





'''simple docstring'''


import argparse

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


logging.set_verbosity_info()




def    __a (     UpperCAmelCase       ,			UpperCAmelCase       ,			UpperCAmelCase    )      ->Optional[int]:



	"""simple docstring"""







	A							  =      TaConfig.from_json_file(UpperCAmelCase    )
	print(f"""Building PyTorch model from configuration: {config}"""    )
	A							  =      TaForConditionalGeneration(UpperCAmelCase    )

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

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


if __name__ == "__main__":
				_lowerCamelCase				:	List[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.'
				)
				_lowerCamelCase				:	Optional[int]				    =       parser.parse_args()
				convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.config_file, args.pytorch_dump_path)








'''simple docstring'''


class 							__UpperCAmelCase  :







		'''simple docstring'''







		def __init__(self						:      List[str]      ):
			# numbermap keys are the number and its values are lists of indexes sorted
			# in ascending order
			A							  =      {}
			# indexmap keys are an index and it's values are the number at that index
			A							  =      {}







		def        A     (self						:      Union[str, Any]      ,      _lowerCAmelCase						:      list | str | range      ,      _lowerCAmelCase						:      int      ):
			if isinstance(_lowerCAmelCase      ,      (range, str)      ):
				A							  =      list(_lowerCAmelCase      )
			elif not isinstance(_lowerCAmelCase      ,      _lowerCAmelCase      ):
				raise TypeError(
				    """binary_search_delete() only accepts either a list, range or str"""      )

			A							  =      0
			A							  =      len(_lowerCAmelCase      ) - 1

			while low <= high:
				A							  =      (low + high) // 2
				if array[mid] == item:
					array.pop(_lowerCAmelCase      )
					return array
				elif array[mid] < item:
					A							  =      mid + 1
				else:
					A							  =      mid - 1
			raise ValueError(
			    """Either the item is not in the array or the array was unsorted"""      )







		def        A     (self						:      Dict      ,      _lowerCAmelCase						:      list | str | range      ,      _lowerCAmelCase						:      int      ):
			if isinstance(_lowerCAmelCase      ,      (range, str)      ):
				A							  =      list(_lowerCAmelCase      )
			elif not isinstance(_lowerCAmelCase      ,      _lowerCAmelCase      ):
				raise TypeError(
				    """binary_search_insert() only accepts either a list, range or str"""      )

			A							  =      0
			A							  =      len(_lowerCAmelCase      ) - 1

			while low <= high:
				A							  =      (low + high) // 2
				if array[mid] == index:
					# If the item already exists in the array,
					# insert it after the existing item
					array.insert(mid + 1      ,      _lowerCAmelCase      )
					return array
				elif array[mid] < index:
					A							  =      mid + 1
				else:
					A							  =      mid - 1

        # If the item doesn't exist in the array, insert it at the appropriate position
			array.insert(_lowerCAmelCase      ,      _lowerCAmelCase      )
			return array







		def        A     (self						:      List[str]      ,      _lowerCAmelCase						:      int      ,      _lowerCAmelCase						:      int      ):
			# Remove previous index
			if index in self.indexmap:
				A							  =      self.indexmap[index]
				if len(self.numbermap[n]      ) == 1:
					del self.numbermap[n]
				else:
					A							  =      self.binary_search_delete(self.numbermap[n]      ,      _lowerCAmelCase      )

        # Set new index
			A							  =      number

			# Number not seen before or empty so insert number value
			if number not in self.numbermap:
				A							  =      [index]

			# Here we need to perform a binary search insertion in order to insert
			# The item in the correct place
			else:
				A							  =      self.binary_search_insert(
				    self.numbermap[number]      ,      _lowerCAmelCase      )







		def        A     (self						:      int      ,      _lowerCAmelCase						:      int      ):
			return self.numbermap.get(_lowerCAmelCase      ,      [-1]      )[0]


if __name__ == "__main__":
				import doctest

				doctest.testmod()

