



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


A__								=						logging.get_logger(__name__)

A__								=						{
    '''caidas/swin2sr-classicalsr-x2-64''': (
        '''https://huggingface.co/caidas/swin2sr-classicalsr-x2-64/resolve/main/config.json'''
    ),
}


class       a							(			__lowerCamelCase				):
		__lowerCAmelCase	:    Tuple											=					"""swin2sr"""

		__lowerCAmelCase	:    Tuple											=					{
		    """hidden_size""": """embed_dim""",
		    """num_attention_heads""": """num_heads""",
		    """num_hidden_layers""": """num_layers""",
		}



		def __init__(     self     :List[str]   ,__lowercase     :Union[str, Any]=6_4   ,__lowercase     :List[str]=1   ,__lowercase     :Optional[int]=3   ,__lowercase     :str=1_8_0   ,__lowercase     :Dict=[6, 6, 6, 6, 6, 6]   ,__lowercase     :Tuple=[6, 6, 6, 6, 6, 6]   ,__lowercase     :Union[str, Any]=8   ,__lowercase     :Tuple=2.0   ,__lowercase     :str=True   ,__lowercase     :Tuple=0.0   ,__lowercase     :Dict=0.0   ,__lowercase     :Union[str, Any]=0.1   ,__lowercase     :Dict="gelu"   ,__lowercase     :Tuple=False   ,__lowercase     :str=0.02   ,__lowercase     :Union[str, Any]=1e-5   ,__lowercase     :Tuple=2   ,__lowercase     :Optional[int]=1.0   ,__lowercase     :Tuple="1conv"   ,__lowercase     :int="pixelshuffle"   ,**__lowercase     :List[str]   ,):
						super().__init__(**__lowercase  )

						snake_case__	:      Optional[Any]     		=	image_size
						snake_case__	:      List[Any]     		=	patch_size
						snake_case__	:      Tuple     		=	num_channels
						snake_case__	:      List[Any]     		=	embed_dim
						snake_case__	:      Optional[Any]     		=	depths
						snake_case__	:      Tuple     		=	len(__lowercase  )
						snake_case__	:      Tuple     		=	num_heads
						snake_case__	:      List[str]     		=	window_size
						snake_case__	:      int     		=	mlp_ratio
						snake_case__	:      Dict     		=	qkv_bias
						snake_case__	:      Tuple     		=	hidden_dropout_prob
						snake_case__	:      Tuple     		=	attention_probs_dropout_prob
						snake_case__	:      str     		=	drop_path_rate
						snake_case__	:      int     		=	hidden_act
						snake_case__	:      Any     		=	use_absolute_embeddings
						snake_case__	:      List[Any]     		=	layer_norm_eps
						snake_case__	:      int     		=	initializer_range
						snake_case__	:      List[Any]     		=	upscale
						snake_case__	:      Optional[int]     		=	img_range
						snake_case__	:      str     		=	resi_connection
						snake_case__	:      Tuple     		=	upsampler






from collections import OrderedDict
from typing import Mapping

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


A__								=						logging.get_logger(__name__)

A__								=						{
    '''distilbert-base-uncased''': '''https://huggingface.co/distilbert-base-uncased/resolve/main/config.json''',
    '''distilbert-base-uncased-distilled-squad''': (
        '''https://huggingface.co/distilbert-base-uncased-distilled-squad/resolve/main/config.json'''
    ),
    '''distilbert-base-cased''': '''https://huggingface.co/distilbert-base-cased/resolve/main/config.json''',
    '''distilbert-base-cased-distilled-squad''': (
        '''https://huggingface.co/distilbert-base-cased-distilled-squad/resolve/main/config.json'''
    ),
    '''distilbert-base-german-cased''': '''https://huggingface.co/distilbert-base-german-cased/resolve/main/config.json''',
    '''distilbert-base-multilingual-cased''': (
        '''https://huggingface.co/distilbert-base-multilingual-cased/resolve/main/config.json'''
    ),
    '''distilbert-base-uncased-finetuned-sst-2-english''': (
        '''https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english/resolve/main/config.json'''
    ),
}


class       a							(			__lowerCamelCase				):
		__lowerCAmelCase	:    str											=					"""distilbert"""
		__lowerCAmelCase	:    str											=					{
		    """hidden_size""": """dim""",
		    """num_attention_heads""": """n_heads""",
		    """num_hidden_layers""": """n_layers""",
		}



		def __init__(     self     :Dict   ,__lowercase     :Tuple=3_0_5_2_2   ,__lowercase     :Optional[Any]=5_1_2   ,__lowercase     :List[str]=False   ,__lowercase     :List[str]=6   ,__lowercase     :Optional[Any]=1_2   ,__lowercase     :Tuple=7_6_8   ,__lowercase     :int=4 * 7_6_8   ,__lowercase     :List[Any]=0.1   ,__lowercase     :List[str]=0.1   ,__lowercase     :Union[str, Any]="gelu"   ,__lowercase     :List[str]=0.02   ,__lowercase     :Optional[int]=0.1   ,__lowercase     :Dict=0.2   ,__lowercase     :Union[str, Any]=0   ,**__lowercase     :Optional[Any]   ,):
						snake_case__	:      List[str]     		=	vocab_size
						snake_case__	:      Tuple     		=	max_position_embeddings
						snake_case__	:      Optional[int]     		=	sinusoidal_pos_embds
						snake_case__	:      str     		=	n_layers
						snake_case__	:      List[Any]     		=	n_heads
						snake_case__	:      Tuple     		=	dim
						snake_case__	:      str     		=	hidden_dim
						snake_case__	:      int     		=	dropout
						snake_case__	:      Dict     		=	attention_dropout
						snake_case__	:      Tuple     		=	activation
						snake_case__	:      int     		=	initializer_range
						snake_case__	:      Optional[Any]     		=	qa_dropout
						snake_case__	:      Union[str, Any]     		=	seq_classif_dropout
						super().__init__(**__lowercase   ,pad_token_id=__lowercase  )


class       a							(			__lowerCamelCase				):



		@property
		def 	__lowerCamelCase			(     self     :Union[str, Any]  ):
						if self.task == "multiple-choice":
										snake_case__	:      str     		=	{0: '''batch''', 1: '''choice''', 2: '''sequence'''}
						else:
										snake_case__	:      Optional[int]     		=	{0: '''batch''', 1: '''sequence'''}
						return OrderedDict(
						    [
						        ('''input_ids''', dynamic_axis),
						        ('''attention_mask''', dynamic_axis),
						    ]  )

