




"""simple docstring"""





import argparse

import torch

from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging


logging.set_verbosity_info()

def 					_UpperCamelCase    (			UpperCamelCase				,       UpperCamelCase				,       UpperCamelCase							)			->			Optional[Any]:


			"""simple docstring"""
			# Construct model
			if gpta_config_file == "":
						__UpperCAmelCase	: Dict		=					GPTaConfig()
			else:
						__UpperCAmelCase	: int		=					GPTaConfig.from_json_file(lowerCAmelCase__							)
			__UpperCAmelCase	: List[str]		=					GPTaModel(lowerCAmelCase__							)

			# Load weights from numpy
			load_tf_weights_in_gpta(lowerCAmelCase__				,       lowerCAmelCase__				,       lowerCAmelCase__							)

			# Save pytorch-model
			__UpperCAmelCase	: Dict		=					pytorch_dump_folder_path + "/" + WEIGHTS_NAME
			__UpperCAmelCase	: Optional[Any]		=					pytorch_dump_folder_path + "/" + CONFIG_NAME
			print(f"Save PyTorch model to {pytorch_weights_dump_path}"							)
			torch.save(model.state_dict()				,       lowerCAmelCase__							)
			print(f"Save configuration file to {pytorch_config_dump_path}"							)
			with open(lowerCAmelCase__				,       "w"				,       encoding="utf-8"							) as f:
						f.write(config.to_json_string()							)


if __name__ == "__main__":
					A   =       argparse.ArgumentParser()
					# Required parameters
					parser.add_argument(
					    """--gpt2_checkpoint_path""", default=None, type=str, required=True, help="""Path to the TensorFlow checkpoint path."""
					)
					parser.add_argument(
					    """--pytorch_dump_folder_path""", default=None, type=str, required=True, help="""Path to the output PyTorch model."""
					)
					parser.add_argument(
					    """--gpt2_config_file""",
					    default="""""",
					    type=str,
					    help=(
					        """An optional config json file corresponding to the pre-trained OpenAI model. \n"""
					        """This specifies the model architecture."""
					    ),
					)
					A   =       parser.parse_args()
					convert_gpta_checkpoint_to_pytorch(args.gpta_checkpoint_path, args.gpta_config_file, args.pytorch_dump_folder_path)








"""simple docstring"""





from math import cos, sin, sqrt, tau

from audio_filters.iir_filter import IIRFilter

def 					_UpperCamelCase    (			UpperCamelCase				,       UpperCamelCase				,       UpperCamelCase = 1 / sqrt(2							)							)			->			IIRFilter:


			"""simple docstring"""
			__UpperCAmelCase	: List[str]		=					tau * frequency / samplerate
			__UpperCAmelCase	: Optional[int]		=					sin(UpperCamelCase							)
			__UpperCAmelCase	: Any		=					cos(UpperCamelCase							)
			__UpperCAmelCase	: Tuple		=					_sin / (2 * q_factor)

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

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

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

def 					_UpperCamelCase    (			UpperCamelCase				,       UpperCamelCase				,       UpperCamelCase = 1 / sqrt(2							)							)			->			IIRFilter:


			"""simple docstring"""
			__UpperCAmelCase	: int		=					tau * frequency / samplerate
			__UpperCAmelCase	: Optional[Any]		=					sin(UpperCamelCase							)
			__UpperCAmelCase	: Dict		=					cos(UpperCamelCase							)
			__UpperCAmelCase	: Tuple		=					_sin / (2 * q_factor)

			__UpperCAmelCase	: Dict		=					(1 + _cos) / 2
			__UpperCAmelCase	: Tuple		=					-1 - _cos

			__UpperCAmelCase	: Any		=					1 + alpha
			__UpperCAmelCase	: int		=					-2 * _cos
			__UpperCAmelCase	: int		=					1 - alpha

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

def 					_UpperCamelCase    (			UpperCamelCase				,       UpperCamelCase				,       UpperCamelCase = 1 / sqrt(2							)							)			->			IIRFilter:


			"""simple docstring"""
			__UpperCAmelCase	: Tuple		=					tau * frequency / samplerate
			__UpperCAmelCase	: Tuple		=					sin(UpperCamelCase							)
			__UpperCAmelCase	: List[str]		=					cos(UpperCamelCase							)
			__UpperCAmelCase	: List[Any]		=					_sin / (2 * q_factor)

			__UpperCAmelCase	: Any		=					_sin / 2
			__UpperCAmelCase	: Optional[int]		=					0
			__UpperCAmelCase	: int		=					-ba

			__UpperCAmelCase	: Dict		=					1 + alpha
			__UpperCAmelCase	: List[str]		=					-2 * _cos
			__UpperCAmelCase	: int		=					1 - alpha

			__UpperCAmelCase	: int		=					IIRFilter(2							)
			filt.set_coefficients([aa, aa, aa]				,       [ba, ba, ba]							)
			return filt

def 					_UpperCamelCase    (			UpperCamelCase				,       UpperCamelCase				,       UpperCamelCase = 1 / sqrt(2							)							)			->			IIRFilter:


			"""simple docstring"""
			__UpperCAmelCase	: str		=					tau * frequency / samplerate
			__UpperCAmelCase	: List[Any]		=					sin(UpperCamelCase							)
			__UpperCAmelCase	: Any		=					cos(UpperCamelCase							)
			__UpperCAmelCase	: List[str]		=					_sin / (2 * q_factor)

			__UpperCAmelCase	: Optional[Any]		=					1 - alpha
			__UpperCAmelCase	: Tuple		=					-2 * _cos
			__UpperCAmelCase	: List[Any]		=					1 + alpha

			__UpperCAmelCase	: str		=					IIRFilter(2							)
			filt.set_coefficients([ba, ba, ba]				,       [ba, ba, ba]							)
			return filt

def 					_UpperCamelCase    (			UpperCamelCase				,       UpperCamelCase				,       UpperCamelCase				,       UpperCamelCase = 1 / sqrt(2							)				,       )			->			IIRFilter:


			"""simple docstring"""
			__UpperCAmelCase	: Dict		=					tau * frequency / samplerate
			__UpperCAmelCase	: Optional[int]		=					sin(UpperCamelCase							)
			__UpperCAmelCase	: Optional[Any]		=					cos(UpperCamelCase							)
			__UpperCAmelCase	: List[Any]		=					_sin / (2 * q_factor)
			__UpperCAmelCase	: List[Any]		=					10 ** (gain_db / 40)

			__UpperCAmelCase	: List[str]		=					1 + alpha * big_a
			__UpperCAmelCase	: Optional[Any]		=					-2 * _cos
			__UpperCAmelCase	: int		=					1 - alpha * big_a
			__UpperCAmelCase	: Optional[int]		=					1 + alpha / big_a
			__UpperCAmelCase	: Union[str, Any]		=					-2 * _cos
			__UpperCAmelCase	: Dict		=					1 - alpha / big_a

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

def 					_UpperCamelCase    (			UpperCamelCase				,       UpperCamelCase				,       UpperCamelCase				,       UpperCamelCase = 1 / sqrt(2							)				,       )			->			IIRFilter:


			"""simple docstring"""
			__UpperCAmelCase	: str		=					tau * frequency / samplerate
			__UpperCAmelCase	: int		=					sin(UpperCamelCase							)
			__UpperCAmelCase	: Optional[Any]		=					cos(UpperCamelCase							)
			__UpperCAmelCase	: str		=					_sin / (2 * q_factor)
			__UpperCAmelCase	: str		=					10 ** (gain_db / 40)
			__UpperCAmelCase	: Union[str, Any]		=					(big_a + 1) - (big_a - 1) * _cos
			__UpperCAmelCase	: Optional[int]		=					(big_a + 1) + (big_a - 1) * _cos
			__UpperCAmelCase	: List[str]		=					(big_a - 1) - (big_a + 1) * _cos
			__UpperCAmelCase	: List[Any]		=					(big_a - 1) + (big_a + 1) * _cos
			__UpperCAmelCase	: Optional[Any]		=					2 * sqrt(UpperCamelCase							) * alpha

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

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





def 					_UpperCamelCase    (			UpperCamelCase				,       UpperCamelCase				,       UpperCamelCase				,       UpperCamelCase = 1 / sqrt(2							)				,       )			->			IIRFilter:


			"""simple docstring"""
			__UpperCAmelCase	: Dict		=					tau * frequency / samplerate
			__UpperCAmelCase	: Optional[int]		=					sin(UpperCamelCase							)
			__UpperCAmelCase	: Dict		=					cos(UpperCamelCase							)
			__UpperCAmelCase	: str		=					_sin / (2 * q_factor)
			__UpperCAmelCase	: int		=					10 ** (gain_db / 40)
			__UpperCAmelCase	: Optional[Any]		=					(big_a + 1) - (big_a - 1) * _cos
			__UpperCAmelCase	: Optional[int]		=					(big_a + 1) + (big_a - 1) * _cos
			__UpperCAmelCase	: Union[str, Any]		=					(big_a - 1) - (big_a + 1) * _cos
			__UpperCAmelCase	: Tuple		=					(big_a - 1) + (big_a + 1) * _cos
			__UpperCAmelCase	: Optional[Any]		=					2 * sqrt(UpperCamelCase							) * alpha

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

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


