





"""simple docstring"""





import argparse

from transformers import (
    TapasConfig,
    TapasForMaskedLM,
    TapasForQuestionAnswering,
    TapasForSequenceClassification,
    TapasModel,
    TapasTokenizer,
    load_tf_weights_in_tapas,
)
from transformers.utils import logging


logging.set_verbosity_info()
def 					__A  (_SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE     )   ->Any:





  """simple docstring"""


  lowerCAmelCase__     :Tuple											=				TapasConfig.from_json_file(_SCREAMING_SNAKE_CASE     )
  # set absolute/relative position embeddings parameter
  lowerCAmelCase__     :int											=				reset_position_index_per_cell

  # set remaining parameters of TapasConfig as well as the model based on the task
  if task == "SQA":
    lowerCAmelCase__     :Optional[int]											=				TapasForQuestionAnswering(config=_SCREAMING_SNAKE_CASE     )
  elif task == "WTQ":
    # run_task_main.py hparams
    lowerCAmelCase__     :Optional[int]											=				4
    lowerCAmelCase__     :Tuple											=				True
    # hparam_utils.py hparams
    lowerCAmelCase__     :Optional[int]											=				0.6_6_4_6_9_4
    lowerCAmelCase__     :Tuple											=				0.2_0_7_9_5_1
    lowerCAmelCase__     :List[str]											=				0.1_2_1_1_9_4
    lowerCAmelCase__     :Optional[Any]											=				True
    lowerCAmelCase__     :Dict											=				True
    lowerCAmelCase__     :Union[str, Any]											=				False
    lowerCAmelCase__     :List[str]											=				0.0_3_5_2_5_1_3

    lowerCAmelCase__     :Optional[Any]											=				TapasForQuestionAnswering(config=_SCREAMING_SNAKE_CASE     )
  elif task == "WIKISQL_SUPERVISED":
    # run_task_main.py hparams
    lowerCAmelCase__     :Optional[Any]											=				4
    lowerCAmelCase__     :str											=				False
    # hparam_utils.py hparams
    lowerCAmelCase__     :Any											=				3_6.4_5_1_9
    lowerCAmelCase__     :Tuple											=				0.9_0_3_4_2_1
    lowerCAmelCase__     :Optional[int]											=				2_2_2.0_8_8
    lowerCAmelCase__     :int											=				True
    lowerCAmelCase__     :List[str]											=				True
    lowerCAmelCase__     :Optional[Any]											=				True
    lowerCAmelCase__     :List[str]											=				0.7_6_3_1_4_1

    lowerCAmelCase__     :Tuple											=				TapasForQuestionAnswering(config=_SCREAMING_SNAKE_CASE     )
  elif task == "TABFACT":
    lowerCAmelCase__     :List[str]											=				TapasForSequenceClassification(config=_SCREAMING_SNAKE_CASE     )
  elif task == "MLM":
    lowerCAmelCase__     :Optional[int]											=				TapasForMaskedLM(config=_SCREAMING_SNAKE_CASE     )
  elif task == "INTERMEDIATE_PRETRAINING":
    lowerCAmelCase__     :Dict											=				TapasModel(config=_SCREAMING_SNAKE_CASE     )
  else:
    raise ValueError(F"Task {task} not supported."     )

  print(F"Building PyTorch model from configuration: {config}"     )
  # Load weights from tf checkpoint
  load_tf_weights_in_tapas(_SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE     )

  # Save pytorch-model (weights and configuration)
  print(F"Save PyTorch model to {pytorch_dump_path}"     )
  model.save_pretrained(_SCREAMING_SNAKE_CASE     )

  # Save tokenizer files
  print(F"Save tokenizer files to {pytorch_dump_path}"     )
  lowerCAmelCase__     :str											=				TapasTokenizer(vocab_file=tf_checkpoint_path[:-10] + 'vocab.txt'	,  model_max_length=512     )
  tokenizer.save_pretrained(_SCREAMING_SNAKE_CASE     )

  print('Used relative position embeddings:'	,  model.config.reset_position_index_per_cell     )


if __name__ == "__main__":
  __A											=						argparse.ArgumentParser()
  # Required parameters
  parser.add_argument(
      """--task""", default="""SQA""", type=str, help="""Model task for which to convert a checkpoint. Defaults to SQA."""
  )
  parser.add_argument(
      """--reset_position_index_per_cell""",
      default=False,
      action="""store_true""",
      help="""Whether to use relative position embeddings or not. Defaults to True.""",
  )
  parser.add_argument(
      """--tf_checkpoint_path""", default=None, type=str, required=True, help="""Path to the TensorFlow checkpoint path."""
  )
  parser.add_argument(
      """--tapas_config_file""",
      default=None,
      type=str,
      required=True,
      help=(
          """The config json file corresponding to the pre-trained TAPAS 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."""
  )
  __A											=						parser.parse_args()
  convert_tf_checkpoint_to_pytorch(
      args.task,
      args.reset_position_index_per_cell,
      args.tf_checkpoint_path,
      args.tapas_config_file,
      args.pytorch_dump_path,
  )







"""simple docstring"""





import re
def 					__A  (_SCREAMING_SNAKE_CASE     )   ->list:





  """simple docstring"""


  return [char.split() for char in re.split(r'[^ a-z A-Z 0-9 \s]'	,  str_     )]
def 					__A  (_SCREAMING_SNAKE_CASE     )   ->str:





  """simple docstring"""


  lowerCAmelCase__     :Optional[Any]											=				split_input(str_     )
  return "".join(
      [''.join([char.capitalize() for char in sub_str]     ) for sub_str in string_split]     )
def 					__A  (_SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE     )   ->str:





  """simple docstring"""


  try:
    lowerCAmelCase__     :Any											=				split_input(_SCREAMING_SNAKE_CASE     )
    if upper:
      lowerCAmelCase__     :str											=				''.join(
          [
              separator.join([char.upper() for char in sub_str]     )
              for sub_str in string_split
          ]     )
    else:
      lowerCAmelCase__     :int											=				''.join(
          [
              separator.join([char.lower() for char in sub_str]     )
              for sub_str in string_split
          ]     )
    return res_str
  except IndexError:
    return "not valid string"
def 					__A  (_SCREAMING_SNAKE_CASE     )   ->str:





  """simple docstring"""


  return to_simple_case(_SCREAMING_SNAKE_CASE     )
def 					__A  (_SCREAMING_SNAKE_CASE     )   ->str:





  """simple docstring"""


  try:
    lowerCAmelCase__     :str											=				to_simple_case(_SCREAMING_SNAKE_CASE     )
    return res_str[0].lower() + res_str[1:]
  except IndexError:
    return "not valid string"
def 					__A  (_SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE     )   ->str:





  """simple docstring"""


  return to_complex_case(_SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE	,  '_'     )
def 					__A  (_SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE     )   ->str:





  """simple docstring"""


  return to_complex_case(_SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE	,  '-'     )


if __name__ == "__main__":
  __import__("""doctest""").testmod()
