



from collections import OrderedDict
from typing import Mapping

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


UpperCamelCase_										=					logging.get_logger(__name__)

UpperCamelCase_										=					{
    'andreasmadsen/efficient_mlm_m0.40': (
        'https://huggingface.co/andreasmadsen/efficient_mlm_m0.40/resolve/main/config.json'
    ),
}







class 	_snake_case							(			UpperCamelCase_      ):






   '''simple docstring'''






   A__	:      List[Any]    =		"roberta-prelayernorm"


   def __init__(  self:			Tuple   ,lowerCamelCase_:			int=50265   ,lowerCamelCase_:			Optional[int]=768   ,lowerCamelCase_:			List[str]=12   ,lowerCamelCase_:			Any=12   ,lowerCamelCase_:			Any=3072   ,lowerCamelCase_:			Union[str, Any]="gelu"   ,lowerCamelCase_:			Dict=0.1   ,lowerCamelCase_:			str=0.1   ,lowerCamelCase_:			List[str]=512   ,lowerCamelCase_:			Optional[int]=2   ,lowerCamelCase_:			Union[str, Any]=0.0_2   ,lowerCamelCase_:			Optional[int]=1e-12   ,lowerCamelCase_:			Dict=1   ,lowerCamelCase_:			Any=0   ,lowerCamelCase_:			Dict=2   ,lowerCamelCase_:			Dict="absolute"   ,lowerCamelCase_:			List[str]=True   ,lowerCamelCase_:			Tuple=None   ,**lowerCamelCase_:			List[Any]   ,)     ->	Tuple:
       super().__init__(pad_token_id=UpperCamelCase__   ,bos_token_id=UpperCamelCase__   ,eos_token_id=UpperCamelCase__   ,**UpperCamelCase__				)

       UpperCAmelCase_			:    Tuple   						= vocab_size
       UpperCAmelCase_			:    str   						= hidden_size
       UpperCAmelCase_			:    int   						= num_hidden_layers
       UpperCAmelCase_			:    List[Any]   						= num_attention_heads
       UpperCAmelCase_			:    Optional[Any]   						= hidden_act
       UpperCAmelCase_			:    str   						= intermediate_size
       UpperCAmelCase_			:    List[str]   						= hidden_dropout_prob
       UpperCAmelCase_			:    Dict   						= attention_probs_dropout_prob
       UpperCAmelCase_			:    int   						= max_position_embeddings
       UpperCAmelCase_			:    List[str]   						= type_vocab_size
       UpperCAmelCase_			:    Any   						= initializer_range
       UpperCAmelCase_			:    List[str]   						= layer_norm_eps
       UpperCAmelCase_			:    Optional[int]   						= position_embedding_type
       UpperCAmelCase_			:    Tuple   						= use_cache
       UpperCAmelCase_			:    int   						= classifier_dropout







class 	_snake_case							(			UpperCamelCase_      ):






   '''simple docstring'''






   @property
   def 	A__  (  self:			Optional[int]				)     ->	Union[str, Any]:





       if self.task == "multiple-choice":
           UpperCAmelCase_			:    List[Any]   						= {0: '''batch''', 1: '''choice''', 2: '''sequence'''}
       else:
           UpperCAmelCase_			:    Tuple   						= {0: '''batch''', 1: '''sequence'''}
       return OrderedDict(
           [
               ("""input_ids""", dynamic_axis),
               ("""attention_mask""", dynamic_axis),
           ]				)

import pytest

from datasets.splits import SplitDict, SplitInfo
from datasets.utils.py_utils import asdict
@pytest.mark.parametrize(
    '''split_dict'''		,  [
        SplitDict(),
        SplitDict({'''train''': SplitInfo(name='''train'''		,  num_bytes=1_337		,  num_examples=42		,  dataset_name='''my_dataset'''						)}						),
        SplitDict({'''train''': SplitInfo(name='''train'''		,  num_bytes=1_337		,  num_examples=42						)}						),
        SplitDict({'''train''': SplitInfo()}						),
    ]		,  )
def       A	(    _lowercase						):
						SCREAMING_SNAKE_CASE							:    Tuple							=							split_dict._to_yaml_list()
						assert len(_lowercase						) == len(_lowercase						)
						SCREAMING_SNAKE_CASE							:    Tuple							=							SplitDict._from_yaml_list(_lowercase						)
						for split_name, split_info in split_dict.items():
												# dataset_name field is deprecated, and is therefore not part of the YAML dump
												SCREAMING_SNAKE_CASE							:    Any							=							None
												# the split name of split_dict takes over the name of the split info object
												SCREAMING_SNAKE_CASE							:    Optional[Any]							=							split_name
						assert split_dict == reloaded



@pytest.mark.parametrize(
    '''split_info'''		,  [SplitInfo(), SplitInfo(dataset_name=_lowercase						), SplitInfo(dataset_name='''my_dataset'''						)]						)
def       A	(    _lowercase						):
						# For backward compatibility, we need asdict(split_dict) to return split info dictrionaries with the "dataset_name"
						# field even if it's deprecated. This way old versionso of `datasets` can still reload dataset_infos.json files
						SCREAMING_SNAKE_CASE							:    List[Any]							=							asdict(SplitDict({'''train''': split_info}						)						)
						assert "dataset_name" in split_dict_asdict["train"]
						assert split_dict_asdict["train"]["dataset_name"] == split_info.dataset_name





