"""simple docstring"""




import argparse

import numpy as np
import torch

from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging


logging.set_verbosity_info()
__lowerCAmelCase    :							List[Any]													=						logging.get_logger("transformers.models.speecht5")


def 							_UpperCAmelCase		(       lowerCamelCase__			,  lowerCamelCase__			,  lowerCamelCase__     ):





		"""simple docstring"""




		hf_model.apply_weight_norm()

		lowerCAmelCase__        =   checkpoint["""input_conv.weight_g"""]
		lowerCAmelCase__        =   checkpoint["""input_conv.weight_v"""]
		lowerCAmelCase__        =   checkpoint["""input_conv.bias"""]

		for i in range(len(config.upsample_rates     )     ):
				lowerCAmelCase__        =   checkpoint[f"""upsamples.{i}.1.weight_g"""]
				lowerCAmelCase__        =   checkpoint[f"""upsamples.{i}.1.weight_v"""]
				lowerCAmelCase__        =   checkpoint[f"""upsamples.{i}.1.bias"""]

		for i in range(len(config.upsample_rates     ) * len(config.resblock_kernel_sizes     )     ):
				for j in range(len(config.resblock_dilation_sizes     )     ):
						lowerCAmelCase__        =   checkpoint[f"""blocks.{i}.convs1.{j}.1.weight_g"""]
						lowerCAmelCase__        =   checkpoint[f"""blocks.{i}.convs1.{j}.1.weight_v"""]
						lowerCAmelCase__        =   checkpoint[f"""blocks.{i}.convs1.{j}.1.bias"""]

						lowerCAmelCase__        =   checkpoint[f"""blocks.{i}.convs2.{j}.1.weight_g"""]
						lowerCAmelCase__        =   checkpoint[f"""blocks.{i}.convs2.{j}.1.weight_v"""]
						lowerCAmelCase__        =   checkpoint[f"""blocks.{i}.convs2.{j}.1.bias"""]

		lowerCAmelCase__        =   checkpoint["""output_conv.1.weight_g"""]
		lowerCAmelCase__        =   checkpoint["""output_conv.1.weight_v"""]
		lowerCAmelCase__        =   checkpoint["""output_conv.1.bias"""]

		hf_model.remove_weight_norm()


@torch.no_grad()
def 							_UpperCAmelCase		(       lowerCamelCase__			,  lowerCamelCase__			,  lowerCamelCase__			,  lowerCamelCase__=None			,  lowerCamelCase__=None			,  ):





		"""simple docstring"""




		if config_path is not None:
				lowerCAmelCase__        =   SpeechTaHifiGanConfig.from_pretrained(UpperCAmelCase__     )
		else:
				lowerCAmelCase__        =   SpeechTaHifiGanConfig()

		lowerCAmelCase__        =   SpeechTaHifiGan(UpperCAmelCase__     )

		lowerCAmelCase__        =   torch.load(UpperCAmelCase__     )
		load_weights(orig_checkpoint["""model"""]["""generator"""]			,  UpperCAmelCase__			,  UpperCAmelCase__     )

		lowerCAmelCase__        =   np.load(UpperCAmelCase__     )
		lowerCAmelCase__        =   stats[0].reshape(-1     )
		lowerCAmelCase__        =   stats[1].reshape(-1     )
		lowerCAmelCase__        =   torch.from_numpy(UpperCAmelCase__     ).float()
		lowerCAmelCase__        =   torch.from_numpy(UpperCAmelCase__     ).float()

		model.save_pretrained(UpperCAmelCase__     )

		if repo_id:
				print("""Pushing to the hub..."""     )
				model.push_to_hub(UpperCAmelCase__     )


if __name__ == "__main__":
			__lowerCAmelCase    :							List[Any]													=						argparse.ArgumentParser()
			parser.add_argument("--checkpoint_path", required=True, default=None, type=str, help="Path to original checkpoint")
			parser.add_argument("--stats_path", required=True, default=None, type=str, help="Path to stats.npy file")
			parser.add_argument("--config_path", default=None, type=str, help="Path to hf config.json of model to convert")
			parser.add_argument(
			    "--pytorch_dump_folder_path", required=True, default=None, type=str, help="Path to the output PyTorch model."
			)
			parser.add_argument(
			    "--push_to_hub", default=None, type=str, help="Where to upload the converted model on the 🤗 hub."
			)

			__lowerCAmelCase    :							Union[str, Any]													=						parser.parse_args()
			convert_hifigan_checkpoint(
			    args.checkpoint_path,
			    args.stats_path,
			    args.pytorch_dump_folder_path,
			    args.config_path,
			    args.push_to_hub,
			)





"""simple docstring"""




def 							_UpperCAmelCase		(       lowerCamelCase__			,  lowerCamelCase__     ):





		"""simple docstring"""




		while b:
				lowerCAmelCase__   ,					lowerCAmelCase__        =   b, a % b
		return a







def 							_UpperCAmelCase		(       lowerCamelCase__			,  lowerCamelCase__     ):





		"""simple docstring"""




		return a if b == 0 else euclidean_gcd_recursive(lowerCamelCase__			,  a % b     )







def 							_UpperCAmelCase		(       ):





		"""simple docstring"""




		print(f"""euclidean_gcd(3, 5) = {euclidean_gcd(3			,  5     )}"""     )
		print(f"""euclidean_gcd(5, 3) = {euclidean_gcd(5			,  3     )}"""     )
		print(f"""euclidean_gcd(1, 3) = {euclidean_gcd(1			,  3     )}"""     )
		print(f"""euclidean_gcd(3, 6) = {euclidean_gcd(3			,  6     )}"""     )
		print(f"""euclidean_gcd(6, 3) = {euclidean_gcd(6			,  3     )}"""     )

		print(f"""euclidean_gcd_recursive(3, 5) = {euclidean_gcd_recursive(3			,  5     )}"""     )
		print(f"""euclidean_gcd_recursive(5, 3) = {euclidean_gcd_recursive(5			,  3     )}"""     )
		print(f"""euclidean_gcd_recursive(1, 3) = {euclidean_gcd_recursive(1			,  3     )}"""     )
		print(f"""euclidean_gcd_recursive(3, 6) = {euclidean_gcd_recursive(3			,  6     )}"""     )
		print(f"""euclidean_gcd_recursive(6, 3) = {euclidean_gcd_recursive(6			,  3     )}"""     )


if __name__ == "__main__":
			main()




