






"""simple docstring"""



from typing import Optional

from .. import Features, NamedSplit
from ..packaged_modules.text.text import Text
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader







class    lowercase__			(							SCREAMING_SNAKE_CASE__   ):


			def __init__(      self     :  Any   ,       snake_case__     :  str   ,       snake_case__     :  int = None   ,       snake_case__     :  str = None   ,       snake_case__     :  Optional[Any] = None   ,       snake_case__     :  Optional[int] = False   ,       snake_case__     :  Union[str, Any] = False   ,       snake_case__     :  List[Any] = None   ,       **snake_case__     :  List[Any]   ,       ):
										super().__init__(
										    lowerCamelCase__   ,       split=lowerCamelCase__   ,       features=lowerCamelCase__   ,       cache_dir=lowerCamelCase__   ,       keep_in_memory=lowerCamelCase__   ,       streaming=lowerCamelCase__   ,       num_proc=lowerCamelCase__   ,       **lowerCamelCase__   ,       )
										lowerCamelCase_       :							str									=path_or_paths if isinstance(lowerCamelCase__   ,       lowerCamelCase__					) else {self.split: path_or_paths}
										lowerCamelCase_       :							List[Any]									=Text(
										    cache_dir=lowerCamelCase__   ,       data_files=lowerCamelCase__   ,       features=lowerCamelCase__   ,       **lowerCamelCase__   ,       )


			def 	UpperCAmelCase__						(      self     :  Any					):
										# Build iterable dataset
										if self.streaming:
																	lowerCamelCase_       :							Dict									=self.builder.as_streaming_dataset(split=self.split					)
										# Build regular (map-style) dataset
										else:
																	lowerCamelCase_       :							Optional[Any]									=None
																	lowerCamelCase_       :							List[str]									=None
																	lowerCamelCase_       :							Union[str, Any]									=None
																	lowerCamelCase_       :							str									=None

																	self.builder.download_and_prepare(
																	    download_config=lowerCamelCase__   ,       download_mode=lowerCamelCase__   ,       verification_mode=lowerCamelCase__   ,       base_path=lowerCamelCase__   ,       num_proc=self.num_proc   ,       )
																	lowerCamelCase_       :							List[Any]									=self.builder.as_dataset(
																	    split=self.split   ,       verification_mode=lowerCamelCase__   ,       in_memory=self.keep_in_memory					)
										return dataset








from collections import OrderedDict
from typing import Mapping

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


SCREAMING_SNAKE_CASE_:Optional[Any]             =						logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_:Dict             =						{
    """camembert-base""": """https://huggingface.co/camembert-base/resolve/main/config.json""",
    """umberto-commoncrawl-cased-v1""": (
        """https://huggingface.co/Musixmatch/umberto-commoncrawl-cased-v1/resolve/main/config.json"""
    ),
    """umberto-wikipedia-uncased-v1""": (
        """https://huggingface.co/Musixmatch/umberto-wikipedia-uncased-v1/resolve/main/config.json"""
    ),
}






class SCREAMING_SNAKE_CASE__     (		SCREAMING_SNAKE_CASE__    ):




    '''simple docstring'''






    __lowerCamelCase			: Optional[int]					=      "camembert"






    def __init__(       self,		lowerCamelCase__=3_0522,		lowerCamelCase__=768,		lowerCamelCase__=12,		lowerCamelCase__=12,		lowerCamelCase__=3072,		lowerCamelCase__="gelu",		lowerCamelCase__=0.1,		lowerCamelCase__=0.1,		lowerCamelCase__=512,		lowerCamelCase__=2,		lowerCamelCase__=0.02,		lowerCamelCase__=1e-12,		lowerCamelCase__=1,		lowerCamelCase__=0,		lowerCamelCase__=2,		lowerCamelCase__="absolute",		lowerCamelCase__=True,		lowerCamelCase__=None,		**lowerCamelCase__,		):
        super().__init__(pad_token_id=lowerCamelCase__,		bos_token_id=lowerCamelCase__,		eos_token_id=lowerCamelCase__,		**lowerCamelCase__		)

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






class SCREAMING_SNAKE_CASE__     (		SCREAMING_SNAKE_CASE__    ):




    '''simple docstring'''






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


