

'''simple docstring'''






def 					__lowerCamelCase			(      SCREAMING_SNAKE_CASE_     :	list[list[int]]    )							->   str:
      """simple docstring"""

      if len(SCREAMING_SNAKE_CASE_    ) == 0 or not all(len(SCREAMING_SNAKE_CASE_    ) == 2 for pair in coordinates    ):
            raise ValueError("The program cannot work out a fitting polynomial."    )

      if len({tuple(SCREAMING_SNAKE_CASE_    ) for pair in coordinates}    ) != len(SCREAMING_SNAKE_CASE_    ):
            raise ValueError("The program cannot work out a fitting polynomial."    )

      SCREAMING_SNAKE_CASE_      :			str     =       {x for x, _ in coordinates}
      if len(SCREAMING_SNAKE_CASE_    ) == 1:
            return F"x={coordinates[0][0]}"

      if len(SCREAMING_SNAKE_CASE_    ) != len(SCREAMING_SNAKE_CASE_    ):
            raise ValueError("The program cannot work out a fitting polynomial."    )

      SCREAMING_SNAKE_CASE_      :			Optional[int]     =       len(SCREAMING_SNAKE_CASE_    )

      SCREAMING_SNAKE_CASE_      :			Union[str, Any]     =       0
      SCREAMING_SNAKE_CASE_      :			list[list[float]]     =       []
      # put the x and x to the power values in a matrix
      while count_of_line < x:
            SCREAMING_SNAKE_CASE_      :			Tuple     =       0
            SCREAMING_SNAKE_CASE_      :			Union[str, Any]     =       coordinates[count_of_line][0]
            SCREAMING_SNAKE_CASE_      :			list[float]     =       []
            while count_in_line < x:
                  count_line.append(a ** (x - (count_in_line + 1))    )
                  count_in_line += 1
            matrix.append(SCREAMING_SNAKE_CASE_    )
            count_of_line += 1

      SCREAMING_SNAKE_CASE_      :			Optional[int]     =       0
      # put the y values into a vector
      SCREAMING_SNAKE_CASE_      :			list[float]     =       []
      while count_of_line < x:
            vector.append(coordinates[count_of_line][1]    )
            count_of_line += 1

      SCREAMING_SNAKE_CASE_      :			Union[str, Any]     =       0

      while count < x:
            SCREAMING_SNAKE_CASE_      :			Tuple     =       0
            while zahlen < x:
                  if count == zahlen:
                        zahlen += 1
                  if zahlen == x:
                        break
                  SCREAMING_SNAKE_CASE_      :			Any     =       matrix[zahlen][count] / matrix[count][count]
                  for counting_columns, item in enumerate(matrix[count]    ):
                        # manipulating all the values in the matrix
                        matrix[zahlen][counting_columns] -= item * bruch
                  # manipulating the values in the vector
                  vector[zahlen] -= vector[count] * bruch
                  zahlen += 1
            count += 1

      SCREAMING_SNAKE_CASE_      :			Any     =       0
      # make solutions
      SCREAMING_SNAKE_CASE_      :			list[str]     =       []
      while count < x:
            solution.append(str(vector[count] / matrix[count][count]    )    )
            count += 1

      SCREAMING_SNAKE_CASE_      :			Dict     =       0
      SCREAMING_SNAKE_CASE_      :			List[Any]     =       "f(x)="

      while count < x:
            SCREAMING_SNAKE_CASE_      :			list[str]     =       solution[count].split("E"    )
            if len(SCREAMING_SNAKE_CASE_    ) > 1:
                  SCREAMING_SNAKE_CASE_      :			List[str]     =       F"{remove_e[0]}*10^{remove_e[1]}"
            solved += F"x^{x - (count + 1)}*{solution[count]}"
            if count + 1 != x:
                  solved += "+"
            count += 1

      return solved


if __name__ == "__main__":
      print(points_to_polynomial([]))
      print(points_to_polynomial([[]]))
      print(points_to_polynomial([[1, 0], [2, 0], [3, 0]]))
      print(points_to_polynomial([[1, 1], [2, 1], [3, 1]]))
      print(points_to_polynomial([[1, 3], [2, 3], [3, 3]]))
      print(points_to_polynomial([[1, 1], [2, 2], [3, 3]]))
      print(points_to_polynomial([[1, 1], [2, 4], [3, 9]]))
      print(points_to_polynomial([[1, 3], [2, 6], [3, 1_1]]))
      print(points_to_polynomial([[1, -3], [2, -6], [3, -1_1]]))
      print(points_to_polynomial([[1, 5], [2, 2], [3, 9]]))




'''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

