
"""simple docstring"""


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




class  __lowerCamelCase  ( lowerCAmelCase			):
				a__:      Any          =    'roberta-prelayernorm'




				def __init__(				self							,						UpperCAmelCase=5_0265							,						UpperCAmelCase=768							,						UpperCAmelCase=12							,						UpperCAmelCase=12							,						UpperCAmelCase=3072							,						UpperCAmelCase="gelu"							,						UpperCAmelCase=0.1							,						UpperCAmelCase=0.1							,						UpperCAmelCase=512							,						UpperCAmelCase=2							,						UpperCAmelCase=0.0_2							,						UpperCAmelCase=1e-1_2							,						UpperCAmelCase=1							,						UpperCAmelCase=0							,						UpperCAmelCase=2							,						UpperCAmelCase="absolute"							,						UpperCAmelCase=True							,						UpperCAmelCase=None							,						**UpperCAmelCase							,						):
							super().__init__(pad_token_id=UpperCAmelCase							,						bos_token_id=UpperCAmelCase							,						eos_token_id=UpperCAmelCase							,						**UpperCAmelCase   )

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




class  __lowerCamelCase  ( lowerCAmelCase			):




				@property
				def        UpperCAmelCase__						(				self   ):
							if self.task == "multiple-choice":
										lowerCamelCase_					=  {0: '''batch''', 1: '''choice''', 2: '''sequence'''}
							else:
										lowerCamelCase_					=  {0: '''batch''', 1: '''sequence'''}
							return OrderedDict(
							    [
							        ('''input_ids''', dynamic_axis),
							        ('''attention_mask''', dynamic_axis),
							    ]   )





"""simple docstring"""


from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union

import pyarrow as pa


if TYPE_CHECKING:
						from .features import FeatureType




@dataclass
class  __lowerCamelCase  :
				a__:      List[str]
				a__:      Optional[str]          =    None
				# Automatically constructed
				a__:      ClassVar[str]          =    "dict"
				a__:      ClassVar[Any]          =    None
				a__:      str          =    field(default='Translation'						,	init=lowerCAmelCase						,	repr=lowerCAmelCase			)




				def __call__(				self   ):
							return pa.struct({lang: pa.string() for lang in sorted(self.languages   )}   )





				def        UpperCAmelCase__						(				self   ):
							from .features import Value

							return {k: Value('''string'''   ) for k in sorted(self.languages   )}




@dataclass
class  __lowerCamelCase  :
				a__:      Optional[List]          =    None
				a__:      Optional[int]          =    None
				a__:      Optional[str]          =    None
				# Automatically constructed
				a__:      ClassVar[str]          =    "dict"
				a__:      ClassVar[Any]          =    None
				a__:      str          =    field(default='TranslationVariableLanguages'						,	init=lowerCAmelCase						,	repr=lowerCAmelCase			)




				def        UpperCAmelCase__						(				self   ):
							lowerCamelCase_					=  sorted(set(self.languages   )   ) if self.languages else None
							lowerCamelCase_					=  len(self.languages   ) if self.languages else None




				def __call__(				self   ):
							return pa.struct({'''language''': pa.list_(pa.string()   ), '''translation''': pa.list_(pa.string()   )}   )




				def        UpperCAmelCase__						(				self							,						UpperCAmelCase   ):
							lowerCamelCase_					=  set(self.languages   )
							if self.languages and set(UpperCAmelCase   ) - lang_set:
										raise ValueError(
										    f"Some languages in example ({', '.join(sorted(set(UpperCAmelCase   ) - lang_set   )   )}) are not in valid set ({', '.join(UpperCAmelCase   )})."   )

							# Convert dictionary into tuples, splitting out cases where there are
							# multiple translations for a single language.
							lowerCamelCase_					=  []
							for lang, text in translation_dict.items():
										if isinstance(UpperCAmelCase							,						UpperCAmelCase   ):
													translation_tuples.append((lang, text)   )
										else:
													translation_tuples.extend([(lang, el) for el in text]   )

        # Ensure translations are in ascending order by language code.
							lowerCamelCase_		, lowerCamelCase_					=  zip(*sorted(UpperCAmelCase   )   )

							return {"language": languages, "translation": translations}





				def        UpperCAmelCase__						(				self   ):
							from .features import Sequence, Value

							return {
							    "language": Sequence(Value('''string'''   )   ),
							    "translation": Sequence(Value('''string'''   )   ),
							}



