






from collections import OrderedDict
from typing import Mapping

from packaging import version

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


lowerCamelCase       :       Tuple        =				logging.get_logger(__name__)

lowerCamelCase       :       Union[str, Any]        =				{
    '''google/mobilenet_v1_1.0_224''': '''https://huggingface.co/google/mobilenet_v1_1.0_224/resolve/main/config.json''',
    '''google/mobilenet_v1_0.75_192''': '''https://huggingface.co/google/mobilenet_v1_0.75_192/resolve/main/config.json''',
    # See all MobileNetV1 models at https://huggingface.co/models?filter=mobilenet_v1
}

class 						lowerCAmelCase   (       __a	):

					'''simple docstring'''

					_A  :	Optional[Any]     =					'''mobilenet_v1'''



					def __init__(     self :		int						,   __a :		List[Any]=3						,   __a :		Optional[int]=224						,   __a :		Optional[int]=1.0						,   __a :		Tuple=8						,   __a :		List[Any]="relu6"						,   __a :		Optional[int]=True						,   __a :		Union[str, Any]=0.999						,   __a :		Tuple=0.02						,   __a :		Dict=0.001						,   **__a :		str						,   )	->     List[str]:


												"""simple docstring"""

												super().__init__(**__a							)

												if depth_multiplier <= 0:
																			raise ValueError("""depth_multiplier must be greater than zero."""							)

												__lowercase					:							Any			=   num_channels
												__lowercase					:							str			=   image_size
												__lowercase					:							Any			=   depth_multiplier
												__lowercase					:							Tuple			=   min_depth
												__lowercase					:							int			=   hidden_act
												__lowercase					:							str			=   tf_padding
												__lowercase					:							List[Any]			=   classifier_dropout_prob
												__lowercase					:							Dict			=   initializer_range
												__lowercase					:							int			=   layer_norm_eps







class 						lowerCAmelCase   (       __a	):

					'''simple docstring'''

					_A  :	Tuple     =					version.parse('''1.11'''	)



					@property
					def 					lowerCAmelCase (     self :		str							)	->     Mapping[str, Mapping[int, str]]:


												"""simple docstring"""

												return OrderedDict([("""pixel_values""", {0: """batch"""})]							)



					@property
					def 					lowerCAmelCase (     self :		Dict							)	->     Mapping[str, Mapping[int, str]]:


												"""simple docstring"""

												if self.task == "image-classification":
																			return OrderedDict([("""logits""", {0: """batch"""})]							)
												else:
																			return OrderedDict([("""last_hidden_state""", {0: """batch"""}), ("""pooler_output""", {0: """batch"""})]							)



					@property
					def 					lowerCAmelCase (     self :		Tuple							)	->     float:


												"""simple docstring"""

												return 1E-4







from __future__ import annotations

import math

lowerCamelCase       :       List[Any]        =				'''2020.9.26'''
lowerCamelCase       :       str        =				'''xcodz-dot, cclaus, dhruvmanila'''
def 					snake_case_						(   lowerCAmelCase_				:  float				,				lowerCAmelCase_				:  float				,				lowerCAmelCase_				:  float				,				lowerCAmelCase_				:  float				,				lowerCAmelCase_				:  float					):
							if not all(isinstance(lowerCAmelCase_				,				(float, int)					) for val in locals().values()					):
														__lowercase					:							str			=   F"Input values must either be float or int: {list(locals().values()					)}"
														raise TypeError(lowerCAmelCase_					)
							__lowercase					:							List[Any]			=   ((x * distance) / (z + distance)) * scale
							__lowercase					:							Tuple			=   ((y * distance) / (z + distance)) * scale
							return projected_x, projected_y
def 					snake_case_						(   lowerCAmelCase_				:  float				,				lowerCAmelCase_				:  float				,				lowerCAmelCase_				:  float				,				lowerCAmelCase_				:  str				,				lowerCAmelCase_				:  float					):
							if not isinstance(lowerCAmelCase_				,				lowerCAmelCase_					):
														raise TypeError("""Axis must be a str"""					)
							__lowercase					:							Optional[int]			=   locals()
							del input_variables["axis"]
							if not all(isinstance(lowerCAmelCase_				,				(float, int)					) for val in input_variables.values()					):
														__lowercase					:							List[str]			=   (
														    """Input values except axis must either be float or int: """
														    F"{list(input_variables.values()					)}"
														)
														raise TypeError(lowerCAmelCase_					)
							__lowercase					:							Tuple			=   (angle % 360) / 450 * 180 / math.pi
							if axis == "z":
														__lowercase					:							int			=   x * math.cos(lowerCAmelCase_					) - y * math.sin(lowerCAmelCase_					)
														__lowercase					:							Tuple			=   y * math.cos(lowerCAmelCase_					) + x * math.sin(lowerCAmelCase_					)
														__lowercase					:							Union[str, Any]			=   z
							elif axis == "x":
														__lowercase					:							str			=   y * math.cos(lowerCAmelCase_					) - z * math.sin(lowerCAmelCase_					)
														__lowercase					:							Dict			=   z * math.cos(lowerCAmelCase_					) + y * math.sin(lowerCAmelCase_					)
														__lowercase					:							List[str]			=   x
							elif axis == "y":
														__lowercase					:							List[str]			=   x * math.cos(lowerCAmelCase_					) - z * math.sin(lowerCAmelCase_					)
														__lowercase					:							List[str]			=   z * math.cos(lowerCAmelCase_					) + x * math.sin(lowerCAmelCase_					)
														__lowercase					:							List[Any]			=   y
							else:
														raise ValueError("""not a valid axis, choose one of 'x', 'y', 'z'"""					)

							return new_x, new_y, new_z


if __name__ == "__main__":
	import doctest

	doctest.testmod()
	print(f'''{convert_to_ad(1.0, 2.0, 3.0, 10.0, 10.0) = }''')
	print(f'''{rotate(1.0, 2.0, 3.0, "y", 90.0) = }''')