






"""simple docstring"""


from __future__ import annotations

from scipy.special import comb  # type: ignore






class 						snake_case  :





    def __init__(							self     : Optional[int]    ,		A     : list[tuple[float, float]]      ):


      '''simple docstring'''




      a					:      List[Any]    =       list_of_points
      # Degree determines the flexibility of the curve.
      # Degree = 1 will produce a straight line.
      a					:      str    =       len(A      ) - 1





    def     lowerCamelCase__				(							self     : Optional[int]    ,		A     : float      ):


      '''simple docstring'''




      assert 0 <= t <= 1, "Time t must be between 0 and 1."
      a					:      list[float]    =       []
      for i in range(len(self.list_of_points      )      ):
        # basis function for each i
        output_values.append(
            comb(self.degree    ,		A      ) * ((1 - t) ** (self.degree - i)) * (t**i)      )
      # the basis must sum up to 1 for it to produce a valid Bezier curve.
      assert round(sum(A      )    ,		5      ) == 1
      return output_values





    def     lowerCamelCase__				(							self     : List[Any]    ,		A     : float      ):


      '''simple docstring'''




      assert 0 <= t <= 1, "Time t must be between 0 and 1."

      a					:      Optional[Any]    =       self.basis_function(A      )
      a					:      Tuple    =       0.0
      a					:      Dict    =       0.0
      for i in range(len(self.list_of_points      )      ):
        # For all points, sum up the product of i-th basis function and i-th point.
        x += basis_function[i] * self.list_of_points[i][0]
        y += basis_function[i] * self.list_of_points[i][1]
      return (x, y)





    def     lowerCamelCase__				(							self     : Union[str, Any]    ,		A     : float = 0.01      ):


      '''simple docstring'''




      from matplotlib import pyplot as plt  # type: ignore

      a					:      list[float]    =       []  # x coordinates of points to plot
      a					:      list[float]    =       []  # y coordinates of points to plot

      a					:      Optional[Any]    =       0.0
      while t <= 1:
        a					:      Tuple    =       self.bezier_curve_function(A      )
        to_plot_x.append(value[0]      )
        to_plot_y.append(value[1]      )
        t += step_size

      a					:      Any    =       [i[0] for i in self.list_of_points]
      a					:      Union[str, Any]    =       [i[1] for i in self.list_of_points]

      plt.plot(
          A    ,		A    ,		color='blue'    ,		label='Curve of Degree ' + str(self.degree      )    ,		)
      plt.scatter(A    ,		A    ,		color='red'    ,		label='Control Points'      )
      plt.legend()
      plt.show()


if __name__ == "__main__":
   import doctest

   doctest.testmod()

   BezierCurve([(1, 2), (3, 5)]).plot_curve()  # degree 1
   BezierCurve([(0, 0), (5, 5), (5, 0)]).plot_curve()  # degree 2
   BezierCurve([(0, 0), (5, 5), (5, 0), (2.5, -2.5)]).plot_curve()  # degree 3












"""simple docstring"""


import inspect
import unittest

import numpy as np

from transformers import ViTConfig, is_flax_available
from transformers.testing_utils import require_flax, slow

from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor


if is_flax_available():
   import jax

   from transformers.models.vit.modeling_flax_vit import FlaxViTForImageClassification, FlaxViTModel






class 						snake_case  (  unittest.TestCase	):





    def __init__(							self     : List[str]    ,		A     : Union[str, Any]    ,		A     : Optional[Any]=1_3    ,		A     : List[Any]=3_0    ,		A     : List[Any]=2    ,		A     : Optional[Any]=3    ,		A     : Union[str, Any]=True    ,		A     : Union[str, Any]=True    ,		A     : Optional[int]=3_2    ,		A     : Tuple=5    ,		A     : List[str]=4    ,		A     : List[Any]=3_7    ,		A     : Optional[Any]="gelu"    ,		A     : Any=0.1    ,		A     : Tuple=0.1    ,		A     : Optional[int]=1_0    ,		A     : Union[str, Any]=0.02    ,		):


      '''simple docstring'''




      a					:      Optional[Any]    =       parent
      a					:      Tuple    =       batch_size
      a					:      int    =       image_size
      a					:      str    =       patch_size
      a					:      List[str]    =       num_channels
      a					:      List[str]    =       is_training
      a					:      List[str]    =       use_labels
      a					:      Optional[int]    =       hidden_size
      a					:      Optional[Any]    =       num_hidden_layers
      a					:      Optional[int]    =       num_attention_heads
      a					:      str    =       intermediate_size
      a					:      List[str]    =       hidden_act
      a					:      List[str]    =       hidden_dropout_prob
      a					:      Union[str, Any]    =       attention_probs_dropout_prob
      a					:      List[Any]    =       type_sequence_label_size
      a					:      Optional[Any]    =       initializer_range

      # in ViT, the seq length equals the number of patches + 1 (we add 1 for the [CLS] token)
      a					:      Optional[int]    =       (image_size // patch_size) ** 2
      a					:      List[Any]    =       num_patches + 1





    def     lowerCamelCase__				(							self     : Tuple      ):


      '''simple docstring'''




      a					:      List[Any]    =       floats_tensor([self.batch_size, self.num_channels, self.image_size, self.image_size]      )

      a					:      str    =       ViTConfig(
          image_size=self.image_size    ,		patch_size=self.patch_size    ,		num_channels=self.num_channels    ,		hidden_size=self.hidden_size    ,		num_hidden_layers=self.num_hidden_layers    ,		num_attention_heads=self.num_attention_heads    ,		intermediate_size=self.intermediate_size    ,		hidden_act=self.hidden_act    ,		hidden_dropout_prob=self.hidden_dropout_prob    ,		attention_probs_dropout_prob=self.attention_probs_dropout_prob    ,		is_decoder=A    ,		initializer_range=self.initializer_range    ,		)

      return config, pixel_values





    def     lowerCamelCase__				(							self     : Union[str, Any]    ,		A     : str    ,		A     : Union[str, Any]      ):


      '''simple docstring'''




      a					:      Tuple    =       FlaxViTModel(config=A      )
      a					:      int    =       model(A      )
      # expected sequence length = num_patches + 1 (we add 1 for the [CLS] token)
      a					:      Optional[Any]    =       (self.image_size, self.image_size)
      a					:      List[str]    =       (self.patch_size, self.patch_size)
      a					:      Optional[Any]    =       (image_size[1] // patch_size[1]) * (image_size[0] // patch_size[0])
      self.parent.assertEqual(result.last_hidden_state.shape    ,		(self.batch_size, num_patches + 1, self.hidden_size)      )





    def     lowerCamelCase__				(							self     : Tuple    ,		A     : Dict    ,		A     : Optional[int]      ):


      '''simple docstring'''




      a					:      Optional[Any]    =       self.type_sequence_label_size
      a					:      List[Any]    =       FlaxViTForImageClassification(config=A      )
      a					:      Tuple    =       model(A      )
      self.parent.assertEqual(result.logits.shape    ,		(self.batch_size, self.type_sequence_label_size)      )

      # test greyscale images
      a					:      Dict    =       1
      a					:      Tuple    =       FlaxViTForImageClassification(A      )

      a					:      List[Any]    =       floats_tensor([self.batch_size, 1, self.image_size, self.image_size]      )
      a					:      Optional[int]    =       model(A      )





    def     lowerCamelCase__				(							self     : Optional[int]      ):


      '''simple docstring'''




      a					:      Optional[int]    =       self.prepare_config_and_inputs()
      (
          (
          a
      ),					(
          a
      ),					
      )					:      Dict    =       config_and_inputs
      a					:      List[Any]    =       {'pixel_values': pixel_values}
      return config, inputs_dict






@require_flax
class 						snake_case  (  UpperCAmelCase       ,			unittest.TestCase	):
    __magic_name__   					=					(FlaxViTModel, FlaxViTForImageClassification) if is_flax_available() else ()





    def     lowerCamelCase__				(							self     : Any      ):


      '''simple docstring'''




      a					:      Any    =       FlaxViTModelTester(self      )
      a					:      List[str]    =       ConfigTester(self    ,		config_class=A    ,		has_text_modality=A    ,		hidden_size=3_7      )





    def     lowerCamelCase__				(							self     : Tuple      ):


      '''simple docstring'''




      self.config_tester.run_common_tests()





    def     lowerCamelCase__				(							self     : List[Any]      ):


      '''simple docstring'''




      a					:      Union[str, Any]    =       self.model_tester.prepare_config_and_inputs()
      self.model_tester.create_and_check_model(*A      )





    def     lowerCamelCase__				(							self     : List[Any]      ):


      '''simple docstring'''




      a					:      Union[str, Any]    =       self.model_tester.prepare_config_and_inputs()
      self.model_tester.create_and_check_for_image_classification(*A      )





    def     lowerCamelCase__				(							self     : Dict      ):


      '''simple docstring'''




      a,					a					:      Optional[Any]    =       self.model_tester.prepare_config_and_inputs_for_common()

      for model_class in self.all_model_classes:
        a					:      Tuple    =       model_class(A      )
        a					:      str    =       inspect.signature(model.__call__      )
        # signature.parameters is an OrderedDict => so arg_names order is deterministic
        a					:      List[str]    =       [*signature.parameters.keys()]

        a					:      Dict    =       ['pixel_values']
        self.assertListEqual(arg_names[:1]    ,		A      )





    def     lowerCamelCase__				(							self     : Any      ):


      '''simple docstring'''




      a,					a					:      Tuple    =       self.model_tester.prepare_config_and_inputs_for_common()

      for model_class in self.all_model_classes:
        with self.subTest(model_class.__name__      ):
          a					:      List[Any]    =       self._prepare_for_class(A    ,		A      )
          a					:      Tuple    =       model_class(A      )

          @jax.jit
          def model_jitted(A     : Tuple    ,		**A     : int      ):
            return model(pixel_values=A    ,		**A      )

          with self.subTest('JIT Enabled'      ):
            a					:      List[str]    =       model_jitted(**A      ).to_tuple()

          with self.subTest('JIT Disabled'      ):
            with jax.disable_jit():
              a					:      List[str]    =       model_jitted(**A      ).to_tuple()

          self.assertEqual(len(A      )    ,		len(A      )      )
          for jitted_output, output in zip(A    ,		A      ):
            self.assertEqual(jitted_output.shape    ,		output.shape      )





    @slow
    def     lowerCamelCase__				(							self     : List[str]      ):


      '''simple docstring'''




      for model_class_name in self.all_model_classes:
        a					:      List[str]    =       model_class_name.from_pretrained('google/vit-base-patch16-224'      )
        a					:      Optional[Any]    =       model(np.ones((1, 3, 2_2_4, 2_2_4)      )      )
        self.assertIsNotNone(A      )




