
import argparse
from collections import defaultdict

import yaml


_A						      =				"docs/source/en/_toctree.yml"



def 		lowercase_    (     A__	)							->							Tuple:
    """simple docstring"""

    snake_case				  =      defaultdict(A__	)
    snake_case				  =      []
    snake_case				  =      []
    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__	)

    snake_case				  =      new_doc_list
    snake_case				  =      [key for key, value in counts.items() if value > 1]

    snake_case				  =      []
    for duplicate_key in duplicates:
        snake_case				  =      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]	)
    snake_case				  =      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	)							->							Optional[int]:
    """simple docstring"""

    with open(A__				,	encoding="utf-8"	) as f:
        snake_case				  =      yaml.safe_load(f.read()	)

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

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

    snake_case				  =      api_doc[scheduler_idx]["sections"]
    snake_case				  =      clean_doc_toc(A__	)

    snake_case				  =      False
    if new_scheduler_doc != scheduler_doc:
        snake_case				  =      True
        if overwrite:
            snake_case				  =      new_scheduler_doc

    if diff:
        if overwrite:
            snake_case				  =      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	)							->							Any:
    """simple docstring"""

    with open(A__				,	encoding="utf-8"	) as f:
        snake_case				  =      yaml.safe_load(f.read()	)

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

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

    snake_case				  =      False
    snake_case				  =      api_doc[pipeline_idx]["sections"]
    snake_case				  =      []

    # sort sub pipeline docs
    for pipeline_doc in pipeline_docs:
        if "section" in pipeline_doc:
            snake_case				  =      pipeline_doc["section"]
            snake_case				  =      clean_doc_toc(A__	)
            if overwrite:
                snake_case				  =      new_sub_pipeline_doc
        new_pipeline_docs.append(A__	)

    # sort overall pipeline doc
    snake_case				  =      clean_doc_toc(A__	)

    if new_pipeline_docs != pipeline_docs:
        snake_case				  =      True
        if overwrite:
            snake_case				  =      new_pipeline_docs

    if diff:
        if overwrite:
            snake_case				  =      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__":
   _A						      =				argparse.ArgumentParser()
   parser.add_argument("--fix_and_overwrite", action="store_true", help="Whether to fix inconsistencies.")
   _A						      =				parser.parse_args()

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



from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


_A						      =				logging.get_logger(__name__)

_A						      =				{
    "roberta-base": "https://huggingface.co/roberta-base/resolve/main/config.json",
    "roberta-large": "https://huggingface.co/roberta-large/resolve/main/config.json",
    "roberta-large-mnli": "https://huggingface.co/roberta-large-mnli/resolve/main/config.json",
    "distilroberta-base": "https://huggingface.co/distilroberta-base/resolve/main/config.json",
    "roberta-base-openai-detector": "https://huggingface.co/roberta-base-openai-detector/resolve/main/config.json",
    "roberta-large-openai-detector": "https://huggingface.co/roberta-large-openai-detector/resolve/main/config.json",
}







class   lowerCamelCase	(						A_						):
     UpperCAmelCase__       :							Optional[int]     =	"roberta"





     def __init__(self   :					Union[str, Any]       ,					_A   :					List[Any]=5_0_2_6_5       ,					_A   :					Dict=7_6_8       ,					_A   :					Tuple=1_2       ,					_A   :					Optional[Any]=1_2       ,					_A   :					int=3_0_7_2       ,					_A   :					List[str]="gelu"       ,					_A   :					Tuple=0.1       ,					_A   :					Dict=0.1       ,					_A   :					Optional[int]=5_1_2       ,					_A   :					Dict=2       ,					_A   :					Optional[Any]=0.02       ,					_A   :					Optional[Any]=1E-12       ,					_A   :					str=1       ,					_A   :					Dict=0       ,					_A   :					Optional[int]=2       ,					_A   :					int="absolute"       ,					_A   :					Any=True       ,					_A   :					Union[str, Any]=None       ,					**_A   :					Optional[int]       ,					)		->		Tuple:
         super().__init__(pad_token_id=_A       ,					bos_token_id=_A       ,					eos_token_id=_A       ,					**_A     )

         snake_case				  =      vocab_size
         snake_case				  =      hidden_size
         snake_case				  =      num_hidden_layers
         snake_case				  =      num_attention_heads
         snake_case				  =      hidden_act
         snake_case				  =      intermediate_size
         snake_case				  =      hidden_dropout_prob
         snake_case				  =      attention_probs_dropout_prob
         snake_case				  =      max_position_embeddings
         snake_case				  =      type_vocab_size
         snake_case				  =      initializer_range
         snake_case				  =      layer_norm_eps
         snake_case				  =      position_embedding_type
         snake_case				  =      use_cache
         snake_case				  =      classifier_dropout







class   lowerCamelCase	(						A_						):





     @property
     def 	UpperCAmelCase(self   :					int     )		->		Mapping[str, Mapping[int, str]]:
         if self.task == "multiple-choice":
             snake_case				  =      {0: "batch", 1: "choice", 2: "sequence"}
         else:
             snake_case				  =      {0: "batch", 1: "sequence"}
         return OrderedDict(
             [
                 ("input_ids", dynamic_axis),
                 ("attention_mask", dynamic_axis),
             ]     )

