
import argparse

import numpy as np
import torch

from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging


logging.set_verbosity_info()
_UpperCAmelCase					: str      =       logging.get_logger("transformers.models.speecht5")


def       A       (					lowercase    ,       lowercase    ,       lowercase )   ->  int:
		'''simple docstring'''

		hf_model.apply_weight_norm()

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

		for i in range(len(config.upsample_rates ) ):
				UpperCamelCase		=     checkpoint[f'''upsamples.{i}.1.weight_g''']
				UpperCamelCase		=     checkpoint[f'''upsamples.{i}.1.weight_v''']
				UpperCamelCase		=     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 ) ):
						UpperCamelCase		=     checkpoint[f'''blocks.{i}.convs1.{j}.1.weight_g''']
						UpperCamelCase		=     checkpoint[f'''blocks.{i}.convs1.{j}.1.weight_v''']
						UpperCamelCase		=     checkpoint[f'''blocks.{i}.convs1.{j}.1.bias''']

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

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

		hf_model.remove_weight_norm()


@torch.no_grad()
def       A       (					lowercase    ,       lowercase    ,       lowercase    ,       lowercase=None    ,       lowercase=None    ,       )   ->  Optional[Any]:
		'''simple docstring'''

		if config_path is not None:
				UpperCamelCase		=     SpeechTaHifiGanConfig.from_pretrained(__lowerCamelCase )
		else:
				UpperCamelCase		=     SpeechTaHifiGanConfig()

		UpperCamelCase		=     SpeechTaHifiGan(__lowerCamelCase )

		UpperCamelCase		=     torch.load(__lowerCamelCase )
		load_weights(orig_checkpoint['model']['generator']    ,       __lowerCamelCase    ,       __lowerCamelCase )

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

		model.save_pretrained(__lowerCamelCase )

		if repo_id:
				print('Pushing to the hub...' )
				model.push_to_hub(__lowerCamelCase )


if __name__ == "__main__":
					_UpperCAmelCase					: Dict      =       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."
					)

					_UpperCAmelCase					: Dict      =       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"""





from math import cos, sin, sqrt, tau

from audio_filters.iir_filter import IIRFilter







def 	__a     (		__lowerCamelCase,		__lowerCamelCase,		__lowerCamelCase = 1 / sqrt(2  )  ):
   UpperCAmelCase_					:					int			     =    tau * frequency / samplerate
   UpperCAmelCase_					:					List[str]			     =    sin(__lowerCamelCase  )
   UpperCAmelCase_					:					int			     =    cos(__lowerCamelCase  )
   UpperCAmelCase_					:					Optional[Any]			     =    _sin / (2 * q_factor)

   UpperCAmelCase_					:					int			     =    (1 - _cos) / 2
   UpperCAmelCase_					:					Optional[Any]			     =    1 - _cos

   UpperCAmelCase_					:					int			     =    1 + alpha
   UpperCAmelCase_					:					Dict			     =    -2 * _cos
   UpperCAmelCase_					:					Tuple			     =    1 - alpha

   UpperCAmelCase_					:					Dict			     =    IIRFilter(2  )
   filt.set_coefficients([aa, aa, aa],		[ba, ba, ba]  )
   return filt







def 	__a     (		__lowerCamelCase,		__lowerCamelCase,		__lowerCamelCase = 1 / sqrt(2  )  ):
   UpperCAmelCase_					:					Dict			     =    tau * frequency / samplerate
   UpperCAmelCase_					:					Tuple			     =    sin(__lowerCamelCase  )
   UpperCAmelCase_					:					Any			     =    cos(__lowerCamelCase  )
   UpperCAmelCase_					:					List[str]			     =    _sin / (2 * q_factor)

   UpperCAmelCase_					:					List[Any]			     =    (1 + _cos) / 2
   UpperCAmelCase_					:					Optional[int]			     =    -1 - _cos

   UpperCAmelCase_					:					Union[str, Any]			     =    1 + alpha
   UpperCAmelCase_					:					Optional[int]			     =    -2 * _cos
   UpperCAmelCase_					:					Tuple			     =    1 - alpha

   UpperCAmelCase_					:					List[str]			     =    IIRFilter(2  )
   filt.set_coefficients([aa, aa, aa],		[ba, ba, ba]  )
   return filt







def 	__a     (		__lowerCamelCase,		__lowerCamelCase,		__lowerCamelCase = 1 / sqrt(2  )  ):
   UpperCAmelCase_					:					Union[str, Any]			     =    tau * frequency / samplerate
   UpperCAmelCase_					:					str			     =    sin(__lowerCamelCase  )
   UpperCAmelCase_					:					Tuple			     =    cos(__lowerCamelCase  )
   UpperCAmelCase_					:					List[Any]			     =    _sin / (2 * q_factor)

   UpperCAmelCase_					:					Any			     =    _sin / 2
   UpperCAmelCase_					:					Union[str, Any]			     =    0
   UpperCAmelCase_					:					Tuple			     =    -ba

   UpperCAmelCase_					:					Optional[Any]			     =    1 + alpha
   UpperCAmelCase_					:					Dict			     =    -2 * _cos
   UpperCAmelCase_					:					Optional[int]			     =    1 - alpha

   UpperCAmelCase_					:					List[str]			     =    IIRFilter(2  )
   filt.set_coefficients([aa, aa, aa],		[ba, ba, ba]  )
   return filt







def 	__a     (		__lowerCamelCase,		__lowerCamelCase,		__lowerCamelCase = 1 / sqrt(2  )  ):
   UpperCAmelCase_					:					Any			     =    tau * frequency / samplerate
   UpperCAmelCase_					:					Any			     =    sin(__lowerCamelCase  )
   UpperCAmelCase_					:					Optional[int]			     =    cos(__lowerCamelCase  )
   UpperCAmelCase_					:					str			     =    _sin / (2 * q_factor)

   UpperCAmelCase_					:					List[str]			     =    1 - alpha
   UpperCAmelCase_					:					str			     =    -2 * _cos
   UpperCAmelCase_					:					Any			     =    1 + alpha

   UpperCAmelCase_					:					Tuple			     =    IIRFilter(2  )
   filt.set_coefficients([ba, ba, ba],		[ba, ba, ba]  )
   return filt







def 	__a     (		__lowerCamelCase,		__lowerCamelCase,		__lowerCamelCase,		__lowerCamelCase = 1 / sqrt(2  ),		):
   UpperCAmelCase_					:					Dict			     =    tau * frequency / samplerate
   UpperCAmelCase_					:					Union[str, Any]			     =    sin(__lowerCamelCase  )
   UpperCAmelCase_					:					int			     =    cos(__lowerCamelCase  )
   UpperCAmelCase_					:					Optional[int]			     =    _sin / (2 * q_factor)
   UpperCAmelCase_					:					List[str]			     =    10 ** (gain_db / 40)

   UpperCAmelCase_					:					List[Any]			     =    1 + alpha * big_a
   UpperCAmelCase_					:					Tuple			     =    -2 * _cos
   UpperCAmelCase_					:					Tuple			     =    1 - alpha * big_a
   UpperCAmelCase_					:					str			     =    1 + alpha / big_a
   UpperCAmelCase_					:					List[str]			     =    -2 * _cos
   UpperCAmelCase_					:					List[str]			     =    1 - alpha / big_a

   UpperCAmelCase_					:					Tuple			     =    IIRFilter(2  )
   filt.set_coefficients([aa, aa, aa],		[ba, ba, ba]  )
   return filt







def 	__a     (		__lowerCamelCase,		__lowerCamelCase,		__lowerCamelCase,		__lowerCamelCase = 1 / sqrt(2  ),		):
   UpperCAmelCase_					:					str			     =    tau * frequency / samplerate
   UpperCAmelCase_					:					int			     =    sin(__lowerCamelCase  )
   UpperCAmelCase_					:					Optional[Any]			     =    cos(__lowerCamelCase  )
   UpperCAmelCase_					:					Tuple			     =    _sin / (2 * q_factor)
   UpperCAmelCase_					:					List[Any]			     =    10 ** (gain_db / 40)
   UpperCAmelCase_					:					Tuple			     =    (big_a + 1) - (big_a - 1) * _cos
   UpperCAmelCase_					:					int			     =    (big_a + 1) + (big_a - 1) * _cos
   UpperCAmelCase_					:					Optional[Any]			     =    (big_a - 1) - (big_a + 1) * _cos
   UpperCAmelCase_					:					Optional[int]			     =    (big_a - 1) + (big_a + 1) * _cos
   UpperCAmelCase_					:					Dict			     =    2 * sqrt(__lowerCamelCase  ) * alpha

   UpperCAmelCase_					:					List[str]			     =    big_a * (pmc + aaa)
   UpperCAmelCase_					:					int			     =    2 * big_a * mpc
   UpperCAmelCase_					:					int			     =    big_a * (pmc - aaa)
   UpperCAmelCase_					:					Dict			     =    ppmc + aaa
   UpperCAmelCase_					:					Any			     =    -2 * pmpc
   UpperCAmelCase_					:					List[str]			     =    ppmc - aaa

   UpperCAmelCase_					:					List[Any]			     =    IIRFilter(2  )
   filt.set_coefficients([aa, aa, aa],		[ba, ba, ba]  )
   return filt







def 	__a     (		__lowerCamelCase,		__lowerCamelCase,		__lowerCamelCase,		__lowerCamelCase = 1 / sqrt(2  ),		):
   UpperCAmelCase_					:					int			     =    tau * frequency / samplerate
   UpperCAmelCase_					:					Optional[Any]			     =    sin(__lowerCamelCase  )
   UpperCAmelCase_					:					Optional[Any]			     =    cos(__lowerCamelCase  )
   UpperCAmelCase_					:					Optional[Any]			     =    _sin / (2 * q_factor)
   UpperCAmelCase_					:					Tuple			     =    10 ** (gain_db / 40)
   UpperCAmelCase_					:					Tuple			     =    (big_a + 1) - (big_a - 1) * _cos
   UpperCAmelCase_					:					Optional[Any]			     =    (big_a + 1) + (big_a - 1) * _cos
   UpperCAmelCase_					:					List[Any]			     =    (big_a - 1) - (big_a + 1) * _cos
   UpperCAmelCase_					:					Any			     =    (big_a - 1) + (big_a + 1) * _cos
   UpperCAmelCase_					:					Dict			     =    2 * sqrt(__lowerCamelCase  ) * alpha

   UpperCAmelCase_					:					Any			     =    big_a * (ppmc + aaa)
   UpperCAmelCase_					:					Union[str, Any]			     =    -2 * big_a * pmpc
   UpperCAmelCase_					:					Dict			     =    big_a * (ppmc - aaa)
   UpperCAmelCase_					:					Optional[int]			     =    pmc + aaa
   UpperCAmelCase_					:					Union[str, Any]			     =    2 * mpc
   UpperCAmelCase_					:					int			     =    pmc - aaa

   UpperCAmelCase_					:					Union[str, Any]			     =    IIRFilter(2  )
   filt.set_coefficients([aa, aa, aa],		[ba, ba, ba]  )
   return filt


