diff --git a/eval_multiple.py b/eval_multiple.py index 30bf31f..a3bf49f 100644 --- a/eval_multiple.py +++ b/eval_multiple.py @@ -7,7 +7,7 @@ from utils.audio import load_audio if __name__ == '__main__': fname = 'Y:\\libritts\\test-clean\\transcribed-brief-w2v.tsv' - outpath = 'D:\\tmp\\tortoise-tts-eval\\redo_outlier' + outpath = 'D:\\tmp\\tortoise-tts-eval\\attempt_best' outpath_real = 'D:\\tmp\\tortoise-tts-eval\\real' os.makedirs(outpath, exist_ok=True) @@ -24,8 +24,9 @@ if __name__ == '__main__': path = os.path.join(os.path.dirname(fname), line[1]) cond_audio = load_audio(path, 22050) torchaudio.save(os.path.join(outpath_real, os.path.basename(line[1])), cond_audio, 22050) - sample = tts.tts(transcript, [cond_audio, cond_audio], num_autoregressive_samples=256, k=1, diffusion_iterations=200, cond_free=False, - top_k=None, top_p=.95, typical_sampling=False, temperature=.7, length_penalty=.5, repetition_penalty=1) + sample = tts.tts(transcript, [cond_audio, cond_audio], num_autoregressive_samples=512, k=1, + repetition_penalty=2.0, length_penalty=2, temperature=.5, top_p=.5, + diffusion_temperature=.7, cond_free_k=2, diffusion_iterations=400) down = torchaudio.functional.resample(sample, 24000, 22050) fout_path = os.path.join(outpath, os.path.basename(line[1])) torchaudio.save(fout_path, down.squeeze(0), 22050) diff --git a/sweep.py b/sweep.py index 07f9dfc..f62246d 100644 --- a/sweep.py +++ b/sweep.py @@ -25,18 +25,18 @@ def permutations(args): if __name__ == '__main__': fname = 'Y:\\libritts\\test-clean\\transcribed-brief-w2v.tsv' - outpath_base = 'D:\\tmp\\tortoise-tts-eval\\std_sweep_diffusion' + outpath_base = 'D:\\tmp\\tortoise-tts-eval\\std_sweep3' outpath_real = 'D:\\tmp\\tortoise-tts-eval\\real' arg_ranges = { - 'diffusion_temperature': [.5, .7, 1], - 'cond_free_k': [.5, 1, 2], + 'top_p': [.3,.4,.5,.6], + 'temperature': [.5, .6], } cfgs = permutations(arg_ranges) shuffle(cfgs) for cfg in cfgs: - outpath = os.path.join(outpath_base, f'{cfg["cond_free_k"]}_{cfg["diffusion_temperature"]}') + outpath = os.path.join(outpath_base, f'{cfg["top_p"]}_{cfg["temperature"]}') os.makedirs(outpath, exist_ok=True) os.makedirs(outpath_real, exist_ok=True) with open(fname, 'r', encoding='utf-8') as f: @@ -51,8 +51,9 @@ if __name__ == '__main__': path = os.path.join(os.path.dirname(fname), line[1]) cond_audio = load_audio(path, 22050) torchaudio.save(os.path.join(outpath_real, os.path.basename(line[1])), cond_audio, 22050) - sample = tts.tts(transcript, [cond_audio, cond_audio], num_autoregressive_samples=256, k=1, diffusion_iterations=200, cond_free=False, - repetition_penalty=1.5, length_penalty=2, temperature=.9, top_p=.9) + sample = tts.tts(transcript, [cond_audio, cond_audio], num_autoregressive_samples=256, k=1, diffusion_iterations=200, + repetition_penalty=2.0, length_penalty=2, temperature=.5, top_p=.5, + diffusion_temperature=.7, cond_free_k=2, **cfg) down = torchaudio.functional.resample(sample, 24000, 22050) fout_path = os.path.join(outpath, os.path.basename(line[1])) torchaudio.save(fout_path, down.squeeze(0), 22050)