


from typing import List

import datasets
from datasets.tasks import ImageClassification

from ..folder_based_builder import folder_based_builder


lowercase_								=    datasets.utils.logging.get_logger(__name__)




class 					_UpperCamelCase (      folder_based_builder.FolderBasedBuilderConfig	):







							'''simple docstring'''
							_A  				=  None
							_A  				=  None




class 					_UpperCamelCase (      folder_based_builder.FolderBasedBuilder	):







							'''simple docstring'''
							_A  				=  datasets.Image()
							_A  				=  "image"
							_A  				=  ImageFolderConfig
							_A  				=  42  # definition at the bottom of the script
							_A  				=  ImageClassification(image_column="image"			,							label_column="label"	)




lowercase_								=    [
    '.blp',
    '.bmp',
    '.dib',
    '.bufr',
    '.cur',
    '.pcx',
    '.dcx',
    '.dds',
    '.ps',
    '.eps',
    '.fit',
    '.fits',
    '.fli',
    '.flc',
    '.ftc',
    '.ftu',
    '.gbr',
    '.gif',
    '.grib',
    '.h5',
    '.hdf',
    '.png',
    '.apng',
    '.jp2',
    '.j2k',
    '.jpc',
    '.jpf',
    '.jpx',
    '.j2c',
    '.icns',
    '.ico',
    '.im',
    '.iim',
    '.tif',
    '.tiff',
    '.jfif',
    '.jpe',
    '.jpg',
    '.jpeg',
    '.mpg',
    '.mpeg',
    '.msp',
    '.pcd',
    '.pxr',
    '.pbm',
    '.pgm',
    '.ppm',
    '.pnm',
    '.psd',
    '.bw',
    '.rgb',
    '.rgba',
    '.sgi',
    '.ras',
    '.tga',
    '.icb',
    '.vda',
    '.vst',
    '.webp',
    '.wmf',
    '.emf',
    '.xbm',
    '.xpm',
]
lowercase_								=    IMAGE_EXTENSIONS






from typing import List, Union

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


lowercase_								=    logging.get_logger(__name__)

lowercase_								=    {
    'allenai/led-base-16384': 'https://huggingface.co/allenai/led-base-16384/resolve/main/config.json',
    # See all LED models at https://huggingface.co/models?filter=led
}




class 					_UpperCamelCase (      lowerCamelCase__	):







							'''simple docstring'''
							_A  				=  "led"
							_A  				=  {
							    "num_attention_heads": "encoder_attention_heads",
							    "hidden_size": "d_model",
							    "attention_probs_dropout_prob": "attention_dropout",
							    "initializer_range": "init_std",
							}







							def __init__(		self  :				List[str]		,				SCREAMING_SNAKE_CASE_  :				List[str]=5_0_2_6_5		,				SCREAMING_SNAKE_CASE_  :				str=1_6_3_8_4		,				SCREAMING_SNAKE_CASE_  :				List[Any]=1_0_2_4		,				SCREAMING_SNAKE_CASE_  :				List[str]=1_2		,				SCREAMING_SNAKE_CASE_  :				Any=4_0_9_6		,				SCREAMING_SNAKE_CASE_  :				Optional[Any]=1_6		,				SCREAMING_SNAKE_CASE_  :				str=1_2		,				SCREAMING_SNAKE_CASE_  :				List[Any]=4_0_9_6		,				SCREAMING_SNAKE_CASE_  :				List[str]=1_6		,				SCREAMING_SNAKE_CASE_  :				Optional[int]=0.0		,				SCREAMING_SNAKE_CASE_  :				Union[str, Any]=0.0		,				SCREAMING_SNAKE_CASE_  :				List[Any]=True		,				SCREAMING_SNAKE_CASE_  :				str=True		,				SCREAMING_SNAKE_CASE_  :				List[str]="gelu"		,				SCREAMING_SNAKE_CASE_  :				List[Any]=1_0_2_4		,				SCREAMING_SNAKE_CASE_  :				Tuple=0.1		,				SCREAMING_SNAKE_CASE_  :				Dict=0.0		,				SCREAMING_SNAKE_CASE_  :				Optional[Any]=0.0		,				SCREAMING_SNAKE_CASE_  :				Tuple=0.02		,				SCREAMING_SNAKE_CASE_  :				str=2		,				SCREAMING_SNAKE_CASE_  :				Tuple=0.0		,				SCREAMING_SNAKE_CASE_  :				Optional[int]=1		,				SCREAMING_SNAKE_CASE_  :				str=0		,				SCREAMING_SNAKE_CASE_  :				Union[str, Any]=2		,				SCREAMING_SNAKE_CASE_  :				Union[List[int], int] = 5_1_2		,				**SCREAMING_SNAKE_CASE_  :				Dict		,				):
													_a     =			vocab_size
													_a     =			max_encoder_position_embeddings
													_a     =			max_decoder_position_embeddings
													_a     =			d_model
													_a     =			encoder_ffn_dim
													_a     =			encoder_layers
													_a     =			encoder_attention_heads
													_a     =			decoder_ffn_dim
													_a     =			decoder_layers
													_a     =			decoder_attention_heads
													_a     =			dropout
													_a     =			attention_dropout
													_a     =			activation_dropout
													_a     =			activation_function
													_a     =			init_std
													_a     =			encoder_layerdrop
													_a     =			decoder_layerdrop
													_a     =			classifier_dropout
													_a     =			use_cache
													_a     =			encoder_layers
													_a     =			attention_window

													super().__init__(
													    pad_token_id=SCREAMING_SNAKE_CASE_		,				bos_token_id=SCREAMING_SNAKE_CASE_		,				eos_token_id=SCREAMING_SNAKE_CASE_		,				is_encoder_decoder=SCREAMING_SNAKE_CASE_		,				decoder_start_token_id=SCREAMING_SNAKE_CASE_		,				**SCREAMING_SNAKE_CASE_		,				)


