misc
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@ -438,18 +438,18 @@ 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_cheater_gen.yml', 'generator',
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also_load_savepoint=False,
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load_path='X:\\dlas\\experiments\\train_music_cheater_gen_v5_cosine_40_lyr\\models\\18500_generator_ema.pth'
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load_path='X:\\dlas\\experiments\\train_music_cheater_gen_v5_cosine_40_lyr\\models\\19500_generator.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': 128, # basis: 192
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'conditioning_free': False, 'conditioning_free_k': 1, 'use_ddim': True, 'clip_audio': False,
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'conditioning_free': True, 'conditioning_free_k': 1, 'use_ddim': False, 'clip_audio': False,
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'diffusion_schedule': 'cosine', 'diffusion_type': 'cheater_gen',
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# Slope 1: 1.03x, 2: 1.06, 4: 1.135, 8: 1.27, 16: 1.54
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#'causal': True, 'causal_slope': 4, # DONT FORGET TO INCREMENT THE STEP!
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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': 201, 'device': 'cuda', 'opt': {}}
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env = {'rank': 0, 'base_path': 'D:\\tmp\\test_eval_music', 'step': 204, 'device': 'cuda', 'opt': {}}
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eval = MusicDiffusionFid(diffusion, opt_eval, env)
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fds = []
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for i in range(2):
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@ -122,7 +122,7 @@ class RandomAudioCropInjector(Injector):
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else:
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len = inp.shape[-1]
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margin = len - crop_sz - self.min_buffer
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margin = len - crop_sz - self.min_buffer * 2
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if margin < 0:
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start = self.min_buffer
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else:
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