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ee3ej6d-e<d.D ]Z=e7e= Z>e,?e> e+D ]uZ@e@\ZAZe,Bej-r&eA. neAZCej-r1eCD ZCeC ZCg ZEeFeCjGd D ]ZHe IeCeHdf dddd"f ZJeEKeLeJ q>eMeEZEeNeAeE d/ O ZPePQ e9k rePQ Z9d0e>iZ:e4d1ePQ   eRejSe: qq	dS dS )3zTSearch a good noise schedule for WaveGrad for a given number of inference iterations    N)product)
DataLoader)tqdm)load_config)AudioProcessor)load_wav_data)WaveGradDataset)setup_model__main__z--model_pathzPath to model checkpoint.)typehelpz--config_pathzPath to model config file.z--data_pathzPath to data directory.z--output_pathz7path for output file including file name and extension.z
--num_iterzRNumber of model inference iterations that you like to optimize noise schedule for.z
--use_cuda
store_truezenable CUDA.)actionr   z--num_samples   z)Number of datasamples used for inference.)r   defaultr   z--search_depth   zISearch granularity. Increasing this increases the run-time exponentially.TF)apitemsseq_lenhop_len	pad_shortconv_padis_trainingreturn_segmentsuse_noise_augment	use_cacheverbose)
batch_sizeshuffle
collate_fn	drop_lastnum_workers
pin_memory
   )sizez > base values: i)numinf)repeat)total   betaz# > Found a better schedule. - MSE:  )T__doc__argparse	itertoolsr   cartesian_productnumpynptorchtorch.utils.datar   r   
TTS.configr   TTS.utils.audior   TTS.vocoder.datasets.preprocessr   %TTS.vocoder.datasets.wavegrad_datasetr   TTS.vocoder.modelsr	   __name__ArgumentParserparseradd_argumentstrint
parse_argsargsconfig_pathconfigaudior   	data_path_
train_datanum_samples
hop_lengthr   r   datasetcollate_full_clipsnum_loader_workersloadermodeluse_cudacudasortedrandomuniformsearch_depthbase_valuesprintlinspacenum_iter	exponentsfloat
best_errorbest_schedulelentotal_search_iterbaser+   compute_noise_leveldatamel	inferencey_hatcpumel_hatrangeshapeimelspectrogrammappend
from_numpystacksummeanmseitemsaveoutput_pathr,   r,   r,   H/home/kuhnn/.local/lib/python3.10/site-packages/TTS/bin/tune_wavegrad.py<module>   s    
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