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| from vocoder.models.fatchord_version import WaveRNN | |
| from vocoder.audio import * | |
| def gen_testset(model: WaveRNN, test_set, samples, batched, target, overlap, save_path): | |
| k = model.get_step() // 1000 | |
| for i, (m, x) in enumerate(test_set, 1): | |
| if i > samples: | |
| break | |
| print('\n| Generating: %i/%i' % (i, samples)) | |
| x = x[0].numpy() | |
| bits = 16 if hp.voc_mode == 'MOL' else hp.bits | |
| if hp.mu_law and hp.voc_mode != 'MOL' : | |
| x = decode_mu_law(x, 2**bits, from_labels=True) | |
| else : | |
| x = label_2_float(x, bits) | |
| save_wav(x, save_path.joinpath("%dk_steps_%d_target.wav" % (k, i))) | |
| batch_str = "gen_batched_target%d_overlap%d" % (target, overlap) if batched else \ | |
| "gen_not_batched" | |
| save_str = save_path.joinpath("%dk_steps_%d_%s.wav" % (k, i, batch_str)) | |
| wav = model.generate(m, batched, target, overlap, hp.mu_law) | |
| save_wav(wav, save_str) | |