

'''simple docstring'''






import warnings
from collections.abc import Callable
from typing import Any

import numpy
from matplotlib import pyplot

snake_case_       =       0.2_5 + 0.0J
snake_case_       =       -0.4 + 0.6J
snake_case_       =       -0.1 + 0.6_51J
snake_case_       =       -2.0
snake_case_       =       5_6
snake_case_       =       2.0
snake_case_       =       6_6_6


def 					__lowerCamelCase			(      SCREAMING_SNAKE_CASE_     :	complex  ,  SCREAMING_SNAKE_CASE_     :	numpy.ndarray    )							->   numpy.ndarray:
      """simple docstring"""

      return numpy.exp(SCREAMING_SNAKE_CASE_    ) + c_parameter


def 					__lowerCamelCase			(      SCREAMING_SNAKE_CASE_     :	complex  ,  SCREAMING_SNAKE_CASE_     :	numpy.ndarray    )							->   numpy.ndarray:
      """simple docstring"""

      return z_values * z_values + c_parameter


def 					__lowerCamelCase			(      SCREAMING_SNAKE_CASE_     :	float  ,  SCREAMING_SNAKE_CASE_     :	int    )							->   numpy.ndarray:
      """simple docstring"""

      SCREAMING_SNAKE_CASE_      :			List[str]     =       numpy.linspace(-window_size  ,  SCREAMING_SNAKE_CASE_  ,  SCREAMING_SNAKE_CASE_    )
      SCREAMING_SNAKE_CASE_      :			List[str]     =       x.reshape((nb_pixels, 1)    )
      SCREAMING_SNAKE_CASE_      :			List[Any]     =       numpy.linspace(-window_size  ,  SCREAMING_SNAKE_CASE_  ,  SCREAMING_SNAKE_CASE_    )
      SCREAMING_SNAKE_CASE_      :			Optional[Any]     =       y.reshape((1, nb_pixels)    )
      return x + 1.0J * y


def 					__lowerCamelCase			(      SCREAMING_SNAKE_CASE_     :	Callable[[Any, numpy.ndarray], numpy.ndarray]  ,  SCREAMING_SNAKE_CASE_     :	Any  ,  SCREAMING_SNAKE_CASE_     :	int  ,  SCREAMING_SNAKE_CASE_     :	numpy.ndarray  ,  SCREAMING_SNAKE_CASE_     :	float | None = None  ,  )							->   numpy.ndarray:
      """simple docstring"""

      SCREAMING_SNAKE_CASE_      :			Any     =       z_a.astype("complex64"    )
      for _ in range(SCREAMING_SNAKE_CASE_    ):
            SCREAMING_SNAKE_CASE_      :			Any     =       eval_function(SCREAMING_SNAKE_CASE_  ,  SCREAMING_SNAKE_CASE_    )
            if infinity is not None:
                  numpy.nan_to_num(SCREAMING_SNAKE_CASE_  ,  copy=SCREAMING_SNAKE_CASE_  ,  nan=SCREAMING_SNAKE_CASE_    )
                  SCREAMING_SNAKE_CASE_      :			Optional[Any]     =       infinity
      return z_n


def 					__lowerCamelCase			(      SCREAMING_SNAKE_CASE_     :	str  ,  SCREAMING_SNAKE_CASE_     :	Any  ,  SCREAMING_SNAKE_CASE_     :	float  ,  SCREAMING_SNAKE_CASE_     :	numpy.ndarray  ,  )							->   None:
      """simple docstring"""

      SCREAMING_SNAKE_CASE_      :			List[str]     =       (abs(SCREAMING_SNAKE_CASE_    )).transpose()
      SCREAMING_SNAKE_CASE_      :			str     =       abs_z_final[::-1, :]
      pyplot.matshow(abs_z_final < escape_radius    )
      pyplot.title(F"Julia set of ${function_label}$, $c={function_params}$"    )
      pyplot.show()


def 					__lowerCamelCase			(      )							->   None:
      """simple docstring"""

      warnings.filterwarnings(
          "ignore"  ,  category=SCREAMING_SNAKE_CASE_  ,  message="overflow encountered in multiply"    )
      warnings.filterwarnings(
          "ignore"  ,  category=SCREAMING_SNAKE_CASE_  ,  message="invalid value encountered in multiply"  ,  )
      warnings.filterwarnings(
          "ignore"  ,  category=SCREAMING_SNAKE_CASE_  ,  message="overflow encountered in absolute"    )
      warnings.filterwarnings(
          "ignore"  ,  category=SCREAMING_SNAKE_CASE_  ,  message="overflow encountered in exp"    )


if __name__ == "__main__":
      snake_case_       =       prepare_grid(window_size, nb_pixels)

      ignore_overflow_warnings()  # See file header for explanations

      snake_case_       =       2_4
      snake_case_       =       2 * abs(c_cauliflower) + 1
      snake_case_       =       iterate_function(
          eval_quadratic_polynomial,
          c_cauliflower,
          nb_iterations,
          z_a,
          infinity=1.1 * escape_radius,
      )
      show_results('z^2+c', c_cauliflower, escape_radius, z_final)

      snake_case_       =       6_4
      snake_case_       =       2 * abs(c_polynomial_a) + 1
      snake_case_       =       iterate_function(
          eval_quadratic_polynomial,
          c_polynomial_a,
          nb_iterations,
          z_a,
          infinity=1.1 * escape_radius,
      )
      show_results('z^2+c', c_polynomial_a, escape_radius, z_final)

      snake_case_       =       1_6_1
      snake_case_       =       2 * abs(c_polynomial_a) + 1
      snake_case_       =       iterate_function(
          eval_quadratic_polynomial,
          c_polynomial_a,
          nb_iterations,
          z_a,
          infinity=1.1 * escape_radius,
      )
      show_results('z^2+c', c_polynomial_a, escape_radius, z_final)

      snake_case_       =       1_2
      snake_case_       =       1_0_0_0_0.0
      snake_case_       =       iterate_function(
          eval_exponential,
          c_exponential,
          nb_iterations,
          z_a + 2,
          infinity=1.0E10,
      )
      show_results('e^z+c', c_exponential, escape_radius, z_final)




'''simple docstring'''






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


snake_case_       =       logging.get_logger(__name__)

snake_case_       =       {
    'apple/mobilevit-small': 'https://huggingface.co/apple/mobilevit-small/resolve/main/config.json',
    'apple/mobilevit-x-small': 'https://huggingface.co/apple/mobilevit-x-small/resolve/main/config.json',
    'apple/mobilevit-xx-small': 'https://huggingface.co/apple/mobilevit-xx-small/resolve/main/config.json',
    'apple/deeplabv3-mobilevit-small': (
        'https://huggingface.co/apple/deeplabv3-mobilevit-small/resolve/main/config.json'
    ),
    'apple/deeplabv3-mobilevit-x-small': (
        'https://huggingface.co/apple/deeplabv3-mobilevit-x-small/resolve/main/config.json'
    ),
    'apple/deeplabv3-mobilevit-xx-small': (
        'https://huggingface.co/apple/deeplabv3-mobilevit-xx-small/resolve/main/config.json'
    ),
    # See all MobileViT models at https://huggingface.co/models?filter=mobilevit
}
class 	SCREAMING_SNAKE_CASE__			(				_UpperCAmelCase      ):
    _A			    =							"mobilevit"




    def __init__(					self				,     lowercase__=3				,     lowercase__=256				,     lowercase__=2				,     lowercase__=[144, 192, 240]				,     lowercase__=[16, 32, 64, 96, 128, 160, 640]				,     lowercase__=4				,     lowercase__=2.0				,     lowercase__=4.0				,     lowercase__="silu"				,     lowercase__=3				,     lowercase__=32				,     lowercase__=0.1				,     lowercase__=0.0				,     lowercase__=0.1				,     lowercase__=0.02				,     lowercase__=1e-5				,     lowercase__=True				,     lowercase__=256				,     lowercase__=[6, 12, 18]				,     lowercase__=0.1				,     lowercase__=255				,     **lowercase__				,     ):






          """simple docstring"""






          super().__init__(**lowercase__			)

          SCREAMING_SNAKE_CASE_      :			int     =       num_channels
          SCREAMING_SNAKE_CASE_      :			List[str]     =       image_size
          SCREAMING_SNAKE_CASE_      :			Optional[Any]     =       patch_size
          SCREAMING_SNAKE_CASE_      :			List[str]     =       hidden_sizes
          SCREAMING_SNAKE_CASE_      :			Union[str, Any]     =       neck_hidden_sizes
          SCREAMING_SNAKE_CASE_      :			Optional[Any]     =       num_attention_heads
          SCREAMING_SNAKE_CASE_      :			Optional[int]     =       mlp_ratio
          SCREAMING_SNAKE_CASE_      :			Optional[Any]     =       expand_ratio
          SCREAMING_SNAKE_CASE_      :			str     =       hidden_act
          SCREAMING_SNAKE_CASE_      :			Optional[Any]     =       conv_kernel_size
          SCREAMING_SNAKE_CASE_      :			List[Any]     =       output_stride
          SCREAMING_SNAKE_CASE_      :			Tuple     =       hidden_dropout_prob
          SCREAMING_SNAKE_CASE_      :			int     =       attention_probs_dropout_prob
          SCREAMING_SNAKE_CASE_      :			Tuple     =       classifier_dropout_prob
          SCREAMING_SNAKE_CASE_      :			Optional[int]     =       initializer_range
          SCREAMING_SNAKE_CASE_      :			Union[str, Any]     =       layer_norm_eps
          SCREAMING_SNAKE_CASE_      :			str     =       qkv_bias

          # decode head attributes for semantic segmentation
          SCREAMING_SNAKE_CASE_      :			Optional[int]     =       aspp_out_channels
          SCREAMING_SNAKE_CASE_      :			Optional[Any]     =       atrous_rates
          SCREAMING_SNAKE_CASE_      :			List[Any]     =       aspp_dropout_prob
          SCREAMING_SNAKE_CASE_      :			Any     =       semantic_loss_ignore_index






class 	SCREAMING_SNAKE_CASE__			(				_UpperCAmelCase      ):
    _A			    =							version.parse("1.11"      )




    @property
    def   __lowerCamelCase      (					self			):






          """simple docstring"""






          return OrderedDict([("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"})]			)




    @property
    def   __lowerCamelCase      (					self			):






          """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			):






          """simple docstring"""






          return 1e-4

