



import argparse

from transformers import TaConfig, TaForConditionalGeneration, load_tf_weights_in_ta
from transformers.utils import logging


logging.set_verbosity_info()



def  _lowerCAmelCase     (_lowerCAmelCase ,						_lowerCAmelCase ,						_lowerCAmelCase):
					# Initialise PyTorch model
					UpperCamelCase_			= TaConfig.from_json_file(_lowerCAmelCase)
					print(f"""Building PyTorch model from configuration: {config}""")
					UpperCamelCase_			= TaForConditionalGeneration(_lowerCAmelCase)

					# Load weights from tf checkpoint
					load_tf_weights_in_ta(_lowerCAmelCase ,						_lowerCAmelCase ,						_lowerCAmelCase)

					# Save pytorch-model
					print(f"""Save PyTorch model to {pytorch_dump_path}""")
					model.save_pretrained(_lowerCAmelCase)


if __name__ == "__main__":
	UpperCAmelCase :				Any							=argparse.ArgumentParser()
	# Required parameters
	parser.add_argument(
	    """--tf_checkpoint_path""", default=None, type=str, required=True, help="""Path to the TensorFlow checkpoint path."""
	)
	parser.add_argument(
	    """--config_file""",
	    default=None,
	    type=str,
	    required=True,
	    help=(
	        """The config json file corresponding to the pre-trained T5 model. \nThis specifies the model architecture."""
	    ),
	)
	parser.add_argument(
	    """--pytorch_dump_path""", default=None, type=str, required=True, help="""Path to the output PyTorch model."""
	)
	UpperCAmelCase :				Dict							=parser.parse_args()
	convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.config_file, args.pytorch_dump_path)


"""simple docstring"""

import numpy as np
def 						UpperCAmelCase   (						a_,		a_="utf-8",		a_="surrogatepass"     ):





		'''simple docstring'''


		lowerCamelCase	:     Dict            =       bin(int.from_bytes(text.encode(a_,		a_     ),		'big'     )     )[2:]
		return bits.zfill(8 * ((len(a_     ) + 7) // 8)     )
def 						UpperCAmelCase   (						a_,		a_="utf-8",		a_="surrogatepass"     ):





		'''simple docstring'''


		lowerCamelCase	:     Union[str, Any]            =       int(a_,		2     )
		return n.to_bytes((n.bit_length() + 7) // 8,		'big'     ).decode(a_,		a_     ) or "\0"
def 						UpperCAmelCase   (						a_,		a_     ):





		'''simple docstring'''


		if size_par + len(a_     ) <= 2**size_par - (len(a_     ) - 1):
				raise ValueError('size of parity don\'t match with size of data'     )

		lowerCamelCase	:     Optional[Any]            =       []
		lowerCamelCase	:     Dict            =       []
		lowerCamelCase	:     str            =       [bin(a_     )[2:] for x in range(1,		size_par + len(a_     ) + 1     )]

		# sorted information data for the size of the output data
		lowerCamelCase	:     List[Any]            =       []
		# data position template + parity
		lowerCamelCase	:     Union[str, Any]            =       []
		# parity bit counter
		lowerCamelCase	:     Union[str, Any]            =       0
		# counter position of data bits
		lowerCamelCase	:     str            =       0

		for x in range(1,		size_par + len(a_     ) + 1     ):
				# Performs a template of bit positions - who should be given,
				# and who should be parity
				if qtd_bp < size_par:
						if (np.log(a_     ) / np.log(2     )).is_integer():
								data_out_gab.append('P'     )
								lowerCamelCase	:     int            =       qtd_bp + 1
						else:
								data_out_gab.append('D'     )
				else:
						data_out_gab.append('D'     )

				# Sorts the data to the new output size
				if data_out_gab[-1] == "D":
						data_ord.append(data[cont_data]     )
						cont_data += 1
				else:
						data_ord.append(a_     )

    # Calculates parity
		lowerCamelCase	:     Union[str, Any]            =       0  # parity bit counter
		for bp in range(1,		size_par + 1     ):
				# Bit counter one for a given parity
				lowerCamelCase	:     Optional[int]            =       0
				# counter to control the loop reading
				lowerCamelCase	:     int            =       0
				for x in data_ord:
						if x is not None:
								try:
										lowerCamelCase	:     Optional[int]            =       (bin_pos[cont_loop])[-1 * (bp)]
								except IndexError:
										lowerCamelCase	:     List[Any]            =       '0'
								if aux == "1" and x == "1":
										cont_bo += 1
						cont_loop += 1
				parity.append(cont_bo % 2     )

				qtd_bp += 1

		# Mount the message
		lowerCamelCase	:     Dict            =       0  # parity bit counter
		for x in range(0,		size_par + len(a_     )     ):
				if data_ord[x] is None:
						data_out.append(str(parity[cont_bp]     )     )
						cont_bp += 1
				else:
						data_out.append(data_ord[x]     )

		return data_out
def 						UpperCAmelCase   (						a_,		a_     ):





		'''simple docstring'''


		lowerCamelCase	:     int            =       []
		# Parity bit counter
		lowerCamelCase	:     Optional[Any]            =       0
		# Counter p data bit reading
		lowerCamelCase	:     int            =       0
		# list of parity received
		lowerCamelCase	:     Any            =       []
		lowerCamelCase	:     Optional[int]            =       []

		for x in range(1,		len(a_     ) + 1     ):
				# Performs a template of bit positions - who should be given,
				#  and who should be parity
				if qtd_bp < size_par and (np.log(a_     ) / np.log(2     )).is_integer():
						data_out_gab.append('P'     )
						lowerCamelCase	:     Tuple            =       qtd_bp + 1
				else:
						data_out_gab.append('D'     )

				# Sorts the data to the new output size
				if data_out_gab[-1] == "D":
						data_output.append(data[cont_data]     )
				else:
						parity_received.append(data[cont_data]     )
				cont_data += 1

		# -----------calculates the parity with the data
		lowerCamelCase	:     Tuple            =       []
		lowerCamelCase	:     str            =       []
		lowerCamelCase	:     Optional[Any]            =       [bin(a_     )[2:] for x in range(1,		size_par + len(a_     ) + 1     )]

		#  sorted information data for the size of the output data
		lowerCamelCase	:     Dict            =       []
		# Data position feedback + parity
		lowerCamelCase	:     Union[str, Any]            =       []
		# Parity bit counter
		lowerCamelCase	:     Union[str, Any]            =       0
		# Counter p data bit reading
		lowerCamelCase	:     List[Any]            =       0

		for x in range(1,		size_par + len(a_     ) + 1     ):
				# Performs a template position of bits - who should be given,
				# and who should be parity
				if qtd_bp < size_par and (np.log(a_     ) / np.log(2     )).is_integer():
						data_out_gab.append('P'     )
						lowerCamelCase	:     Any            =       qtd_bp + 1
				else:
						data_out_gab.append('D'     )

				# Sorts the data to the new output size
				if data_out_gab[-1] == "D":
						data_ord.append(data_output[cont_data]     )
						cont_data += 1
				else:
						data_ord.append(a_     )

    # Calculates parity
		lowerCamelCase	:     Optional[int]            =       0  # parity bit counter
		for bp in range(1,		size_par + 1     ):
				# Bit counter one for a certain parity
				lowerCamelCase	:     Tuple            =       0
				# Counter to control loop reading
				lowerCamelCase	:     Any            =       0
				for x in data_ord:
						if x is not None:
								try:
										lowerCamelCase	:     List[str]            =       (bin_pos[cont_loop])[-1 * (bp)]
								except IndexError:
										lowerCamelCase	:     str            =       '0'
								if aux == "1" and x == "1":
										cont_bo += 1
						cont_loop += 1
				parity.append(str(cont_bo % 2     )     )

				qtd_bp += 1

		# Mount the message
		lowerCamelCase	:     Optional[int]            =       0  # Parity bit counter
		for x in range(0,		size_par + len(a_     )     ):
				if data_ord[x] is None:
						data_out.append(str(parity[cont_bp]     )     )
						cont_bp += 1
				else:
						data_out.append(data_ord[x]     )

		lowerCamelCase	:     Any            =       parity_received == parity
		return data_output, ack






