



from ...configuration_utils import PretrainedConfig
from ...utils import logging


SCREAMING_SNAKE_CASE__   			=   logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__   			=   {
    '''SCUT-DLVCLab/lilt-roberta-en-base''': (
        '''https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base/resolve/main/config.json'''
    ),
}


class   __lowerCAmelCase  (		UpperCAmelCase_   ):
					"""simple docstring"""






					A__					:		int      							=     "lilt"



					def __init__(  self       :							int					,       _snake_case       :							Dict=3_05_22					,       _snake_case       :							List[str]=7_68					,       _snake_case       :							Optional[int]=12					,       _snake_case       :							Tuple=12					,       _snake_case       :							Union[str, Any]=30_72					,       _snake_case       :							str="gelu"					,       _snake_case       :							List[Any]=0.1					,       _snake_case       :							Union[str, Any]=0.1					,       _snake_case       :							Dict=5_12					,       _snake_case       :							List[str]=2					,       _snake_case       :							Any=0.02					,       _snake_case       :							str=1E-12					,       _snake_case       :							Union[str, Any]=0					,       _snake_case       :							int="absolute"					,       _snake_case       :							str=None					,       _snake_case       :							Union[str, Any]=4					,       _snake_case       :							List[Any]=10_24					,       **_snake_case       :							Any					,       ):






								"""simple docstring"""


								super().__init__(pad_token_id=_snake_case					,       **_snake_case       )

								A__	  =     vocab_size
								A__	  =     hidden_size
								A__	  =     num_hidden_layers
								A__	  =     num_attention_heads
								A__	  =     hidden_act
								A__	  =     intermediate_size
								A__	  =     hidden_dropout_prob
								A__	  =     attention_probs_dropout_prob
								A__	  =     max_position_embeddings
								A__	  =     type_vocab_size
								A__	  =     initializer_range
								A__	  =     layer_norm_eps
								A__	  =     position_embedding_type
								A__	  =     classifier_dropout
								A__	  =     channel_shrink_ratio
								A__	  =     max_ad_position_embeddings








'''simple docstring'''







import argparse
from collections import defaultdict

import yaml


lowerCAmelCase     :  Dict											=    """docs/source/en/_toctree.yml"""






def       lowercase					(_A       ):







       """simple docstring"""







       _lowerCAmelCase     :				Optional[int]       =							defaultdict(_A       )
       _lowerCAmelCase     :				Tuple       =							[]
       _lowerCAmelCase     :				Dict       =							[]
       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(_A       )

       _lowerCAmelCase     :				str       =							new_doc_list
       _lowerCAmelCase     :				List[Any]       =							[key for key, value in counts.items() if value > 1]

       _lowerCAmelCase     :				List[str]       =							[]
       for duplicate_key in duplicates:
              _lowerCAmelCase     :				Any       =							list({doc['title'] for doc in doc_list if doc['local'] == duplicate_key}       )
              if len(_A       ) > 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     :				Any       =							sorted(_A ,    key=lambda _A       : s["title"].lower()       )

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

       overview_doc.extend(_A       )

       # Sort
       return overview_doc






def       lowercase					(_A=False       ):







       """simple docstring"""







       with open(_A ,    encoding='utf-8'       ) as f:
              _lowerCAmelCase     :				Union[str, Any]       =							yaml.safe_load(f.read()       )

       # Get to the API doc
       _lowerCAmelCase     :				Tuple       =							0
       while content[api_idx]["title"] != "API":
              api_idx += 1
       _lowerCAmelCase     :				str       =							content[api_idx]['sections']

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

       _lowerCAmelCase     :				Optional[int]       =							api_doc[scheduler_idx]['sections']
       _lowerCAmelCase     :				Any       =							clean_doc_toc(_A       )

       _lowerCAmelCase     :				int       =							False
       if new_scheduler_doc != scheduler_doc:
              _lowerCAmelCase     :				str       =							True
              if overwrite:
                     _lowerCAmelCase     :				int       =							new_scheduler_doc

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






def       lowercase					(_A=False       ):







       """simple docstring"""







       with open(_A ,    encoding='utf-8'       ) as f:
              _lowerCAmelCase     :				Optional[Any]       =							yaml.safe_load(f.read()       )

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

       # Then to the model doc
       _lowerCAmelCase     :				Optional[int]       =							0
       while api_doc[pipeline_idx]["title"] != "Pipelines":
              pipeline_idx += 1

       _lowerCAmelCase     :				List[Any]       =							False
       _lowerCAmelCase     :				List[Any]       =							api_doc[pipeline_idx]['sections']
       _lowerCAmelCase     :				Union[str, Any]       =							[]

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

       # sort overall pipeline doc
       _lowerCAmelCase     :				str       =							clean_doc_toc(_A       )

       if new_pipeline_docs != pipeline_docs:
              _lowerCAmelCase     :				Any       =							True
              if overwrite:
                     _lowerCAmelCase     :				Optional[int]       =							new_pipeline_docs

       if diff:
              if overwrite:
                     _lowerCAmelCase     :				str       =							api_doc
                     with open(_A ,    'w' ,    encoding='utf-8'       ) as f:
                            f.write(yaml.dump(_A ,    allow_unicode=_A       )       )
              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__":
       lowerCAmelCase     :  Tuple											=    argparse.ArgumentParser()
       parser.add_argument("""--fix_and_overwrite""", action="""store_true""", help="""Whether to fix inconsistencies.""")
       lowerCAmelCase     :  List[Any]											=    parser.parse_args()

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

