





from collections import OrderedDict
from typing import Any, List, Mapping, Optional

from ... import PretrainedConfig, PreTrainedTokenizer
from ...onnx import OnnxConfig, PatchingSpec
from ...utils import TensorType, is_torch_available, logging


__lowercase				    =      logging.get_logger(__name__)

__lowercase				    =      {
    """microsoft/layoutlm-base-uncased""": (
        """https://huggingface.co/microsoft/layoutlm-base-uncased/resolve/main/config.json"""
    ),
    """microsoft/layoutlm-large-uncased""": (
        """https://huggingface.co/microsoft/layoutlm-large-uncased/resolve/main/config.json"""
    ),
}

class 	__snake_case					(      _a ):






    '''simple docstring'''
    _lowerCAmelCase  =						"""layoutlm"""





    def __init__( self    :		str      ,    snake_case    :		str=30_522      ,    snake_case    :		Dict=768      ,    snake_case    :		str=12      ,    snake_case    :		Dict=12      ,    snake_case    :		str=3_072      ,    snake_case    :		Tuple="gelu"      ,    snake_case    :		int=0.1      ,    snake_case    :		List[str]=0.1      ,    snake_case    :		Optional[Any]=512      ,    snake_case    :		Tuple=2      ,    snake_case    :		List[Any]=0.02      ,    snake_case    :		int=1e-12      ,    snake_case    :		Dict=0      ,    snake_case    :		Dict="absolute"      ,    snake_case    :		str=True      ,    snake_case    :		Any=1_024      ,    **snake_case    :		Dict      ,    ):

      """simple docstring"""





      super().__init__(pad_token_id=snake_case      ,    **snake_case				)
      __lowerCAmelCase								=					vocab_size
      __lowerCAmelCase								=					hidden_size
      __lowerCAmelCase								=					num_hidden_layers
      __lowerCAmelCase								=					num_attention_heads
      __lowerCAmelCase								=					hidden_act
      __lowerCAmelCase								=					intermediate_size
      __lowerCAmelCase								=					hidden_dropout_prob
      __lowerCAmelCase								=					attention_probs_dropout_prob
      __lowerCAmelCase								=					max_position_embeddings
      __lowerCAmelCase								=					type_vocab_size
      __lowerCAmelCase								=					initializer_range
      __lowerCAmelCase								=					layer_norm_eps
      __lowerCAmelCase								=					position_embedding_type
      __lowerCAmelCase								=					use_cache
      __lowerCAmelCase								=					max_ad_position_embeddings


class 	__snake_case					(      _a ):






    '''simple docstring'''





    def __init__( self    :		Any      ,    snake_case    :		PretrainedConfig      ,    snake_case    :		str = "default"      ,    snake_case    :		List[PatchingSpec] = None      ,    ):

      """simple docstring"""





      super().__init__(snake_case      ,    task=snake_case      ,    patching_specs=snake_case				)
      __lowerCAmelCase								=					config.max_ad_position_embeddings - 1





    @property
    def 						A		( self    :		Dict				):

      """simple docstring"""





      return OrderedDict(
          [
              ('''input_ids''', {0: '''batch''', 1: '''sequence'''}),
              ('''bbox''', {0: '''batch''', 1: '''sequence'''}),
              ('''attention_mask''', {0: '''batch''', 1: '''sequence'''}),
              ('''token_type_ids''', {0: '''batch''', 1: '''sequence'''}),
          ]				)





    def 						A		( self    :		Tuple      ,    snake_case    :		PreTrainedTokenizer      ,    snake_case    :		int = -1      ,    snake_case    :		int = -1      ,    snake_case    :		bool = False      ,    snake_case    :		Optional[TensorType] = None      ,    ):

      """simple docstring"""





      __lowerCAmelCase								=					super().generate_dummy_inputs(
          snake_case      ,    batch_size=snake_case      ,    seq_length=snake_case      ,    is_pair=snake_case      ,    framework=snake_case				)

      # Generate a dummy bbox
      __lowerCAmelCase								=					[48, 84, 73, 128]

      if not framework == TensorType.PYTORCH:
        raise NotImplementedError('''Exporting LayoutLM to ONNX is currently only supported for PyTorch.'''				)

      if not is_torch_available():
        raise ValueError('''Cannot generate dummy inputs without PyTorch installed.'''				)
      import torch

      __lowerCAmelCase						,    __lowerCAmelCase								=					input_dict['''input_ids'''].shape
      __lowerCAmelCase								=					torch.tensor([*[box] * seq_length]				).tile(snake_case      ,    1      ,    1				)
      return input_dict







# 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


__lowercase				    =      """Update an existing config file with the latest defaults while maintaining the old configuration."""


def        __SCREAMING_SNAKE_CASE	(				__lowercase:		Optional[Any]):



  '''simple docstring'''






  __lowerCAmelCase								=					args.config_file
  if config_file is None and Path(__lowercase).exists():
    __lowerCAmelCase								=					default_config_file
  elif not Path(__lowercase).exists():
    raise ValueError(F'''The passed config file located at {config_file} doesn\'t exist.''')
  __lowerCAmelCase								=					load_config_from_file(__lowercase)

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


def        __SCREAMING_SNAKE_CASE	(				__lowercase:		Tuple  ,				__lowercase:		int):



  '''simple docstring'''






  __lowerCAmelCase								=					parser.add_parser('''update'''  ,				parents=__lowercase  ,				help=__lowercase  ,				formatter_class=__lowercase)
  parser.add_argument(
      '''--config_file'''  ,				default=__lowercase  ,				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=__lowercase)
  return parser




def        __SCREAMING_SNAKE_CASE	(				__lowercase:		Any):



  '''simple docstring'''






  __lowerCAmelCase								=					update_config(__lowercase)
  print(F'''Sucessfully updated the configuration file at {config_file}.''')
