





import argparse

import torch

from transformers import RemBertConfig, RemBertModel, load_tf_weights_in_rembert
from transformers.utils import logging


logging.set_verbosity_info()






def 							_lowerCAmelCase (  _a   :					Union[str, Any]					,   _a   :					Dict					,   _a   :					List[str]			)	->			Dict:
     # Initialise PyTorch model
     lowerCAmelCase_					:       Dict    =		RemBertConfig.from_json_file(_a			)
     print("""Building PyTorch model from configuration: {}""".format(str(_a			)			)			)
     lowerCAmelCase_					:       Any    =		RemBertModel(_a			)

     # Load weights from tf checkpoint
     load_tf_weights_in_rembert(_a					,   _a					,   _a			)

     # Save pytorch-model
     print("""Save PyTorch model to {}""".format(_a			)			)
     torch.save(model.state_dict()					,   _a			)


if __name__ == "__main__":
      UpperCAmelCase_					:   Dict 							=						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(
          """--rembert_config_file""",
          default=None,
          type=str,
          required=True,
          help=(
              """The config json file corresponding to the pre-trained RemBERT 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."""
      )
      UpperCAmelCase_					:   List[str] 							=						parser.parse_args()
      convert_rembert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.rembert_config_file, args.pytorch_dump_path)







from __future__ import annotations






def 							_lowerCAmelCase (  _a   :					list[int]			)	->			list[int]:  # This function is recursive
     lowerCAmelCase_					:       List[Any]    =		len(_a			)
     # If the array contains only one element, we return it (it's the stop condition of
     # recursion)
     if array_length <= 1:
          return array
          # Else
     lowerCAmelCase_					:       Union[str, Any]    =		array[0]
     lowerCAmelCase_					:       str    =		False
     lowerCAmelCase_					:       Optional[int]    =		1
     lowerCAmelCase_					:       list[int]    =		[]
     while not is_found and i < array_length:
          if array[i] < pivot:
               lowerCAmelCase_					:       Optional[Any]    =		True
               lowerCAmelCase_					:       Tuple    =		[element for element in array[i:] if element >= array[i]]
               lowerCAmelCase_					:       Any    =		longest_subsequence(_a			)
               if len(_a			) > len(_a			):
                    lowerCAmelCase_					:       List[Any]    =		temp_array
          else:
               i += 1

     lowerCAmelCase_					:       Tuple    =		[element for element in array[1:] if element >= pivot]
     lowerCAmelCase_					:       List[Any]    =		[pivot, *longest_subsequence(_a			)]
     if len(_a			) > len(_a			):
          return temp_array
     else:
          return longest_subseq


if __name__ == "__main__":
      import doctest

      doctest.testmod()
