From cdc26b5e23de8d28ce328a212c8e8a2c3e9449b4 Mon Sep 17 00:00:00 2001 From: James Betker Date: Tue, 29 Mar 2022 13:59:59 -0600 Subject: [PATCH] Add sweeper script for finding optimal generation hyperparameters. --- sweep.py | 61 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 61 insertions(+) create mode 100644 sweep.py diff --git a/sweep.py b/sweep.py new file mode 100644 index 0000000..07f9dfc --- /dev/null +++ b/sweep.py @@ -0,0 +1,61 @@ +import os +from random import shuffle + +import torchaudio + +from api import TextToSpeech +from utils.audio import load_audio + + +def permutations(args): + res = [] + k = next(iter(args.keys())) + vals = args[k] + del args[k] + if not args: + return [{k: v} for v in vals] + lower = permutations(args) + for v in vals: + for l in lower: + lc = l.copy() + lc[k] = v + res.append(lc) + return res + + +if __name__ == '__main__': + fname = 'Y:\\libritts\\test-clean\\transcribed-brief-w2v.tsv' + outpath_base = 'D:\\tmp\\tortoise-tts-eval\\std_sweep_diffusion' + outpath_real = 'D:\\tmp\\tortoise-tts-eval\\real' + + arg_ranges = { + 'diffusion_temperature': [.5, .7, 1], + 'cond_free_k': [.5, 1, 2], + } + cfgs = permutations(arg_ranges) + shuffle(cfgs) + + for cfg in cfgs: + outpath = os.path.join(outpath_base, f'{cfg["cond_free_k"]}_{cfg["diffusion_temperature"]}') + os.makedirs(outpath, exist_ok=True) + os.makedirs(outpath_real, exist_ok=True) + with open(fname, 'r', encoding='utf-8') as f: + lines = [l.strip().split('\t') for l in f.readlines()] + + recorder = open(os.path.join(outpath, 'transcript.tsv'), 'w', encoding='utf-8') + tts = TextToSpeech() + for e, line in enumerate(lines): + transcript = line[0] + if len(transcript) > 120: + continue # We need to support this, but cannot yet. + 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) + 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) + recorder.write(f'{transcript}\t{fout_path}\n') + recorder.flush() + recorder.close() \ No newline at end of file