import os

import torchaudio

from api import TextToSpeech
from utils.audio import load_audio

if __name__ == '__main__':
    fname = 'Y:\\clips\\books2\\subset512-oco.tsv'
    stop_after = 128
    outpath_base = 'D:\\tmp\\tortoise-tts-eval\\audiobooks'
    outpath_real = 'D:\\tmp\\tortoise-tts-eval\\real'

    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()]

    tts = TextToSpeech()
    for k in range(4):
        outpath = f'{outpath_base}_{k}'
        os.makedirs(outpath, exist_ok=True)
        recorder = open(os.path.join(outpath, 'transcript.tsv'), 'w', encoding='utf-8')
        for e, line in enumerate(lines):
            if e >= stop_after:
                break
            transcript = line[0]
            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=128, k=1,
                                 repetition_penalty=2.0, length_penalty=2, temperature=.5, top_p=.5,
                                 diffusion_temperature=.7, cond_free_k=2, diffusion_iterations=70)

            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()