'''simple docstring'''





from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCamelCase    :			List[Any]						     =  logging.get_logger(__name__)

UpperCamelCase    :			str						     =  {
    """bert-base-uncased""": """https://huggingface.co/bert-base-uncased/resolve/main/config.json""",
    # QDQBERT models can be loaded from any BERT checkpoint, available at https://huggingface.co/models?filter=bert
}



class    UpperCamelCase (    a_    ):







    """simple docstring"""





    A			:  List[str]            =       "qdqbert"





    def __init__( self			:		Any				,				UpperCAmelCase_			:		Optional[int]=3_0_5_2_2				,				UpperCAmelCase_			:		Optional[int]=7_6_8				,				UpperCAmelCase_			:		int=1_2				,				UpperCAmelCase_			:		List[str]=1_2				,				UpperCAmelCase_			:		List[str]=3_0_7_2				,				UpperCAmelCase_			:		Tuple="gelu"				,				UpperCAmelCase_			:		Optional[int]=0.1				,				UpperCAmelCase_			:		Any=0.1				,				UpperCAmelCase_			:		List[Any]=5_1_2				,				UpperCAmelCase_			:		List[Any]=2				,				UpperCAmelCase_			:		Union[str, Any]=0.02				,				UpperCAmelCase_			:		Optional[int]=1e-12				,				UpperCAmelCase_			:		Optional[int]=True				,				UpperCAmelCase_			:		str=1				,				UpperCAmelCase_			:		Union[str, Any]=0				,				UpperCAmelCase_			:		Optional[Any]=2				,				**UpperCAmelCase_			:		Dict				,				):


         """simple docstring"""







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

         a :				List[Any]				=      vocab_size
         a :				Optional[int]				=      max_position_embeddings
         a :				Any				=      hidden_size
         a :				List[Any]				=      num_hidden_layers
         a :				List[Any]				=      num_attention_heads
         a :				Dict				=      intermediate_size
         a :				Union[str, Any]				=      hidden_act
         a :				Union[str, Any]				=      hidden_dropout_prob
         a :				Optional[Any]				=      attention_probs_dropout_prob
         a :				Optional[int]				=      initializer_range
         a :				Optional[int]				=      type_vocab_size
         a :				Optional[int]				=      layer_norm_eps
         a :				List[Any]				=      use_cache







from typing import Optional

from ..utils.logging import get_logger
from .audio_classificiation import AudioClassification
from .automatic_speech_recognition import AutomaticSpeechRecognition
from .base import TaskTemplate
from .image_classification import ImageClassification
from .language_modeling import LanguageModeling
from .question_answering import QuestionAnsweringExtractive
from .summarization import Summarization
from .text_classification import TextClassification


UpperCamelCase__              =						[
    'AutomaticSpeechRecognition',
    'AudioClassification',
    'ImageClassification',
    'LanguageModeling',
    'QuestionAnsweringExtractive',
    'Summarization',
    'TaskTemplate',
    'TextClassification',
]

UpperCamelCase__              =						get_logger(__name__)


UpperCamelCase__              =						{
    AutomaticSpeechRecognition.task: AutomaticSpeechRecognition,
    AudioClassification.task: AudioClassification,
    ImageClassification.task: ImageClassification,
    LanguageModeling.task: LanguageModeling,
    QuestionAnsweringExtractive.task: QuestionAnsweringExtractive,
    Summarization.task: Summarization,
    TextClassification.task: TextClassification,
}






def 					snake_case					(							A			)							->							Optional[TaskTemplate]:




	'''simple docstring'''


	lowerCamelCase_							:		Any							   =							task_template_dict.get('task'			)
	if task_name is None:
		logger.warning(f"Couldn't find template for task '{task_name}'. Available templates: {list(A			)}"			)
		return None
	lowerCamelCase_							:		Any							   =							NAMEaTEMPLATE.get(A			)
	return template.from_dict(A			)
