

"""simple docstring"""




A_				:      Union[str, Any]           =			"\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n"

A_				:      Tuple           =			[{"type": "code", "content": INSTALL_CONTENT}]
A_				:      Optional[Any]           =			{
    "{processor_class}": "FakeProcessorClass",
    "{model_class}": "FakeModelClass",
    "{object_class}": "FakeObjectClass",
}





"""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  lowerCamelCase    (unittest.TestCase      ):

			def __init__(       self					:    List[Any]     ,					__UpperCAmelCase					:    Dict     ,					__UpperCAmelCase					:    Optional[Any]=1_3     ,					__UpperCAmelCase					:    Tuple=3_0     ,					__UpperCAmelCase					:    str=2     ,					__UpperCAmelCase					:    List[Any]=3     ,					__UpperCAmelCase					:    Any=True     ,					__UpperCAmelCase					:    Dict=True     ,					__UpperCAmelCase					:    Optional[Any]=3_2     ,					__UpperCAmelCase					:    Any=5     ,					__UpperCAmelCase					:    Optional[Any]=4     ,					__UpperCAmelCase					:    Tuple=3_7     ,					__UpperCAmelCase					:    List[str]="gelu"     ,					__UpperCAmelCase					:    Union[str, Any]=0.1     ,					__UpperCAmelCase					:    List[str]=0.1     ,					__UpperCAmelCase					:    int=1_0     ,					__UpperCAmelCase					:    Any=0.02     ,					) ->     Union[str, Any]:
						SCREAMING_SNAKE_CASE__										=   parent
						SCREAMING_SNAKE_CASE__										=   batch_size
						SCREAMING_SNAKE_CASE__										=   image_size
						SCREAMING_SNAKE_CASE__										=   patch_size
						SCREAMING_SNAKE_CASE__										=   num_channels
						SCREAMING_SNAKE_CASE__										=   is_training
						SCREAMING_SNAKE_CASE__										=   use_labels
						SCREAMING_SNAKE_CASE__										=   hidden_size
						SCREAMING_SNAKE_CASE__										=   num_hidden_layers
						SCREAMING_SNAKE_CASE__										=   num_attention_heads
						SCREAMING_SNAKE_CASE__										=   intermediate_size
						SCREAMING_SNAKE_CASE__										=   hidden_act
						SCREAMING_SNAKE_CASE__										=   hidden_dropout_prob
						SCREAMING_SNAKE_CASE__										=   attention_probs_dropout_prob
						SCREAMING_SNAKE_CASE__										=   type_sequence_label_size
						SCREAMING_SNAKE_CASE__										=   initializer_range

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

			def        SCREAMING_SNAKE_CASE					(       self					:    List[str]							) ->     Any:
						SCREAMING_SNAKE_CASE__										=   floats_tensor([self.batch_size, self.num_channels, self.image_size, self.image_size]							)

						SCREAMING_SNAKE_CASE__										=   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=__UpperCAmelCase     ,					initializer_range=self.initializer_range     ,					)

						return config, pixel_values

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

						# test greyscale images
						SCREAMING_SNAKE_CASE__										=   1
						SCREAMING_SNAKE_CASE__										=   FlaxViTForImageClassification(__UpperCAmelCase							)

						SCREAMING_SNAKE_CASE__										=   floats_tensor([self.batch_size, 1, self.image_size, self.image_size]							)
						SCREAMING_SNAKE_CASE__										=   model(__UpperCAmelCase							)





			def        SCREAMING_SNAKE_CASE					(       self					:    Tuple							) ->     str:
						SCREAMING_SNAKE_CASE__										=   self.prepare_config_and_inputs()
						(
						    (
						    SCREAMING_SNAKE_CASE__
						)				,		(
						    SCREAMING_SNAKE_CASE__
						)				,		
						)										=   config_and_inputs
						SCREAMING_SNAKE_CASE__										=   {"""pixel_values""": pixel_values}
						return config, inputs_dict





@require_flax
class  lowerCamelCase    (A__      ,unittest.TestCase      ):
			lowerCamelCase__ :		Tuple       		=				(FlaxViTModel, FlaxViTForImageClassification) if is_flax_available() else ()

			def        SCREAMING_SNAKE_CASE					(       self					:    int							) ->     None:
						SCREAMING_SNAKE_CASE__										=   FlaxViTModelTester(self							)
						SCREAMING_SNAKE_CASE__										=   ConfigTester(self     ,					config_class=__UpperCAmelCase     ,					has_text_modality=__UpperCAmelCase     ,					hidden_size=3_7							)

			def        SCREAMING_SNAKE_CASE					(       self					:    int							) ->     Dict:
						self.config_tester.run_common_tests()

			def        SCREAMING_SNAKE_CASE					(       self					:    Optional[int]							) ->     Optional[Any]:
						SCREAMING_SNAKE_CASE__										=   self.model_tester.prepare_config_and_inputs()
						self.model_tester.create_and_check_model(*__UpperCAmelCase							)

			def        SCREAMING_SNAKE_CASE					(       self					:    Optional[Any]							) ->     List[str]:
						SCREAMING_SNAKE_CASE__										=   self.model_tester.prepare_config_and_inputs()
						self.model_tester.create_and_check_for_image_classification(*__UpperCAmelCase							)

			def        SCREAMING_SNAKE_CASE					(       self					:    Any							) ->     str:
						SCREAMING_SNAKE_CASE__				,		SCREAMING_SNAKE_CASE__										=   self.model_tester.prepare_config_and_inputs_for_common()

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

									SCREAMING_SNAKE_CASE__										=   ["""pixel_values"""]
									self.assertListEqual(arg_names[:1]     ,					__UpperCAmelCase							)

			def        SCREAMING_SNAKE_CASE					(       self					:    Any							) ->     Optional[Any]:
						SCREAMING_SNAKE_CASE__				,		SCREAMING_SNAKE_CASE__										=   self.model_tester.prepare_config_and_inputs_for_common()

						for model_class in self.all_model_classes:
									with self.subTest(model_class.__name__							):
												SCREAMING_SNAKE_CASE__										=   self._prepare_for_class(__UpperCAmelCase     ,					__UpperCAmelCase							)
												SCREAMING_SNAKE_CASE__										=   model_class(__UpperCAmelCase							)

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

												with self.subTest("""JIT Enabled"""							):
															SCREAMING_SNAKE_CASE__										=   model_jitted(**__UpperCAmelCase							).to_tuple()

												with self.subTest("""JIT Disabled"""							):
															with jax.disable_jit():
																		SCREAMING_SNAKE_CASE__										=   model_jitted(**__UpperCAmelCase							).to_tuple()

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





			@slow
			def        SCREAMING_SNAKE_CASE					(       self					:    Any							) ->     Dict:
						for model_class_name in self.all_model_classes:
									SCREAMING_SNAKE_CASE__										=   model_class_name.from_pretrained("""google/vit-base-patch16-224"""							)
									SCREAMING_SNAKE_CASE__										=   model(np.ones((1, 3, 2_2_4, 2_2_4)							)							)
									self.assertIsNotNone(__UpperCAmelCase							)


