

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


SCREAMING_SNAKE_CASE		:str						=     logging.get_logger(__name__)

SCREAMING_SNAKE_CASE		:int						=     {
    """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 						__magic_name__					(							snake_case			,      snake_case				):
     UpperCamelCase_	:Optional[Any]										=      """dinat"""

     UpperCamelCase_	:List[Any]										=      {
         """num_attention_heads""": """num_heads""",
         """num_hidden_layers""": """num_layers""",
     }






     def __init__(				self		,						_lowercase=4		,						_lowercase=3		,						_lowercase=64		,						_lowercase=[3, 4, 6, 5]		,						_lowercase=[2, 4, 8, 16]		,						_lowercase=7		,						_lowercase=[[1, 8, 1], [1, 4, 1, 4], [1, 2, 1, 2, 1, 2], [1, 1, 1, 1, 1]]		,						_lowercase=3.0		,						_lowercase=True		,						_lowercase=0.0		,						_lowercase=0.0		,						_lowercase=0.1		,						_lowercase="gelu"		,						_lowercase=0.02		,						_lowercase=1e-5		,						_lowercase=0.0		,						_lowercase=None		,						_lowercase=None		,						**_lowercase		,						)->     Union[str, Any]:
         super().__init__(**_lowercase	)

         UpperCamelCase_			  =						patch_size
         UpperCamelCase_			  =						num_channels
         UpperCamelCase_			  =						embed_dim
         UpperCamelCase_			  =						depths
         UpperCamelCase_			  =						len(_lowercase	)
         UpperCamelCase_			  =						num_heads
         UpperCamelCase_			  =						kernel_size
         UpperCamelCase_			  =						dilations
         UpperCamelCase_			  =						mlp_ratio
         UpperCamelCase_			  =						qkv_bias
         UpperCamelCase_			  =						hidden_dropout_prob
         UpperCamelCase_			  =						attention_probs_dropout_prob
         UpperCamelCase_			  =						drop_path_rate
         UpperCamelCase_			  =						hidden_act
         UpperCamelCase_			  =						layer_norm_eps
         UpperCamelCase_			  =						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
         UpperCamelCase_			  =						int(embed_dim * 2 ** (len(_lowercase	) - 1)	)
         UpperCamelCase_			  =						layer_scale_init_value
         UpperCamelCase_			  =						["stem"] + [F"stage{idx}" for idx in range(1		,						len(_lowercase	) + 1	)]
         UpperCamelCase_  ,       UpperCamelCase_			  =						get_aligned_output_features_output_indices(
             out_features=_lowercase		,						out_indices=_lowercase		,						stage_names=self.stage_names	)



def 			lowerCAmelCase(      SCREAMING_SNAKE_CASE_			)->						list:



    """simple docstring"""






    if bit_count < 0:
        raise ValueError("The given input must be positive"			)

    # get the generated string sequence
    UpperCamelCase_			  =						gray_code_sequence_string(SCREAMING_SNAKE_CASE_			)
    #
    # convert them to integers
    for i in range(len(SCREAMING_SNAKE_CASE_			)			):
        UpperCamelCase_			  =						int(sequence[i]			,						2			)

    return sequence




def 			lowerCAmelCase(      SCREAMING_SNAKE_CASE_			)->						list:



    """simple docstring"""






    if bit_count == 0:
        return ["0"]

    if bit_count == 1:
        return ["0", "1"]

    UpperCamelCase_			  =						1 << bit_count  # defines the length of the sequence
    # 1<< n is equivalent to 2^n

    # recursive answer will generate answer for n-1 bits
    UpperCamelCase_			  =						gray_code_sequence_string(bit_count - 1			)

    UpperCamelCase_			  =						[]

    # append 0 to first half of the smaller sequence generated
    for i in range(seq_len // 2			):
        UpperCamelCase_			  =						"0" + smaller_sequence[i]
        sequence.append(SCREAMING_SNAKE_CASE_			)

    # append 1 to second half ... start from the end of the list
    for i in reversed(range(seq_len // 2			)			):
        UpperCamelCase_			  =						"1" + smaller_sequence[i]
        sequence.append(SCREAMING_SNAKE_CASE_			)

    return sequence


if __name__ == "__main__":
 import doctest

 doctest.testmod()
