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   __lowercase       (     _A     ):
						lowercase       			=  'distilbert'
						lowercase       			=  {
						    'hidden_size': 'dim',
						    'num_attention_heads': 'n_heads',
						    'num_hidden_layers': 'n_layers',
						}

						def __init__(						self					:   List[str]				,				__lowerCamelCase					:   List[str]=3_05_22				,				__lowerCamelCase					:   str=5_12				,				__lowerCamelCase					:   List[str]=False				,				__lowerCamelCase					:   List[str]=6				,				__lowerCamelCase					:   List[str]=12				,				__lowerCamelCase					:   int=7_68				,				__lowerCamelCase					:   str=4 * 7_68				,				__lowerCamelCase					:   int=0.1				,				__lowerCamelCase					:   Any=0.1				,				__lowerCamelCase					:   Optional[int]="gelu"				,				__lowerCamelCase					:   Optional[Any]=0.02				,				__lowerCamelCase					:   Tuple=0.1				,				__lowerCamelCase					:   Union[str, Any]=0.2				,				__lowerCamelCase					:   Tuple=0				,				**__lowerCamelCase					:   Any				,				)				->		Any:


									'''simple docstring'''

									lowercase       		=		vocab_size
									lowercase       		=		max_position_embeddings
									lowercase       		=		sinusoidal_pos_embds
									lowercase       		=		n_layers
									lowercase       		=		n_heads
									lowercase       		=		dim
									lowercase       		=		hidden_dim
									lowercase       		=		dropout
									lowercase       		=		attention_dropout
									lowercase       		=		activation
									lowercase       		=		initializer_range
									lowercase       		=		qa_dropout
									lowercase       		=		seq_classif_dropout
									super().__init__(**__lowercase				,				pad_token_id=__lowercase )






class   __lowercase       (     _A     ):

						@property
						def 							__a		(						self					:   Dict )				->		List[str]:


									'''simple docstring'''

									if self.task == "multiple-choice":
												lowercase       		=		{0: '''batch''', 1: '''choice''', 2: '''sequence'''}
									else:
												lowercase       		=		{0: '''batch''', 1: '''sequence'''}
									return OrderedDict(
									    [
									        ('''input_ids''', dynamic_axis),
									        ('''attention_mask''', dynamic_axis),
									    ] )








'''simple docstring'''

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


UpperCAmelCase					 =	logging.get_logger(__name__)

UpperCAmelCase					 =	{
    '''shi-labs/dinat-mini-in1k-224''': '''https://huggingface.co/shi-labs/dinat-mini-in1k-224/resolve/main/config.json''',
    # See all Dinat models at https://huggingface.co/models?filter=dinat
}


class 	lowerCAmelCase  (   A ,      A ):
       lowerCAmelCase_												=			"dinat"

       lowerCAmelCase_												=			{
           "num_attention_heads": "num_heads",
           "num_hidden_layers": "num_layers",
       }







       def __init__(				self      :			int    ,   __lowercase      :			str=4    ,   __lowercase      :			str=3    ,   __lowercase      :			int=64    ,   __lowercase      :			int=[3, 4, 6, 5]    ,   __lowercase      :			Union[str, Any]=[2, 4, 8, 16]    ,   __lowercase      :			Optional[int]=7    ,   __lowercase      :			str=[[1, 8, 1], [1, 4, 1, 4], [1, 2, 1, 2, 1, 2], [1, 1, 1, 1, 1]]    ,   __lowercase      :			Any=3.0    ,   __lowercase      :			Optional[Any]=True    ,   __lowercase      :			List[Any]=0.0    ,   __lowercase      :			Optional[Any]=0.0    ,   __lowercase      :			int=0.1    ,   __lowercase      :			Union[str, Any]="gelu"    ,   __lowercase      :			Any=0.0_2    ,   __lowercase      :			int=1E-5    ,   __lowercase      :			Optional[int]=0.0    ,   __lowercase      :			Optional[int]=None    ,   __lowercase      :			str=None    ,   **__lowercase      :			Any    ,   ):







            """simple docstring"""







            super().__init__(**__lowercase   )

            __lowercase      		=patch_size
            __lowercase      		=num_channels
            __lowercase      		=embed_dim
            __lowercase      		=depths
            __lowercase      		=len(__lowercase   )
            __lowercase      		=num_heads
            __lowercase      		=kernel_size
            __lowercase      		=dilations
            __lowercase      		=mlp_ratio
            __lowercase      		=qkv_bias
            __lowercase      		=hidden_dropout_prob
            __lowercase      		=attention_probs_dropout_prob
            __lowercase      		=drop_path_rate
            __lowercase      		=hidden_act
            __lowercase      		=layer_norm_eps
            __lowercase      		=initializer_range
            # we set the hidden_size attribute in order to make Dinat work with VisionEncoderDecoderModel
            # this indicates the channel dimension after the last stage of the model
            __lowercase      		=int(embed_dim * 2 ** (len(__lowercase   ) - 1)   )
            __lowercase      		=layer_scale_init_value
            __lowercase      		=['stem'] + [f'''stage{idx}''' for idx in range(1    ,   len(__lowercase   ) + 1   )]
            __lowercase		,  __lowercase      		=get_aligned_output_features_output_indices(
                out_features=__lowercase    ,   out_indices=__lowercase    ,   stage_names=self.stage_names   )


