
"""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      _UpperCAmelCase							(		unittest.TestCase							):




      def __init__(							self   ,       lowercase_   ,       lowercase_=1_3   ,       lowercase_=3_0   ,       lowercase_=2   ,       lowercase_=3   ,       lowercase_=True   ,       lowercase_=True   ,       lowercase_=3_2   ,       lowercase_=5   ,       lowercase_=4   ,       lowercase_=3_7   ,       lowercase_="gelu"   ,       lowercase_=0.1   ,       lowercase_=0.1   ,       lowercase_=1_0   ,       lowercase_=0.0_2   ,       )						->					Optional[Any]:
          UpperCAmelCase									=					parent
          UpperCAmelCase									=					batch_size
          UpperCAmelCase									=					image_size
          UpperCAmelCase									=					patch_size
          UpperCAmelCase									=					num_channels
          UpperCAmelCase									=					is_training
          UpperCAmelCase									=					use_labels
          UpperCAmelCase									=					hidden_size
          UpperCAmelCase									=					num_hidden_layers
          UpperCAmelCase									=					num_attention_heads
          UpperCAmelCase									=					intermediate_size
          UpperCAmelCase									=					hidden_act
          UpperCAmelCase									=					hidden_dropout_prob
          UpperCAmelCase									=					attention_probs_dropout_prob
          UpperCAmelCase									=					type_sequence_label_size
          UpperCAmelCase									=					initializer_range

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




      def     a_      (							self							)						->					Optional[int]:
          UpperCAmelCase									=					floats_tensor([self.batch_size, self.num_channels, self.image_size, self.image_size]							)

          UpperCAmelCase									=					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=lowercase_   ,       initializer_range=self.initializer_range   ,       )

          return config, pixel_values




      def     a_      (							self   ,       lowercase_   ,       lowercase_							)						->					Union[str, Any]:
          UpperCAmelCase									=					FlaxViTModel(config=lowercase_							)
          UpperCAmelCase									=					model(lowercase_							)
          # expected sequence length = num_patches + 1 (we add 1 for the [CLS] token)
          UpperCAmelCase									=					(self.image_size, self.image_size)
          UpperCAmelCase									=					(self.patch_size, self.patch_size)
          UpperCAmelCase									=					(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     a_      (							self   ,       lowercase_   ,       lowercase_							)						->					Optional[Any]:
          UpperCAmelCase									=					self.type_sequence_label_size
          UpperCAmelCase									=					FlaxViTForImageClassification(config=lowercase_							)
          UpperCAmelCase									=					model(lowercase_							)
          self.parent.assertEqual(result.logits.shape   ,       (self.batch_size, self.type_sequence_label_size)							)

          # test greyscale images
          UpperCAmelCase									=					1
          UpperCAmelCase									=					FlaxViTForImageClassification(lowercase_							)

          UpperCAmelCase									=					floats_tensor([self.batch_size, 1, self.image_size, self.image_size]							)
          UpperCAmelCase									=					model(lowercase_							)




      def     a_      (							self							)						->					Optional[int]:
          UpperCAmelCase									=					self.prepare_config_and_inputs()
          (
              (
              UpperCAmelCase							
          )			,							(
              UpperCAmelCase							
          )			,														
          )									=					config_and_inputs
          UpperCAmelCase									=					{'pixel_values': pixel_values}
          return config, inputs_dict

@require_flax
class      _UpperCAmelCase							(		SCREAMING_SNAKE_CASE_     ,			unittest.TestCase							):
      __SCREAMING_SNAKE_CASE   :							List[Any]							      =	(FlaxViTModel, FlaxViTForImageClassification) if is_flax_available() else ()




      def     a_      (							self							)						->					None:
          UpperCAmelCase									=					FlaxViTModelTester(self							)
          UpperCAmelCase									=					ConfigTester(self   ,       config_class=lowercase_   ,       has_text_modality=lowercase_   ,       hidden_size=3_7							)




      def     a_      (							self							)						->					Any:
          self.config_tester.run_common_tests()




      def     a_      (							self							)						->					str:
          UpperCAmelCase									=					self.model_tester.prepare_config_and_inputs()
          self.model_tester.create_and_check_model(*lowercase_							)




      def     a_      (							self							)						->					Dict:
          UpperCAmelCase									=					self.model_tester.prepare_config_and_inputs()
          self.model_tester.create_and_check_for_image_classification(*lowercase_							)




      def     a_      (							self							)						->					Optional[int]:
          UpperCAmelCase			,							UpperCAmelCase									=					self.model_tester.prepare_config_and_inputs_for_common()

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

              UpperCAmelCase									=					['pixel_values']
              self.assertListEqual(arg_names[:1]   ,       lowercase_							)




      def     a_      (							self							)						->					List[str]:
          UpperCAmelCase			,							UpperCAmelCase									=					self.model_tester.prepare_config_and_inputs_for_common()

          for model_class in self.all_model_classes:
              with self.subTest(model_class.__name__							):
                  UpperCAmelCase									=					self._prepare_for_class(lowercase_   ,       lowercase_							)
                  UpperCAmelCase									=					model_class(lowercase_							)

                  @jax.jit
                  def model_jitted(lowercase_   ,       **lowercase_							):
                      return model(pixel_values=lowercase_   ,       **lowercase_							)

                  with self.subTest('JIT Enabled'							):
                      UpperCAmelCase									=					model_jitted(**lowercase_							).to_tuple()

                  with self.subTest('JIT Disabled'							):
                      with jax.disable_jit():
                          UpperCAmelCase									=					model_jitted(**lowercase_							).to_tuple()

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




      @slow
      def     a_      (							self							)						->					Dict:
          for model_class_name in self.all_model_classes:
              UpperCAmelCase									=					model_class_name.from_pretrained('google/vit-base-patch16-224'							)
              UpperCAmelCase									=					model(np.ones((1, 3, 2_2_4, 2_2_4)							)							)
              self.assertIsNotNone(lowercase_							)





"""simple docstring"""

import sys
import turtle




def     lowercase__						(					lowerCAmelCase				:					tuple[float, float] ,				lowerCAmelCase				:					tuple[float, float] ) ->      tuple[float, float]:






    """simple docstring"""




    return (pa[0] + pa[0]) / 2, (pa[1] + pa[1]) / 2




def     lowercase__						(					lowerCAmelCase				:					tuple[float, float] ,				lowerCAmelCase				:					tuple[float, float] ,				lowerCAmelCase				:					tuple[float, float] ,				lowerCAmelCase				:					int ,				) ->      None:






    """simple docstring"""




    my_pen.up()
    my_pen.goto(vertexa[0] ,				vertexa[1] )
    my_pen.down()
    my_pen.goto(vertexa[0] ,				vertexa[1] )
    my_pen.goto(vertexa[0] ,				vertexa[1] )
    my_pen.goto(vertexa[0] ,				vertexa[1] )

    if depth == 0:
        return

    triangle(lowerCAmelCase ,				get_mid(lowerCAmelCase ,				lowerCAmelCase ) ,				get_mid(lowerCAmelCase ,				lowerCAmelCase ) ,				depth - 1 )
    triangle(lowerCAmelCase ,				get_mid(lowerCAmelCase ,				lowerCAmelCase ) ,				get_mid(lowerCAmelCase ,				lowerCAmelCase ) ,				depth - 1 )
    triangle(lowerCAmelCase ,				get_mid(lowerCAmelCase ,				lowerCAmelCase ) ,				get_mid(lowerCAmelCase ,				lowerCAmelCase ) ,				depth - 1 )


if __name__ == "__main__":
   if len(sys.argv) != 2:
      raise ValueError(
          '''Correct format for using this script: '''
          '''python fractals.py <int:depth_for_fractal>'''
      )
   SCREAMING_SNAKE_CASE_    					=						turtle.Turtle()
   my_pen.ht()
   my_pen.speed(5)
   my_pen.pencolor('''red''')

   SCREAMING_SNAKE_CASE_    					=						[(-175, -125), (0, 175), (175, -125)]  # vertices of triangle
   triangle(vertices[0], vertices[1], vertices[2], int(sys.argv[1]))



