p=.5,
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diffusion_temperature=.7, cond_free_k=2, diffusion_iterations=400)
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down = torchaudio.functional.resample(sample, 24000, 22050)
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down = torchaudio.functional.resample(sample, 24000, 22050)
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fout_path = os.path.join(outpath, os.path.basename(line[1]))
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fout_path = os.path.join(outpath, os.path.basename(line[1]))
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torchaudio.save(fout_path, down.squeeze(0), 22050)
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torchaudio.save(fout_path, down.squeeze(0), 22050)
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13
sweep.py
13
sweep.py
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@ -25,18 +25,18 @@ def permutations(args):
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if __name__ == '__main__':
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if __name__ == '__main__':
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fname = 'Y:\\libritts\\test-clean\\transcribed-brief-w2v.tsv'
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fname = 'Y:\\libritts\\test-clean\\transcribed-brief-w2v.tsv'
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outpath_base = 'D:\\tmp\\tortoise-tts-eval\\std_sweep_diffusion'
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outpath_base = 'D:\\tmp\\tortoise-tts-eval\\std_sweep3'
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outpath_real = 'D:\\tmp\\tortoise-tts-eval\\real'
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outpath_real = 'D:\\tmp\\tortoise-tts-eval\\real'
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arg_ranges = {
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arg_ranges = {
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'diffusion_temperature': [.5, .7, 1],
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'top_p': [.3,.4,.5,.6],
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'cond_free_k': [.5, 1, 2],
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'temperature': [.5, .6],
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}
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}
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cfgs = permutations(arg_ranges)
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cfgs = permutations(arg_ranges)
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shuffle(cfgs)
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shuffle(cfgs)
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for cfg in cfgs:
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for cfg in cfgs:
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outpath = os.path.join(outpath_base, f'{cfg["cond_free_k"]}_{cfg["diffusion_temperature"]}')
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outpath = os.path.join(outpath_base, f'{cfg["top_p"]}_{cfg["temperature"]}')
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os.makedirs(outpath, exist_ok=True)
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os.makedirs(outpath, exist_ok=True)
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os.makedirs(outpath_real, exist_ok=True)
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os.makedirs(outpath_real, exist_ok=True)
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with open(fname, 'r', encoding='utf-8') as f:
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with open(fname, 'r', encoding='utf-8') as f:
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@ -51,8 +51,9 @@ if __name__ == '__main__':
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path = os.path.join(os.path.dirname(fname), line[1])
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path = os.path.join(os.path.dirname(fname), line[1])
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cond_audio = load_audio(path, 22050)
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cond_audio = load_audio(path, 22050)
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torchaudio.save(os.path.join(outpath_real, os.path.basename(line[1])), cond_audio, 22050)
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torchaudio.save(os.path.join(outpath_real, os.path.basename(line[1])), cond_audio, 22050)
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sample = tts.tts(transcript, [cond_audio, cond_audio], num_autoregressive_samples=256, k=1, diffusion_iterations=200, cond_free=False,
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sample = tts.tts(transcript, [cond_audio, cond_audio], num_autoregressive_samples=256, k=1, diffusion_iterations=200,
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repetition_penalty=1.5, length_penalty=2, temperature=.9, top_p=.9)
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repetition_penalty=2.0, length_penalty=2, temperature=.5, top_p=.5,
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diffusion_temperature=.7, cond_free_k=2, **cfg)
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down = torchaudio.functional.resample(sample, 24000, 22050)
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down = torchaudio.functional.resample(sample, 24000, 22050)
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fout_path = os.path.join(outpath, os.path.basename(line[1]))
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fout_path = os.path.join(outpath, os.path.basename(line[1]))
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torchaudio.save(fout_path, down.squeeze(0), 22050)
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torchaudio.save(fout_path, down.squeeze(0), 22050)
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