




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


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

_lowerCAmelCase    : List[Any]		= {
    "dandelin/vilt-b32-mlm": "https://huggingface.co/dandelin/vilt-b32-mlm/blob/main/config.json"
}
class       _UpperCamelCase   (					lowerCAmelCase		):
      UpperCAmelCase_          =		"""vilt"""
      def __init__(      self :Tuple			,   lowerCamelCase :Union[str, Any]=3_0522			,   lowerCamelCase :Dict=2			,   lowerCamelCase :str=2			,   lowerCamelCase :Dict=40			,   lowerCamelCase :Tuple=768			,   lowerCamelCase :Tuple=12			,   lowerCamelCase :int=12			,   lowerCamelCase :List[str]=3072			,   lowerCamelCase :Union[str, Any]="gelu"			,   lowerCamelCase :int=0.0			,   lowerCamelCase :Any=0.0			,   lowerCamelCase :Optional[int]=0.02			,   lowerCamelCase :Tuple=1e-12			,   lowerCamelCase :Tuple=384			,   lowerCamelCase :Optional[Any]=32			,   lowerCamelCase :List[str]=3			,   lowerCamelCase :Any=True			,   lowerCamelCase :Union[str, Any]=-1			,   lowerCamelCase :Optional[Any]=False			,   lowerCamelCase :Any=-1			,   **lowerCamelCase :Dict			,   )  ->      Optional[int]:
       super().__init__(tie_word_embeddings=lowerCamelCase			,   **lowerCamelCase   )

       UpperCAmelCase__							=    vocab_size
       UpperCAmelCase__							=    type_vocab_size
       UpperCAmelCase__							=    modality_type_vocab_size
       UpperCAmelCase__							=    max_position_embeddings

       UpperCAmelCase__							=    hidden_size
       UpperCAmelCase__							=    num_hidden_layers
       UpperCAmelCase__							=    num_attention_heads
       UpperCAmelCase__							=    intermediate_size
       UpperCAmelCase__							=    hidden_act
       UpperCAmelCase__							=    hidden_dropout_prob
       UpperCAmelCase__							=    attention_probs_dropout_prob
       UpperCAmelCase__							=    initializer_range
       UpperCAmelCase__							=    layer_norm_eps

       UpperCAmelCase__							=    image_size
       UpperCAmelCase__							=    patch_size
       UpperCAmelCase__							=    num_channels
       UpperCAmelCase__							=    qkv_bias
       UpperCAmelCase__							=    max_image_length
       UpperCAmelCase__							=    num_images











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


_lowerCAmelCase    : Any		= [
    "AutomaticSpeechRecognition",
    "AudioClassification",
    "ImageClassification",
    "LanguageModeling",
    "QuestionAnsweringExtractive",
    "Summarization",
    "TaskTemplate",
    "TextClassification",
]

_lowerCAmelCase    : Dict		= get_logger(__name__)


_lowerCAmelCase    : Optional[Any]		= {
    AutomaticSpeechRecognition.task: AutomaticSpeechRecognition,
    AudioClassification.task: AudioClassification,
    ImageClassification.task: ImageClassification,
    LanguageModeling.task: LanguageModeling,
    QuestionAnsweringExtractive.task: QuestionAnsweringExtractive,
    Summarization.task: Summarization,
    TextClassification.task: TextClassification,
}



def     lowerCAmelCase		(		_lowerCAmelCase				: dict						):




 """simple docstring"""







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





