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@ -52,7 +52,7 @@ class MusicDiffusionFid(evaluator.Evaluator):
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model_var_type='learned_range', loss_type='mse', betas=get_named_beta_schedule('linear', 4000),
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conditioning_free=False, conditioning_free_k=1)
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self.dev = self.env['device']
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mode = opt_get(opt_eval, ['diffusion_type'], 'tts')
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mode = opt_get(opt_eval, ['diffusion_type'], 'spec_decode')
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self.spec_decoder = get_mel2wav_model()
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self.projector = ContrastiveAudio(model_dim=512, transformer_heads=8, dropout=0, encoder_depth=8, mel_channels=256)
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@ -141,7 +141,11 @@ class MusicDiffusionFid(evaluator.Evaluator):
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model_kwargs={'aligned_conditioning': gen_mel_denorm})
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gen_wav = pixel_shuffle_1d(gen_wav, 16)
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return gen_wav, real_resampled, gen_mel, mel_norm, sample_rate
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real_wav = self.spectral_diffuser.p_sample_loop(self.spec_decoder, output_shape,
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model_kwargs={'aligned_conditioning': mel})
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real_wav = pixel_shuffle_1d(real_wav, 16)
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return gen_wav, real_wav.squeeze(0), gen_mel, mel_norm, sample_rate
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def perform_partial_diffusion_from_codes_quant(self, audio, sample_rate=22050, partial_low=0, partial_high=256):
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if sample_rate != sample_rate:
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@ -271,15 +275,15 @@ class MusicDiffusionFid(evaluator.Evaluator):
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if __name__ == '__main__':
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diffusion = load_model_from_config('X:\\dlas\\experiments\\train_music_diffusion_tfd_quant.yml', 'generator',
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also_load_savepoint=False,
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load_path='X:\\dlas\\experiments\\train_music_diffusion_tfd11\\models\\24000_generator_ema.pth'
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load_path='X:\\dlas\\experiments\\train_music_diffusion_tfd12\\models\\41500_generator_ema.pth'
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).cuda()
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opt_eval = {'path': 'Y:\\split\\yt-music-eval', # eval music, mostly electronica. :)
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#'path': 'E:\\music_eval', # this is music from the training dataset, including a lot more variety.
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'diffusion_steps': 200,
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'conditioning_free': False, 'conditioning_free_k': 1,
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'diffusion_schedule': 'cosine', 'diffusion_type': 'from_codes_quant',
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'conditioning_free': True, 'conditioning_free_k': 2,
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'diffusion_schedule': 'linear', 'diffusion_type': 'from_codes_quant',
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#'partial_low': 128, 'partial_high': 192
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}
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env = {'rank': 0, 'base_path': 'D:\\tmp\\test_eval_music', 'step': 600, 'device': 'cuda', 'opt': {}}
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env = {'rank': 0, 'base_path': 'D:\\tmp\\test_eval_music', 'step': 605, 'device': 'cuda', 'opt': {}}
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eval = MusicDiffusionFid(diffusion, opt_eval, env)
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print(eval.perform_eval())
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