




'''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 		SCREAMING_SNAKE_CASE__  (			unittest.TestCase	):





			def __init__(      self						:    str      ,		a_						:    Dict      ,		a_						:    Optional[Any]=13      ,		a_						:    Union[str, Any]=30      ,		a_						:    str=2      ,		a_						:    Union[str, Any]=3      ,		a_						:    Optional[Any]=True      ,		a_						:    Dict=True      ,		a_						:    Optional[Any]=32      ,		a_						:    str=5      ,		a_						:    Union[str, Any]=4      ,		a_						:    Optional[int]=37      ,		a_						:    Optional[Any]="gelu"      ,		a_						:    Optional[Any]=0.1      ,		a_						:    Any=0.1      ,		a_						:    Optional[Any]=10      ,		a_						:    Optional[Any]=0.02      ,		):



						"""simple docstring"""




						__snake_case			=		parent
						__snake_case			=		batch_size
						__snake_case			=		image_size
						__snake_case			=		patch_size
						__snake_case			=		num_channels
						__snake_case			=		is_training
						__snake_case			=		use_labels
						__snake_case			=		hidden_size
						__snake_case			=		num_hidden_layers
						__snake_case			=		num_attention_heads
						__snake_case			=		intermediate_size
						__snake_case			=		hidden_act
						__snake_case			=		hidden_dropout_prob
						__snake_case			=		attention_probs_dropout_prob
						__snake_case			=		type_sequence_label_size
						__snake_case			=		initializer_range

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





			def 							A (      self						:    str							):



						"""simple docstring"""




						__snake_case			=		floats_tensor([self.batch_size, self.num_channels, self.image_size, self.image_size]							)

						__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=a_      ,		initializer_range=self.initializer_range      ,		)

						return config, pixel_values





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



						"""simple docstring"""




						__snake_case			=		FlaxViTModel(config=a_							)
						__snake_case			=		model(a_							)
						# expected sequence length = num_patches + 1 (we add 1 for the [CLS] token)
						__snake_case			=		(self.image_size, self.image_size)
						__snake_case			=		(self.patch_size, self.patch_size)
						__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 							A (      self						:    List[str]      ,		a_						:    Dict      ,		a_						:    str							):



						"""simple docstring"""




						__snake_case			=		self.type_sequence_label_size
						__snake_case			=		FlaxViTForImageClassification(config=a_							)
						__snake_case			=		model(a_							)
						self.parent.assertEqual(result.logits.shape      ,		(self.batch_size, self.type_sequence_label_size)							)

						# test greyscale images
						__snake_case			=		1
						__snake_case			=		FlaxViTForImageClassification(a_							)

						__snake_case			=		floats_tensor([self.batch_size, 1, self.image_size, self.image_size]							)
						__snake_case			=		model(a_							)






			def 							A (      self						:    Any							):



						"""simple docstring"""




						__snake_case			=		self.prepare_config_and_inputs()
						(
						    (
						    __snake_case
						)		,     (
						    __snake_case
						)		,     
						)			=		config_and_inputs
						__snake_case			=		{"pixel_values": pixel_values}
						return config, inputs_dict







@require_flax
class 		SCREAMING_SNAKE_CASE__  (			_UpperCamelCase				,     unittest.TestCase	):
			__SCREAMING_SNAKE_CASE    =			(FlaxViTModel, FlaxViTForImageClassification) if is_flax_available() else ()





			def 							A (      self						:    str							):



						"""simple docstring"""




						__snake_case			=		FlaxViTModelTester(self							)
						__snake_case			=		ConfigTester(self      ,		config_class=a_      ,		has_text_modality=a_      ,		hidden_size=37							)





			def 							A (      self						:    Any							):



						"""simple docstring"""




						self.config_tester.run_common_tests()





			def 							A (      self						:    List[str]							):



						"""simple docstring"""




						__snake_case			=		self.model_tester.prepare_config_and_inputs()
						self.model_tester.create_and_check_model(*a_							)





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



						"""simple docstring"""




						__snake_case			=		self.model_tester.prepare_config_and_inputs()
						self.model_tester.create_and_check_for_image_classification(*a_							)





			def 							A (      self						:    List[Any]							):



						"""simple docstring"""




						__snake_case		,     __snake_case			=		self.model_tester.prepare_config_and_inputs_for_common()

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

									__snake_case			=		["pixel_values"]
									self.assertListEqual(arg_names[:1]      ,		a_							)





			def 							A (      self						:    List[str]							):



						"""simple docstring"""




						__snake_case		,     __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__							):
												__snake_case			=		self._prepare_for_class(a_      ,		a_							)
												__snake_case			=		model_class(a_							)

												@jax.jit
												def model_jitted(a_						:    Dict      ,		**a_						:    str							):
															return model(pixel_values=a_      ,		**a_							)

												with self.subTest("JIT Enabled"							):
															__snake_case			=		model_jitted(**a_							).to_tuple()

												with self.subTest("JIT Disabled"							):
															with jax.disable_jit():
																		__snake_case			=		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 							A (      self						:    Union[str, Any]							):



						"""simple docstring"""




						for model_class_name in self.all_model_classes:
									__snake_case			=		model_class_name.from_pretrained("google/vit-base-patch16-224"							)
									__snake_case			=		model(np.ones((1, 3, 224, 224)							)							)
									self.assertIsNotNone(a_							)









'''simple docstring'''






import os

import pytest

from datasets import (
    get_dataset_config_info,
    get_dataset_config_names,
    get_dataset_infos,
    get_dataset_split_names,
    inspect_dataset,
    inspect_metric,
)


lowercase				=pytest.mark.integration





@pytest.mark.parametrize('path'			,       ['paws', 'csv']				)
def lowerCamelCase__     (		__lowerCamelCase			:				List[Any]			,       __lowerCamelCase			:				Optional[Any]				):







   '''simple docstring'''




   inspect_dataset(__lowerCamelCase			,       __lowerCamelCase				)
   _UpperCAmelCase  :  List[str]				       =path + '.py'
   assert script_name in os.listdir(__lowerCamelCase				)
   assert "__pycache__" not in os.listdir(__lowerCamelCase				)





@pytest.mark.filterwarnings('ignore:inspect_metric is deprecated:FutureWarning'				)
@pytest.mark.filterwarnings('ignore:metric_module_factory is deprecated:FutureWarning'				)
@pytest.mark.parametrize('path'			,       ['accuracy']				)
def lowerCamelCase__     (		__lowerCamelCase			:				Dict			,       __lowerCamelCase			:				str				):







   '''simple docstring'''




   inspect_metric(__lowerCamelCase			,       __lowerCamelCase				)
   _UpperCAmelCase  :  List[Any]				       =path + '.py'
   assert script_name in os.listdir(__lowerCamelCase				)
   assert "__pycache__" not in os.listdir(__lowerCamelCase				)





@pytest.mark.parametrize(
    'path, config_name, expected_splits'			,       [
        ('squad', 'plain_text', ['train', 'validation']),
        ('dalle-mini/wit', 'dalle-mini--wit', ['train']),
        ('paws', 'labeled_final', ['train', 'test', 'validation']),
    ]			,       )
def lowerCamelCase__     (		__lowerCamelCase			:				Any			,       __lowerCamelCase			:				Optional[int]			,       __lowerCamelCase			:				str				):







   '''simple docstring'''




   _UpperCAmelCase  :  str				       =get_dataset_config_info(__lowerCamelCase			,       config_name=__lowerCamelCase				)
   assert info.config_name == config_name
   assert list(info.splits.keys()				) == expected_splits





@pytest.mark.parametrize(
    'path, config_name, expected_exception'			,       [
        ('paws', None, ValueError),
    ]			,       )
def lowerCamelCase__     (		__lowerCamelCase			:				List[Any]			,       __lowerCamelCase			:				Optional[Any]			,       __lowerCamelCase			:				List[str]				):







   '''simple docstring'''




   with pytest.raises(__lowerCamelCase				):
      get_dataset_config_info(__lowerCamelCase			,       config_name=__lowerCamelCase				)





@pytest.mark.parametrize(
    'path, expected'			,       [
        ('squad', 'plain_text'),
        ('acronym_identification', 'default'),
        ('lhoestq/squad', 'plain_text'),
        ('lhoestq/test', 'default'),
        ('lhoestq/demo1', 'lhoestq--demo1'),
        ('dalle-mini/wit', 'dalle-mini--wit'),
    ]			,       )
def lowerCamelCase__     (		__lowerCamelCase			:				Tuple			,       __lowerCamelCase			:				List[str]				):







   '''simple docstring'''




   _UpperCAmelCase  :  Dict				       =get_dataset_config_names(__lowerCamelCase				)
   assert expected in config_names





@pytest.mark.parametrize(
    'path, expected_configs, expected_splits_in_first_config'			,       [
        ('squad', ['plain_text'], ['train', 'validation']),
        ('dalle-mini/wit', ['dalle-mini--wit'], ['train']),
        ('paws', ['labeled_final', 'labeled_swap', 'unlabeled_final'], ['train', 'test', 'validation']),
    ]			,       )
def lowerCamelCase__     (		__lowerCamelCase			:				Tuple			,       __lowerCamelCase			:				List[Any]			,       __lowerCamelCase			:				List[Any]				):







   '''simple docstring'''




   _UpperCAmelCase  :  Optional[int]				       =get_dataset_infos(__lowerCamelCase				)
   assert list(infos.keys()				) == expected_configs
   _UpperCAmelCase  :  Optional[int]				       =expected_configs[0]
   assert expected_config in infos
   _UpperCAmelCase  :  Optional[int]				       =infos[expected_config]
   assert info.config_name == expected_config
   assert list(info.splits.keys()				) == expected_splits_in_first_config





@pytest.mark.parametrize(
    'path, expected_config, expected_splits'			,       [
        ('squad', 'plain_text', ['train', 'validation']),
        ('dalle-mini/wit', 'dalle-mini--wit', ['train']),
        ('paws', 'labeled_final', ['train', 'test', 'validation']),
    ]			,       )
def lowerCamelCase__     (		__lowerCamelCase			:				Tuple			,       __lowerCamelCase			:				Tuple			,       __lowerCamelCase			:				int				):







   '''simple docstring'''




   _UpperCAmelCase  :  str				       =get_dataset_infos(__lowerCamelCase				)
   assert expected_config in infos
   _UpperCAmelCase  :  Dict				       =infos[expected_config]
   assert info.config_name == expected_config
   assert list(info.splits.keys()				) == expected_splits





@pytest.mark.parametrize(
    'path, config_name, expected_exception'			,       [
        ('paws', None, ValueError),
    ]			,       )
def lowerCamelCase__     (		__lowerCamelCase			:				Union[str, Any]			,       __lowerCamelCase			:				Optional[Any]			,       __lowerCamelCase			:				Any				):







   '''simple docstring'''




   with pytest.raises(__lowerCamelCase				):
      get_dataset_split_names(__lowerCamelCase			,       config_name=__lowerCamelCase				)

