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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)
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