


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 	__lowercase    (unittest.TestCase  ):





							"""simple docstring"""







							def __init__(      self			,						lowerCAmelCase__			,						lowerCAmelCase__=1_3			,						lowerCAmelCase__=3_0			,						lowerCAmelCase__=2			,						lowerCAmelCase__=3			,						lowerCAmelCase__=True			,						lowerCAmelCase__=True			,						lowerCAmelCase__=3_2			,						lowerCAmelCase__=5			,						lowerCAmelCase__=4			,						lowerCAmelCase__=3_7			,						lowerCAmelCase__="gelu"			,						lowerCAmelCase__=0.1			,						lowerCAmelCase__=0.1			,						lowerCAmelCase__=1_0			,						lowerCAmelCase__=0.02			,						):





										"""simple docstring"""




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

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






							def 					UpperCamelCase__     (      self       ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		:     str					=					floats_tensor([self.batch_size, self.num_channels, self.image_size, self.image_size]       )

										SCREAMING_SNAKE_CASE_		:     List[Any]					=					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=lowerCAmelCase__			,						initializer_range=self.initializer_range			,						)

										return config, pixel_values






							def 					UpperCamelCase__     (      self			,						lowerCAmelCase__			,						lowerCAmelCase__       ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		:     List[Any]					=					FlaxViTModel(config=lowerCAmelCase__       )
										SCREAMING_SNAKE_CASE_		:     Optional[int]					=					model(lowerCAmelCase__       )
										# expected sequence length = num_patches + 1 (we add 1 for the [CLS] token)
										SCREAMING_SNAKE_CASE_		:     Dict					=					(self.image_size, self.image_size)
										SCREAMING_SNAKE_CASE_		:     Optional[int]					=					(self.patch_size, self.patch_size)
										SCREAMING_SNAKE_CASE_		:     int					=					(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 					UpperCamelCase__     (      self			,						lowerCAmelCase__			,						lowerCAmelCase__       ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		:     Tuple					=					self.type_sequence_label_size
										SCREAMING_SNAKE_CASE_		:     str					=					FlaxViTForImageClassification(config=lowerCAmelCase__       )
										SCREAMING_SNAKE_CASE_		:     Optional[int]					=					model(lowerCAmelCase__       )
										self.parent.assertEqual(result.logits.shape			,						(self.batch_size, self.type_sequence_label_size)       )

										# test greyscale images
										SCREAMING_SNAKE_CASE_		:     Union[str, Any]					=					1
										SCREAMING_SNAKE_CASE_		:     Union[str, Any]					=					FlaxViTForImageClassification(lowerCAmelCase__       )

										SCREAMING_SNAKE_CASE_		:     Dict					=					floats_tensor([self.batch_size, 1, self.image_size, self.image_size]       )
										SCREAMING_SNAKE_CASE_		:     List[Any]					=					model(lowerCAmelCase__       )






							def 					UpperCamelCase__     (      self       ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		:     str					=					self.prepare_config_and_inputs()
										(
										    (
										    SCREAMING_SNAKE_CASE_
										)		,      (
										    SCREAMING_SNAKE_CASE_
										)		,      
										)		:     int					=					config_and_inputs
										SCREAMING_SNAKE_CASE_		:     Dict					=					{'pixel_values': pixel_values}
										return config, inputs_dict







@require_flax
class 	__lowercase    (__SCREAMING_SNAKE_CASE	,       unittest.TestCase  ):





							"""simple docstring"""







							_UpperCAmelCase      =						(FlaxViTModel, FlaxViTForImageClassification) if is_flax_available() else ()






							def 					UpperCamelCase__     (      self       ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		:     Optional[Any]					=					FlaxViTModelTester(self       )
										SCREAMING_SNAKE_CASE_		:     Optional[int]					=					ConfigTester(self			,						config_class=lowerCAmelCase__			,						has_text_modality=lowerCAmelCase__			,						hidden_size=3_7       )






							def 					UpperCamelCase__     (      self       ):





										"""simple docstring"""




										self.config_tester.run_common_tests()






							def 					UpperCamelCase__     (      self       ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		:     Any					=					self.model_tester.prepare_config_and_inputs()
										self.model_tester.create_and_check_model(*lowerCAmelCase__       )






							def 					UpperCamelCase__     (      self       ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		:     Optional[Any]					=					self.model_tester.prepare_config_and_inputs()
										self.model_tester.create_and_check_for_image_classification(*lowerCAmelCase__       )






							def 					UpperCamelCase__     (      self       ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		,      SCREAMING_SNAKE_CASE_		:     int					=					self.model_tester.prepare_config_and_inputs_for_common()

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

													SCREAMING_SNAKE_CASE_		:     Tuple					=					['pixel_values']
													self.assertListEqual(arg_names[:1]			,						lowerCAmelCase__       )






							def 					UpperCamelCase__     (      self       ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		,      SCREAMING_SNAKE_CASE_		:     List[Any]					=					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_		:     Optional[Any]					=					self._prepare_for_class(lowerCAmelCase__			,						lowerCAmelCase__       )
																SCREAMING_SNAKE_CASE_		:     List[Any]					=					model_class(lowerCAmelCase__       )

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

																with self.subTest('JIT Enabled'       ):
																			SCREAMING_SNAKE_CASE_		:     int					=					model_jitted(**lowerCAmelCase__       ).to_tuple()

																with self.subTest('JIT Disabled'       ):
																			with jax.disable_jit():
																						SCREAMING_SNAKE_CASE_		:     str					=					model_jitted(**lowerCAmelCase__       ).to_tuple()

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






							@slow
							def 					UpperCamelCase__     (      self       ):





										"""simple docstring"""




										for model_class_name in self.all_model_classes:
													SCREAMING_SNAKE_CASE_		:     Dict					=					model_class_name.from_pretrained('google/vit-base-patch16-224'       )
													SCREAMING_SNAKE_CASE_		:     Dict					=					model(np.ones((1, 3, 2_2_4, 2_2_4)       )       )
													self.assertIsNotNone(lowerCAmelCase__       )






def _lowerCamelCase  (		snake_case  ):
							assert (
							    isinstance(snake_case     , snake_case  ) and number_of_steps > 0
							), F'number_of_steps needs to be positive integer, your input {number_of_steps}'
							if number_of_steps == 1:
														return 1
							_lowerCAmelCase			,		_lowerCAmelCase							=							1, 1
							for _ in range(number_of_steps - 1  ):
														_lowerCAmelCase			,		_lowerCAmelCase							=							current + previous, current
							return current


if __name__ == "__main__":
				import doctest

				doctest.testmod()






