
'''simple docstring'''



from __future__ import annotations

from typing import Any





def 	_A						(							*lowercase__		):
						if all(_check_not_integer(lowercase__		) for m in matrix_s		):
												for i in matrix_s[1:]:
																		_verify_matrix_sizes(matrix_s[0]						,						lowercase__		)
												return [[sum(lowercase__		) for t in zip(*lowercase__		)] for m in zip(*lowercase__		)]
						raise TypeError("""Expected a matrix, got int/list instead"""		)





def 	_A						(							lowercase__						,						lowercase__		):
						if (
						    _check_not_integer(lowercase__		)
						    and _check_not_integer(lowercase__		)
						    and _verify_matrix_sizes(lowercase__						,						lowercase__		)
						):
												return [[i - j for i, j in zip(*lowercase__		)] for m in zip(lowercase__						,						lowercase__		)]
						raise TypeError("""Expected a matrix, got int/list instead"""		)





def 	_A						(							lowercase__						,						lowercase__		):
						return [[x * n for x in row] for row in matrix]





def 	_A						(							lowercase__						,						lowercase__		):
						if _check_not_integer(lowercase__		) and _check_not_integer(lowercase__		):
												lowercase__	,  lowercase__								=    _verify_matrix_sizes(lowercase__						,						lowercase__		)

						if cols[0] != rows[1]:
												lowercase__								=    (
												    """Cannot multiply matrix of dimensions """
												    f'''({rows[0]},{cols[0]}) and ({rows[1]},{cols[1]})'''
												)
												raise ValueError(lowercase__		)
						return [
						    [sum(m * n for m, n in zip(lowercase__						,						lowercase__		)		) for j in zip(*lowercase__		)] for i in matrix_a
						]





def 	_A						(							lowercase__		):
						lowercase__								=    int(lowercase__		)
						return [[int(row == column		) for column in range(lowercase__		)] for row in range(lowercase__		)]





def 	_A						(							lowercase__						,						lowercase__ = True		):
						if _check_not_integer(lowercase__		):
												if return_map:
																		return map(lowercase__						,						zip(*lowercase__		)		)
												else:
																		return list(map(lowercase__						,						zip(*lowercase__		)		)		)
						raise TypeError("""Expected a matrix, got int/list instead"""		)





def 	_A						(							lowercase__						,						lowercase__						,						lowercase__		):
						lowercase__								=    matrix[:row] + matrix[row + 1 :]
						return [row[:column] + row[column + 1 :] for row in minor]





def 	_A						(							lowercase__		):
						if len(lowercase__		) == 1:
												return matrix[0][0]

						return sum(
						    x * determinant(minor(lowercase__						,						0						,						lowercase__		)		) * (-1) ** i
						    for i, x in enumerate(matrix[0]		)		)





def 	_A						(							lowercase__		):
						lowercase__								=    determinant(lowercase__		)
						if det == 0:
												return None

						lowercase__								=    [
						    [determinant(minor(lowercase__						,						lowercase__						,						lowercase__		)		) for j in range(len(lowercase__		)		)]
						    for i in range(len(lowercase__		)		)
						]

						lowercase__								=    [
						    [x * (-1) ** (row + col) for col, x in enumerate(matrix_minor[row]		)]
						    for row in range(len(lowercase__		)		)
						]
						lowercase__								=    list(transpose(lowercase__		)		)
						return scalar_multiply(lowercase__						,						1 / det		)





def 	_A						(							lowercase__		):
						return not isinstance(lowercase__						,						lowercase__		) and not isinstance(matrix[0]						,						lowercase__		)





def 	_A						(							lowercase__		):
						return len(lowercase__		), len(matrix[0]		)





def 	_A						(							lowercase__						,						lowercase__		):
						lowercase__								=    _shape(lowercase__		) + _shape(lowercase__		)
						if shape[0] != shape[3] or shape[1] != shape[2]:
												lowercase__								=    (
												    """operands could not be broadcast together with shape """
												    f'''({shape[0], shape[1]}), ({shape[2], shape[3]})'''
												)
												raise ValueError(lowercase__		)
						return (shape[0], shape[2]), (shape[1], shape[3])





def 	_A						(							):
						lowercase__								=    [[12, 10], [3, 9]]
						lowercase__								=    [[3, 4], [7, 4]]
						lowercase__								=    [[11, 12, 13, 14], [21, 22, 23, 24], [31, 32, 33, 34], [41, 42, 43, 44]]
						lowercase__								=    [[3, 0, 2], [2, 0, -2], [0, 1, 1]]
						print(f'''Add Operation, {add(lowercase__						,						lowercase__		) = } \n'''		)
						print(
						    f'''Multiply Operation, {multiply(lowercase__						,						lowercase__		) = } \n'''						,						)
						print(f'''Identity: {identity(5		)}\n'''		)
						print(f'''Minor of {matrix_c} = {minor(lowercase__						,						1						,						2		)} \n'''		)
						print(f'''Determinant of {matrix_b} = {determinant(lowercase__		)} \n'''		)
						print(f'''Inverse of {matrix_d} = {inverse(lowercase__		)}\n'''		)


if __name__ == "__main__":
				import doctest

				doctest.testmod()
				main()








'''simple docstring'''



import copy
from typing import Dict

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
from ..bit import BitConfig


__A       =      logging.get_logger(__name__)

__A       =      {
    "google/vit-hybrid-base-bit-384": "https://huggingface.co/vit-hybrid-base-bit-384/resolve/main/config.json",
    # See all ViT hybrid models at https://huggingface.co/models?filter=vit
}





class      A							(    __UpperCAmelCase			):
			lowerCamelCase							:							List[str]    						=					"""vit-hybrid"""



			def __init__(   self    ,       lowerCamelCase__=None    ,       lowerCamelCase__=768    ,       lowerCamelCase__=12    ,       lowerCamelCase__=12    ,       lowerCamelCase__=3_072    ,       lowerCamelCase__="gelu"    ,       lowerCamelCase__=0.0    ,       lowerCamelCase__=0.0    ,       lowerCamelCase__=0.02    ,       lowerCamelCase__=1e-12    ,       lowerCamelCase__=224    ,       lowerCamelCase__=1    ,       lowerCamelCase__=3    ,       lowerCamelCase__=[1, 1_024, 24, 24]    ,       lowerCamelCase__=True    ,       **lowerCamelCase__    ,       )     ->						Optional[Any]:




									'''simple docstring'''



									super().__init__(**lowerCamelCase__    )

									if backbone_config is None:
															logger.info("""`backbone_config` is `None`. Initializing the config with a `BiT` backbone."""    )
															lowercase__								=    {
															    """global_padding""": """same""",
															    """layer_type""": """bottleneck""",
															    """depths""": [3, 4, 9],
															    """out_features""": ["""stage3"""],
															    """embedding_dynamic_padding""": True,
															}

									if isinstance(lowerCamelCase__    ,       lowerCamelCase__    ):
															if "model_type" in backbone_config:
																					lowercase__								=    CONFIG_MAPPING[backbone_config["""model_type"""]]
															else:
																					logger.info(
																					    """`model_type` is not found in `backbone_config`. Use `Bit` as the backbone configuration class."""    )
																					lowercase__								=    BitConfig
															lowercase__								=    backbone_config_class(**lowerCamelCase__    )

									lowercase__								=    backbone_featmap_shape
									lowercase__								=    backbone_config
									lowercase__								=    hidden_size
									lowercase__								=    num_hidden_layers
									lowercase__								=    num_attention_heads
									lowercase__								=    intermediate_size
									lowercase__								=    hidden_act
									lowercase__								=    hidden_dropout_prob
									lowercase__								=    attention_probs_dropout_prob
									lowercase__								=    initializer_range
									lowercase__								=    layer_norm_eps
									lowercase__								=    image_size
									lowercase__								=    patch_size
									lowercase__								=    num_channels
									lowercase__								=    qkv_bias



			def A__	(   self    )     ->						Dict[str, any]:




									'''simple docstring'''



									lowercase__								=    copy.deepcopy(self.__dict__    )
									lowercase__								=    self.backbone_config.to_dict()
									lowercase__								=    self.__class__.model_type
									return output






