






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 						A_					(						lowercase_			)				->Optional[TaskTemplate]:







 """simple docstring"""

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










"""simple docstring"""

import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig
from ..clip.configuration_clip import CLIPVisionConfig


UpperCamelCase__			:     Optional[Any]			       =				logging.get_logger(__name__)
class      A__   (   lowercase_  ):
	A_				:					List[str]      =   """vision-text-dual-encoder"""
	A_				:					Tuple      =   True




	def __init__( self	:						Tuple   ,     lowercase	:						List[Any]=512   ,     lowercase	:						Any=2.65_92   ,     **lowercase	:						int						)       ->			int:
						super().__init__(**lowercase						)

						if "vision_config" not in kwargs:
											raise ValueError("""`vision_config` can not be `None`."""						)

						if "text_config" not in kwargs:
											raise ValueError("""`text_config` can not be `None`."""						)

						__snake_case        =						kwargs.pop("""vision_config"""						)
						__snake_case        =						kwargs.pop("""text_config"""						)

						__snake_case        =						vision_config.pop("""model_type"""						)
						__snake_case        =						text_config.pop("""model_type"""						)

						if vision_model_type == "clip":
											__snake_case        =						AutoConfig.for_model(lowercase   ,     **lowercase						).vision_config
						elif vision_model_type == "clip_vision_model":
											__snake_case        =						CLIPVisionConfig(**lowercase						)
						else:
											__snake_case        =						AutoConfig.for_model(lowercase   ,     **lowercase						)

						__snake_case        =						AutoConfig.for_model(lowercase   ,     **lowercase						)

						__snake_case        =						projection_dim
						__snake_case        =						logit_scale_init_value




	@classmethod
	def 				a_		( cls	:						Union[str, Any]   ,     lowercase	:						PretrainedConfig   ,     lowercase	:						PretrainedConfig   ,     **lowercase	:						Optional[int]						)       ->			Dict:
						return cls(vision_config=vision_config.to_dict()   ,     text_config=text_config.to_dict()   ,     **lowercase						)




	def 				a_		( self	:						Dict						)       ->			Dict:
						__snake_case        =						copy.deepcopy(self.__dict__						)
						__snake_case        =						self.vision_config.to_dict()
						__snake_case        =						self.text_config.to_dict()
						__snake_case        =						self.__class__.model_type
						return output


