






"""simple docstring"""


import argparse

import torch

from transformers import MraConfig, MraForMaskedLM




def      snake_case    (A_ :Tuple ):







  '''simple docstring'''

  if "model" in orig_key:
    a	:     Any							=  orig_key.replace('model.'      ,     '' )
  if "norm1" in orig_key:
    a	:     str							=  orig_key.replace('norm1'      ,     'attention.output.LayerNorm' )
  if "norm2" in orig_key:
    a	:     Any							=  orig_key.replace('norm2'      ,     'output.LayerNorm' )
  if "norm" in orig_key:
    a	:     Tuple							=  orig_key.replace('norm'      ,     'LayerNorm' )
  if "transformer" in orig_key:
    a	:     Tuple							=  orig_key.split('.' )[0].split('_' )[-1]
    a	:     Optional[Any]							=  orig_key.replace(f'''transformer_{layer_num}'''      ,     f'''encoder.layer.{layer_num}''' )
  if "mha.attn" in orig_key:
    a	:     List[Any]							=  orig_key.replace('mha.attn'      ,     'attention.self' )
  if "mha" in orig_key:
    a	:     Optional[Any]							=  orig_key.replace('mha'      ,     'attention' )
  if "W_q" in orig_key:
    a	:     Dict							=  orig_key.replace('W_q'      ,     'self.query' )
  if "W_k" in orig_key:
    a	:     List[Any]							=  orig_key.replace('W_k'      ,     'self.key' )
  if "W_v" in orig_key:
    a	:     Dict							=  orig_key.replace('W_v'      ,     'self.value' )
  if "ff.0" in orig_key:
    a	:     Tuple							=  orig_key.replace('ff.0'      ,     'intermediate.dense' )
  if "ff.2" in orig_key:
    a	:     Any							=  orig_key.replace('ff.2'      ,     'output.dense' )
  if "ff" in orig_key:
    a	:     Any							=  orig_key.replace('ff'      ,     'output.dense' )
  if "mlm_class" in orig_key:
    a	:     str							=  orig_key.replace('mlm.mlm_class'      ,     'cls.predictions.decoder' )
  if "mlm" in orig_key:
    a	:     str							=  orig_key.replace('mlm'      ,     'cls.predictions.transform' )
  if "backbone.backbone.encoders" in orig_key:
    a	:     Any							=  orig_key.replace('backbone.backbone.encoders'      ,     'encoder.layer' )
  if "cls" not in orig_key:
    a	:     int							=  'mra.' + orig_key

  return orig_key




def      snake_case    (A_ :Dict      ,     A_ :List[str] ):







  '''simple docstring'''

  for key in orig_state_dict.copy().keys():
    a	:     Optional[int]							=  orig_state_dict.pop(A_ )

    if ("pooler" in key) or ("sen_class" in key):
      continue
    else:
      a	:     int							=  val

  a	:     int							=  orig_state_dict['cls.predictions.decoder.bias']
  a	:     str							=  torch.arange(A_ ).expand((1, -1) ) + 2

  return orig_state_dict




def      snake_case    (A_ :Optional[int]      ,     A_ :int      ,     A_ :str ):







  '''simple docstring'''

  a	:     str							=  torch.load(A_      ,     map_location='cpu' )['model_state_dict']
  a	:     Union[str, Any]							=  MraConfig.from_json_file(A_ )
  a	:     Dict							=  MraForMaskedLM(A_ )

  a	:     Optional[Any]							=  convert_checkpoint_helper(config.max_position_embeddings      ,     A_ )

  print(model.load_state_dict(A_ ) )
  model.eval()
  model.save_pretrained(A_ )

  print(f'''Checkpoint successfuly converted. Model saved at {pytorch_dump_path}''' )


if __name__ == "__main__":
   _UpperCamelCase							:       List[str]       					=		argparse.ArgumentParser()
   # Required parameters
   parser.add_argument(
       '--pytorch_model_path', default=None, type=str, required=True, help='Path to Mra pytorch checkpoint.'
   )
   parser.add_argument(
       '--config_file',
       default=None,
       type=str,
       required=True,
       help='The json file for Mra model config.',
   )
   parser.add_argument(
       '--pytorch_dump_path', default=None, type=str, required=True, help='Path to the output PyTorch model.'
   )
   _UpperCamelCase							:       Tuple       					=		parser.parse_args()
   convert_mra_checkpoint(args.pytorch_model_path, args.config_file, args.pytorch_dump_path)












"""simple docstring"""


# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from pathlib import Path

from .config_args import default_config_file, load_config_from_file
from .config_utils import SubcommandHelpFormatter


_UpperCamelCase							:       int       					=		'Update an existing config file with the latest defaults while maintaining the old configuration.'




def      snake_case    (A_ :str ):







  '''simple docstring'''

  a	:     int							=  args.config_file
  if config_file is None and Path(A_ ).exists():
    a	:     List[Any]							=  default_config_file
  elif not Path(A_ ).exists():
    raise ValueError(f'''The passed config file located at {config_file} doesn\'t exist.''' )
  a	:     Dict							=  load_config_from_file(A_ )

  if config_file.endswith('.json' ):
    config.to_json_file(A_ )
  else:
    config.to_yaml_file(A_ )
  return config_file




def      snake_case    (A_ :List[str]      ,     A_ :Union[str, Any] ):







  '''simple docstring'''

  a	:     int							=  parser.add_parser('update'      ,     parents=A_      ,     help=A_      ,     formatter_class=A_ )
  parser.add_argument(
      '--config_file'      ,     default=A_      ,     help=(
          'The path to the config file to update. Will default to a file named default_config.yaml in the cache '
          'location, which is the content of the environment `HF_HOME` suffixed with \'accelerate\', or if you don\'t have '
          'such an environment variable, your cache directory (\'~/.cache\' or the content of `XDG_CACHE_HOME`) suffixed '
          'with \'huggingface\'.'
      )      ,     )

  parser.set_defaults(func=A_ )
  return parser






def      snake_case    (A_ :List[str] ):







  '''simple docstring'''

  a	:     List[str]							=  update_config(A_ )
  print(f'''Sucessfully updated the configuration file at {config_file}.''' )




