





import argparse
import os

import numpy as np
import tensorflow as tf
import torch

from transformers import BertModel





def 	lowerCAmelCase_					(			__a      ,       __a      ,       __a						)	->						int:







  """simple docstring"""





  lowerCamelCase__: Tuple         =("dense.weight", "attention.self.query", "attention.self.key", "attention.self.value")

  lowerCamelCase__: Optional[int]         =(
      ("layer.", "layer_"),
      ("word_embeddings.weight", "word_embeddings"),
      ("position_embeddings.weight", "position_embeddings"),
      ("token_type_embeddings.weight", "token_type_embeddings"),
      (".", "/"),
      ("LayerNorm/weight", "LayerNorm/gamma"),
      ("LayerNorm/bias", "LayerNorm/beta"),
      ("weight", "kernel"),
  )

  if not os.path.isdir(__a						):
    os.makedirs(__a						)

  lowerCamelCase__: str         =model.state_dict()

  def to_tf_var_name(__a						):
    for patt, repl in iter(__a						):
      lowerCamelCase__: Tuple         =name.replace(__a      ,       __a						)
    return F"""bert/{name}"""

  def create_tf_var(__a      ,       __a      ,       __a						):
    lowerCamelCase__: str         =tf.dtypes.as_dtype(tensor.dtype						)
    lowerCamelCase__: Union[str, Any]         =tf.get_variable(dtype=__a      ,       shape=tensor.shape      ,       name=__a      ,       initializer=tf.zeros_initializer()						)
    session.run(tf.variables_initializer([tf_var]						)						)
    session.run(__a						)
    return tf_var

  tf.reset_default_graph()
  with tf.Session() as session:
    for var_name in state_dict:
      lowerCamelCase__: Dict         =to_tf_var_name(__a						)
      lowerCamelCase__: str         =state_dict[var_name].numpy()
      if any(x in var_name for x in tensors_to_transpose						):
        lowerCamelCase__: Tuple         =torch_tensor.T
      lowerCamelCase__: int         =create_tf_var(tensor=__a      ,       name=__a      ,       session=__a						)
      tf.keras.backend.set_value(__a      ,       __a						)
      lowerCamelCase__: Optional[Any]         =session.run(__a						)
      print(F"""Successfully created {tf_name}: {np.allclose(__a      ,       __a						)}"""						)

    lowerCamelCase__: Union[str, Any]         =tf.train.Saver(tf.trainable_variables()						)
    saver.save(__a      ,       os.path.join(__a      ,       model_name.replace("-"      ,       "_"						) + ".ckpt"						)						)





def 	lowerCAmelCase_					(			__a=None						)	->						List[str]:







  """simple docstring"""





  lowerCamelCase__: Optional[int]         =argparse.ArgumentParser()
  parser.add_argument("--model_name"      ,       type=__a      ,       required=__a      ,       help="model name e.g. bert-base-uncased"						)
  parser.add_argument(
      "--cache_dir"      ,       type=__a      ,       default=__a      ,       required=__a      ,       help="Directory containing pytorch model"						)
  parser.add_argument("--pytorch_model_path"      ,       type=__a      ,       required=__a      ,       help="/path/to/<pytorch-model-name>.bin"						)
  parser.add_argument("--tf_cache_dir"      ,       type=__a      ,       required=__a      ,       help="Directory in which to save tensorflow model"						)
  lowerCamelCase__: Any         =parser.parse_args(__a						)

  lowerCamelCase__: int         =BertModel.from_pretrained(
      pretrained_model_name_or_path=args.model_name      ,       state_dict=torch.load(args.pytorch_model_path						)      ,       cache_dir=args.cache_dir      ,       )

  convert_pytorch_checkpoint_to_tf(model=__a      ,       ckpt_dir=args.tf_cache_dir      ,       model_name=args.model_name						)


if __name__ == "__main__":
     main()


'''simple docstring'''

import math
import sys



def snake_case_      (					__snake_case  :							str)			->					str:
   lowerCAmelCase_			=      ''''''
   try:
      with open(__snake_case	,   '''rb''') as binary_file:
         lowerCAmelCase_			=      binary_file.read()
      for dat in data:
         lowerCAmelCase_			=      F'''{dat:08b}'''
         result += curr_byte
      return result
   except OSError:
      print('''File not accessible''')
      sys.exit()



def snake_case_      (					__snake_case  :							str)			->					str:
   lowerCAmelCase_			=      {'''0''': '''0''', '''1''': '''1'''}
   lowerCAmelCase_	,lowerCAmelCase_			=      '''''', ''''''
   lowerCAmelCase_			=      len(__snake_case)

   for i in range(len(__snake_case)):
      curr_string += data_bits[i]
      if curr_string not in lexicon:
         continue

      lowerCAmelCase_			=      lexicon[curr_string]
      result += last_match_id
      lowerCAmelCase_			=      last_match_id + '''0'''

      if math.loga(__snake_case).is_integer():
         lowerCAmelCase_			=      {}
         for curr_key in list(__snake_case):
            lowerCAmelCase_			=      lexicon.pop(__snake_case)
         lowerCAmelCase_			=      new_lex

      lowerCAmelCase_			=      last_match_id + '''1'''
      index += 1
      lowerCAmelCase_			=      ''''''
   return result



def snake_case_      (					__snake_case  :							str	,   __snake_case  :							str)			->					None:
   lowerCAmelCase_			=      8
   try:
      with open(__snake_case	,   '''wb''') as opened_file:
         lowerCAmelCase_			=      [
             to_write[i : i + byte_length]
             for i in range(0	,   len(__snake_case)	,   __snake_case)
         ]

         if len(result_byte_array[-1]) % byte_length == 0:
            result_byte_array.append('''10000000''')
         else:
            result_byte_array[-1] += "1" + "0" * (
                byte_length - len(result_byte_array[-1]) - 1
            )

         for elem in result_byte_array[:-1]:
            opened_file.write(int(__snake_case	,   2).to_bytes(1	,   byteorder='''big'''))
   except OSError:
      print('''File not accessible''')
      sys.exit()



def snake_case_      (					__snake_case  :							str)			->					str:
   lowerCAmelCase_			=      0
   for letter in data_bits:
      if letter == "1":
         break
      counter += 1

   lowerCAmelCase_			=      data_bits[counter:]
   lowerCAmelCase_			=      data_bits[counter + 1 :]
   return data_bits



def snake_case_      (					__snake_case  :							str	,   __snake_case  :							str)			->					None:
   lowerCAmelCase_			=      read_file_binary(__snake_case)
   lowerCAmelCase_			=      remove_prefix(__snake_case)
   lowerCAmelCase_			=      decompress_data(__snake_case)
   write_file_binary(__snake_case	,   __snake_case)


if __name__ == "__main__":
 compress(sys.argv[1], sys.argv[2])





