






'''simple docstring'''



import argparse

import torch

from transformers import BertConfig, BertForPreTraining, load_tf_weights_in_bert
from transformers.utils import logging


logging.set_verbosity_info()


def 				lowercase_					(     __A			:							Tuple       ,   __A			:							Union[str, Any]       ,   __A			:							Optional[int]      )							->   str:



 """simple docstring"""




 lowercase       : Union[str, Any]						=BertConfig.from_json_file(__A      )
 print(F'Building PyTorch model from configuration: {config}'      )
 lowercase       : Optional[int]						=BertForPreTraining(__A      )

 # Load weights from tf checkpoint
 load_tf_weights_in_bert(__A       ,   __A       ,   __A      )

 # Save pytorch-model
 print(F'Save PyTorch model to {pytorch_dump_path}'      )
 torch.save(model.state_dict()       ,   __A      )


if __name__ == "__main__":
      SCREAMING_SNAKE_CASE							=						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(
          '--bert_config_file',
          default=None,
          type=str,
          required=True,
          help=(
              'The config json file corresponding to the pre-trained BERT model. \n'
              'This specifies the model architecture.'
          ),
      )
      parser.add_argument(
          '--pytorch_dump_path', default=None, type=str, required=True, help='Path to the output PyTorch model.'
      )
      SCREAMING_SNAKE_CASE							=						parser.parse_args()
      convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.bert_config_file, args.pytorch_dump_path)




'''simple docstring'''


from __future__ import annotations

# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
__snake_case						  =		10

def   A_      (       SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_						)			->int:
  for i in range(SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_						):
    if array[i] == target:
      return i
  return -1

def   A_      (       SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_						)			->int:
  lowercase_     =       0
  lowercase_     =       len(SCREAMING_SNAKE_CASE_						)
  while left <= right:
    if right - left < precision:
      return lin_search(SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_						)

    lowercase_     =       (left + right) // 3 + 1
    lowercase_     =       2 * (left + right) // 3 + 1

    if array[one_third] == target:
      return one_third
    elif array[two_third] == target:
      return two_third

    elif target < array[one_third]:
      lowercase_     =       one_third - 1
    elif array[two_third] < target:
      lowercase_     =       two_third + 1

    else:
      lowercase_     =       one_third + 1
      lowercase_     =       two_third - 1
  else:
    return -1

def   A_      (       SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_						)			->int:
  if left < right:
    if right - left < precision:
      return lin_search(SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_						)
    lowercase_     =       (left + right) // 3 + 1
    lowercase_     =       2 * (left + right) // 3 + 1

    if array[one_third] == target:
      return one_third
    elif array[two_third] == target:
      return two_third

    elif target < array[one_third]:
      return rec_ternary_search(SCREAMING_SNAKE_CASE_ ,	one_third - 1 ,	SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_						)
    elif array[two_third] < target:
      return rec_ternary_search(two_third + 1 ,	SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_						)
    else:
      return rec_ternary_search(one_third + 1 ,	two_third - 1 ,	SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_						)
  else:
    return -1


if __name__ == "__main__":
       import doctest

       doctest.testmod()

       __snake_case						  =		input("""Enter numbers separated by comma:\n""").strip()
       __snake_case						  =		[int(item.strip()) for item in user_input.split(""",""")]
       assert collection == sorted(collection), f"List must be ordered.\n{collection}."
       __snake_case						  =		int(input("""Enter the number to be found in the list:\n""").strip())
       __snake_case						  =		ite_ternary_search(collection, target)
       __snake_case						  =		rec_ternary_search(0, len(collection) - 1, collection, target)
       if resulta != -1:
              print(f'''Iterative search: {target} found at positions: {resulta}''')
              print(f'''Recursive search: {target} found at positions: {resulta}''')
       else:
              print("""Not found""")

