


'''simple docstring'''
import argparse
from collections import defaultdict

import yaml


UpperCAmelCase_			:  Optional[Any]										=   'docs/source/en/_toctree.yml'


def       _lowercase							(					UpperCamelCase__							:       Union[str, Any]      ):
 __A	:		Optional[int]	  =      defaultdict(UpperCamelCase__      )
 __A	:		List[str]	  =      []
 __A	:		Optional[int]	  =      []
 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(UpperCamelCase__      )

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

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

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

 overview_doc.extend(UpperCamelCase__      )

 # Sort
 return overview_doc


def       _lowercase							(					UpperCamelCase__							:       Any=False      ):
 with open(UpperCamelCase__,					encoding='utf-8'      ) as f:
  __A	:		List[Any]	  =      yaml.safe_load(f.read()      )

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

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

 __A	:		int	  =      api_doc[scheduler_idx]['sections']
 __A	:		str	  =      clean_doc_toc(UpperCamelCase__      )

 __A	:		int	  =      False
 if new_scheduler_doc != scheduler_doc:
  __A	:		int	  =      True
  if overwrite:
   __A	:		int	  =      new_scheduler_doc

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


def       _lowercase							(					UpperCamelCase__							:       Optional[int]=False      ):
 with open(UpperCamelCase__,					encoding='utf-8'      ) as f:
  __A	:		str	  =      yaml.safe_load(f.read()      )

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

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

 __A	:		Tuple	  =      False
 __A	:		int	  =      api_doc[pipeline_idx]['sections']
 __A	:		Optional[Any]	  =      []

 # sort sub pipeline docs
 for pipeline_doc in pipeline_docs:
  if "section" in pipeline_doc:
   __A	:		List[str]	  =      pipeline_doc['section']
   __A	:		Tuple	  =      clean_doc_toc(UpperCamelCase__      )
   if overwrite:
    __A	:		Tuple	  =      new_sub_pipeline_doc
  new_pipeline_docs.append(UpperCamelCase__      )

 # sort overall pipeline doc
 __A	:		List[str]	  =      clean_doc_toc(UpperCamelCase__      )

 if new_pipeline_docs != pipeline_docs:
  __A	:		Union[str, Any]	  =      True
  if overwrite:
   __A	:		Optional[Any]	  =      new_pipeline_docs

 if diff:
  if overwrite:
   __A	:		int	  =      api_doc
   with open(UpperCamelCase__,					'w',					encoding='utf-8'      ) as f:
    f.write(yaml.dump(UpperCamelCase__,					allow_unicode=UpperCamelCase__      )      )
  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_			:  List[Any]										=   argparse.ArgumentParser()
 parser.add_argument('--fix_and_overwrite', action='store_true', help='Whether to fix inconsistencies.')
 UpperCAmelCase_			:  Dict										=   parser.parse_args()

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










'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCAmelCase_			:  Optional[int]										=   logging.get_logger(__name__)

UpperCAmelCase_			:  List[str]										=   {
    'google/fnet-base': 'https://huggingface.co/google/fnet-base/resolve/main/config.json',
    'google/fnet-large': 'https://huggingface.co/google/fnet-large/resolve/main/config.json'
    # See all FNet models at https://huggingface.co/models?filter=fnet
}

class     _lowerCamelCase       (     snake_case_					):




 '''simple docstring'''
 __lowercase					:		List[Any]     				=    '''fnet'''


 def __init__(   self   ,   __lowercase=32_000   ,   __lowercase=768   ,   __lowercase=12   ,   __lowercase=3_072   ,   __lowercase="gelu_new"   ,   __lowercase=0.1   ,   __lowercase=512   ,   __lowercase=4   ,   __lowercase=0.0_2   ,   __lowercase=1E-12   ,   __lowercase=False   ,   __lowercase=512   ,   __lowercase=3   ,   __lowercase=1   ,   __lowercase=2   ,   **__lowercase   ,   ):

  """simple docstring"""







  super().__init__(pad_token_id=__lowercase   ,   bos_token_id=__lowercase   ,   eos_token_id=__lowercase   ,   **__lowercase    )

  __A	:		Union[str, Any]	  =      vocab_size
  __A	:		Dict	  =      max_position_embeddings
  __A	:		List[str]	  =      hidden_size
  __A	:		Tuple	  =      num_hidden_layers
  __A	:		Optional[int]	  =      intermediate_size
  __A	:		Dict	  =      hidden_act
  __A	:		List[str]	  =      hidden_dropout_prob
  __A	:		str	  =      initializer_range
  __A	:		Dict	  =      type_vocab_size
  __A	:		int	  =      layer_norm_eps
  __A	:		Tuple	  =      use_tpu_fourier_optimizations
  __A	:		Optional[Any]	  =      tpu_short_seq_length






