



'''simple docstring'''





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
    is_vision_available,
)


_UpperCamelCase											=		{
    'configuration_layoutlmv3': [
        'LAYOUTLMV3_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'LayoutLMv3Config',
        'LayoutLMv3OnnxConfig',
    ],
    'processing_layoutlmv3': ['LayoutLMv3Processor'],
    'tokenization_layoutlmv3': ['LayoutLMv3Tokenizer'],
}

try:
   if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _UpperCamelCase											=		['LayoutLMv3TokenizerFast']

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _UpperCamelCase											=		[
       'LAYOUTLMV3_PRETRAINED_MODEL_ARCHIVE_LIST',
       'LayoutLMv3ForQuestionAnswering',
       'LayoutLMv3ForSequenceClassification',
       'LayoutLMv3ForTokenClassification',
       'LayoutLMv3Model',
       'LayoutLMv3PreTrainedModel',
   ]

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _UpperCamelCase											=		[
       'TF_LAYOUTLMV3_PRETRAINED_MODEL_ARCHIVE_LIST',
       'TFLayoutLMv3ForQuestionAnswering',
       'TFLayoutLMv3ForSequenceClassification',
       'TFLayoutLMv3ForTokenClassification',
       'TFLayoutLMv3Model',
       'TFLayoutLMv3PreTrainedModel',
   ]

try:
   if not is_vision_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _UpperCamelCase											=		['LayoutLMv3FeatureExtractor']
   _UpperCamelCase											=		['LayoutLMv3ImageProcessor']


if TYPE_CHECKING:
   from .configuration_layoutlmva import (
       LAYOUTLMV3_PRETRAINED_CONFIG_ARCHIVE_MAP,
       LayoutLMvaConfig,
       LayoutLMvaOnnxConfig,
   )
   from .processing_layoutlmva import LayoutLMvaProcessor
   from .tokenization_layoutlmva import LayoutLMvaTokenizer

   try:
      if not is_tokenizers_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_layoutlmva_fast import LayoutLMvaTokenizerFast

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_layoutlmva import (
          LAYOUTLMV3_PRETRAINED_MODEL_ARCHIVE_LIST,
          LayoutLMvaForQuestionAnswering,
          LayoutLMvaForSequenceClassification,
          LayoutLMvaForTokenClassification,
          LayoutLMvaModel,
          LayoutLMvaPreTrainedModel,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_layoutlmva import (
          TF_LAYOUTLMV3_PRETRAINED_MODEL_ARCHIVE_LIST,
          TFLayoutLMvaForQuestionAnswering,
          TFLayoutLMvaForSequenceClassification,
          TFLayoutLMvaForTokenClassification,
          TFLayoutLMvaModel,
          TFLayoutLMvaPreTrainedModel,
      )

   try:
      if not is_vision_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .feature_extraction_layoutlmva import LayoutLMvaFeatureExtractor
      from .image_processing_layoutlmva import LayoutLMvaImageProcessor

else:
   import sys

   _UpperCamelCase											=		_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)











'''simple docstring'''





import argparse
from collections import defaultdict

import yaml


_UpperCamelCase											=		'docs/source/en/_toctree.yml'

def 			a_	(				_lowerCAmelCase			) -> Any:
  __lowerCamelCase			:			Optional[int]       			=					defaultdict(_lowerCAmelCase			)
  __lowerCamelCase			:			Optional[Any]       			=					[]
  __lowerCamelCase			:			Union[str, Any]       			=					[]
  for doc in doc_list:
    if "local" in doc:
      counts[doc["local"]] += 1

    if doc["title"].lower() == "overview":
      overview_doc.append({'local': doc['local'], 'title': doc['title']}			)
    else:
      new_doc_list.append(_lowerCAmelCase			)

  __lowerCamelCase			:			Dict       			=					new_doc_list
  __lowerCamelCase			:			Optional[Any]       			=					[key for key, value in counts.items() if value > 1]

  __lowerCamelCase			:			int       			=					[]
  for duplicate_key in duplicates:
    __lowerCamelCase			:			int       			=					list({doc['title'] for doc in doc_list if doc['local'] == duplicate_key}			)
    if len(_lowerCAmelCase			) > 1:
      raise ValueError(
          F'{duplicate_key} is present several times in the documentation table of content at '
          '`docs/source/en/_toctree.yml` with different *Title* values. Choose one of those and remove the '
          'others.'			)
    # Only add this once
    new_doc.append({'local': duplicate_key, 'title': titles[0]}			)

  # Add none duplicate-keys
  new_doc.extend([doc for doc in doc_list if 'local' not in counts or counts[doc['local']] == 1]			)
  __lowerCamelCase			:			Dict       			=					sorted(_lowerCAmelCase			,key=lambda _lowerCAmelCase			: s["title"].lower()			)

  # "overview" gets special treatment and is always first
  if len(_lowerCAmelCase			) > 1:
    raise ValueError('{doc_list} has two \'overview\' docs which is not allowed.'			)

  overview_doc.extend(_lowerCAmelCase			)

  # Sort
  return overview_doc

def 			a_	(				_lowerCAmelCase=False			) -> Optional[Any]:
  with open(_lowerCAmelCase			,encoding='utf-8'			) as f:
    __lowerCamelCase			:			str       			=					yaml.safe_load(f.read()			)

  # Get to the API doc
  __lowerCamelCase			:			Union[str, Any]       			=					0
  while content[api_idx]["title"] != "API":
    api_idx += 1
  __lowerCamelCase			:			List[str]       			=					content[api_idx]['sections']

  # Then to the model doc
  __lowerCamelCase			:			List[Any]       			=					0
  while api_doc[scheduler_idx]["title"] != "Schedulers":
    scheduler_idx += 1

  __lowerCamelCase			:			List[Any]       			=					api_doc[scheduler_idx]['sections']
  __lowerCamelCase			:			Optional[Any]       			=					clean_doc_toc(_lowerCAmelCase			)

  __lowerCamelCase			:			str       			=					False
  if new_scheduler_doc != scheduler_doc:
    __lowerCamelCase			:			int       			=					True
    if overwrite:
      __lowerCamelCase			:			Any       			=					new_scheduler_doc

  if diff:
    if overwrite:
      __lowerCamelCase			:			Tuple       			=					api_doc
      with open(_lowerCAmelCase			,'w'			,encoding='utf-8'			) as f:
        f.write(yaml.dump(_lowerCAmelCase			,allow_unicode=_lowerCAmelCase			)			)
    else:
      raise ValueError(
          'The model doc part of the table of content is not properly sorted, run `make style` to fix this.'			)

def 			a_	(				_lowerCAmelCase=False			) -> List[Any]:
  with open(_lowerCAmelCase			,encoding='utf-8'			) as f:
    __lowerCamelCase			:			List[str]       			=					yaml.safe_load(f.read()			)

  # Get to the API doc
  __lowerCamelCase			:			List[Any]       			=					0
  while content[api_idx]["title"] != "API":
    api_idx += 1
  __lowerCamelCase			:			Optional[Any]       			=					content[api_idx]['sections']

  # Then to the model doc
  __lowerCamelCase			:			List[Any]       			=					0
  while api_doc[pipeline_idx]["title"] != "Pipelines":
    pipeline_idx += 1

  __lowerCamelCase			:			int       			=					False
  __lowerCamelCase			:			str       			=					api_doc[pipeline_idx]['sections']
  __lowerCamelCase			:			Optional[Any]       			=					[]

  # sort sub pipeline docs
  for pipeline_doc in pipeline_docs:
    if "section" in pipeline_doc:
      __lowerCamelCase			:			str       			=					pipeline_doc['section']
      __lowerCamelCase			:			Optional[Any]       			=					clean_doc_toc(_lowerCAmelCase			)
      if overwrite:
        __lowerCamelCase			:			Union[str, Any]       			=					new_sub_pipeline_doc
    new_pipeline_docs.append(_lowerCAmelCase			)

  # sort overall pipeline doc
  __lowerCamelCase			:			int       			=					clean_doc_toc(_lowerCAmelCase			)

  if new_pipeline_docs != pipeline_docs:
    __lowerCamelCase			:			Tuple       			=					True
    if overwrite:
      __lowerCamelCase			:			int       			=					new_pipeline_docs

  if diff:
    if overwrite:
      __lowerCamelCase			:			Tuple       			=					api_doc
      with open(_lowerCAmelCase			,'w'			,encoding='utf-8'			) as f:
        f.write(yaml.dump(_lowerCAmelCase			,allow_unicode=_lowerCAmelCase			)			)
    else:
      raise ValueError(
          'The model doc part of the table of content is not properly sorted, run `make style` to fix this.'			)


if __name__ == "__main__":
   _UpperCamelCase											=		argparse.ArgumentParser()
   parser.add_argument('--fix_and_overwrite', action='store_true', help='Whether to fix inconsistencies.')
   _UpperCamelCase											=		parser.parse_args()

   check_scheduler_doc(args.fix_and_overwrite)
   check_pipeline_doc(args.fix_and_overwrite)






