






"""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 ):






      '''simple docstring'''

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




          '''simple docstring'''


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

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




          '''simple docstring'''


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

          SCREAMING_SNAKE_CASE_      :  Union[str, 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=lowercase_						,	initializer_range=self.initializer_range						,	)

          return config, pixel_values
      def _SCREAMING_SNAKE_CASE (						self     :  Optional[Any]						,	lowercase_     :  List[Any]						,	lowercase_     :  Dict):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_      :  Optional[Any]    						=		FlaxViTModel(config=lowercase_)
          SCREAMING_SNAKE_CASE_      :  List[str]    						=		model(lowercase_)
          # expected sequence length = num_patches + 1 (we add 1 for the [CLS] token)
          SCREAMING_SNAKE_CASE_      :  str    						=		(self.image_size, self.image_size)
          SCREAMING_SNAKE_CASE_      :  Tuple    						=		(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 _SCREAMING_SNAKE_CASE (						self     :  str						,	lowercase_     :  Any						,	lowercase_     :  Optional[int]):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_      :  Tuple    						=		self.type_sequence_label_size
          SCREAMING_SNAKE_CASE_      :  Dict    						=		FlaxViTForImageClassification(config=lowercase_)
          SCREAMING_SNAKE_CASE_      :  List[Any]    						=		model(lowercase_)
          self.parent.assertEqual(result.logits.shape						,	(self.batch_size, self.type_sequence_label_size))

          # test greyscale images
          SCREAMING_SNAKE_CASE_      :  int    						=		1
          SCREAMING_SNAKE_CASE_      :  List[str]    						=		FlaxViTForImageClassification(lowercase_)

          SCREAMING_SNAKE_CASE_      :  str    						=		floats_tensor([self.batch_size, 1, self.image_size, self.image_size])
          SCREAMING_SNAKE_CASE_      :  Any    						=		model(lowercase_)



      def _SCREAMING_SNAKE_CASE (						self     :  Dict):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_      :  List[Any]    						=		self.prepare_config_and_inputs()
          (
              (
              SCREAMING_SNAKE_CASE_
          )						,			(
              SCREAMING_SNAKE_CASE_
          )						,			
          )      :  List[str]    						=		config_and_inputs
          SCREAMING_SNAKE_CASE_      :  str    						=		{'''pixel_values''': pixel_values}
          return config, inputs_dict




@require_flax
class 							lowerCAmelCase__				(			UpperCAmelCase__				,		unittest.TestCase ):






      '''simple docstring'''

      __UpperCamelCase	 =  (FlaxViTModel, FlaxViTForImageClassification) if is_flax_available() else ()
      def _SCREAMING_SNAKE_CASE (						self     :  Dict):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_      :  Optional[int]    						=		FlaxViTModelTester(self)
          SCREAMING_SNAKE_CASE_      :  int    						=		ConfigTester(self						,	config_class=lowercase_						,	has_text_modality=lowercase_						,	hidden_size=37)
      def _SCREAMING_SNAKE_CASE (						self     :  Optional[int]):




          '''simple docstring'''


          self.config_tester.run_common_tests()
      def _SCREAMING_SNAKE_CASE (						self     :  Dict):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_      :  Dict    						=		self.model_tester.prepare_config_and_inputs()
          self.model_tester.create_and_check_model(*lowercase_)
      def _SCREAMING_SNAKE_CASE (						self     :  Tuple):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_      :  List[Any]    						=		self.model_tester.prepare_config_and_inputs()
          self.model_tester.create_and_check_for_image_classification(*lowercase_)
      def _SCREAMING_SNAKE_CASE (						self     :  str):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_						,			SCREAMING_SNAKE_CASE_      :  List[str]    						=		self.model_tester.prepare_config_and_inputs_for_common()

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

              SCREAMING_SNAKE_CASE_      :  List[Any]    						=		['''pixel_values''']
              self.assertListEqual(arg_names[:1]						,	lowercase_)
      def _SCREAMING_SNAKE_CASE (						self     :  str):




          '''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_      :  Dict    						=		self._prepare_for_class(lowercase_						,	lowercase_)
                  SCREAMING_SNAKE_CASE_      :  Union[str, Any]    						=		model_class(lowercase_)

                  @jax.jit
                  def model_jitted(lowercase_     :  int						,	**lowercase_     :  Optional[Any]):
                      return model(pixel_values=lowercase_						,	**lowercase_)

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

                  with self.subTest('''JIT Disabled'''):
                      with jax.disable_jit():
                          SCREAMING_SNAKE_CASE_      :  Optional[int]    						=		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 _SCREAMING_SNAKE_CASE (						self     :  int):




          '''simple docstring'''


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






'''simple docstring'''



import os
import textwrap

import pyarrow as pa
import pytest

from datasets import ClassLabel, Features, Image
from datasets.packaged_modules.csv.csv import Csv

from ..utils import require_pil






@pytest.fixture
def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   Dict   ):
					__a			:       Optional[Any]					    =  tmp_path / 'file.csv'
					__a			:       Union[str, Any]					    =  textwrap.dedent(
					    '\\n        header1,header2\n        1,2\n        10,20\n        '   )
					with open(_SCREAMING_SNAKE_CASE						,      'w'   ) as f:
										f.write(_SCREAMING_SNAKE_CASE   )
					return str(_SCREAMING_SNAKE_CASE   )






@pytest.fixture
def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   Union[str, Any]   ):
					__a			:       str					    =  tmp_path / 'malformed_file.csv'
					__a			:       int					    =  textwrap.dedent(
					    '\\n        header1,header2\n        1,2\n        10,20,\n        '   )
					with open(_SCREAMING_SNAKE_CASE						,      'w'   ) as f:
										f.write(_SCREAMING_SNAKE_CASE   )
					return str(_SCREAMING_SNAKE_CASE   )






@pytest.fixture
def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   Optional[Any]						,      _SCREAMING_SNAKE_CASE      :   List[str]   ):
					__a			:       Optional[Any]					    =  tmp_path / 'csv_with_image.csv'
					__a			:       Dict					    =  textwrap.dedent(
					    F"""\
        image
        {image_file}
        """   )
					with open(_SCREAMING_SNAKE_CASE						,      'w'   ) as f:
										f.write(_SCREAMING_SNAKE_CASE   )
					return str(_SCREAMING_SNAKE_CASE   )






@pytest.fixture
def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   Optional[Any]   ):
					__a			:       Union[str, Any]					    =  tmp_path / 'csv_with_label.csv'
					__a			:       Any					    =  textwrap.dedent(
					    '\\n        label\n        good\n        bad\n        good\n        '   )
					with open(_SCREAMING_SNAKE_CASE						,      'w'   ) as f:
										f.write(_SCREAMING_SNAKE_CASE   )
					return str(_SCREAMING_SNAKE_CASE   )






@pytest.fixture
def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   List[Any]   ):
					__a			:       Dict					    =  tmp_path / 'csv_with_int_list.csv'
					__a			:       Tuple					    =  textwrap.dedent(
					    '\\n        int_list\n        1 2 3\n        4 5 6\n        7 8 9\n        '   )
					with open(_SCREAMING_SNAKE_CASE						,      'w'   ) as f:
										f.write(_SCREAMING_SNAKE_CASE   )
					return str(_SCREAMING_SNAKE_CASE   )






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   List[str]						,      _SCREAMING_SNAKE_CASE      :   int						,      _SCREAMING_SNAKE_CASE      :   List[str]   ):
					__a			:       int					    =  Csv()
					__a			:       str					    =  csv._generate_tables([[csv_file, malformed_csv_file]]   )
					with pytest.raises(_SCREAMING_SNAKE_CASE						,      match='Error tokenizing data'   ):
										for _ in generator:
															pass
					assert any(
					    record.levelname == 'ERROR'
					    and 'Failed to read file' in record.message
					    and os.path.basename(_SCREAMING_SNAKE_CASE   ) in record.message
					    for record in caplog.records   )






@require_pil
def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   List[str]   ):
					with open(_SCREAMING_SNAKE_CASE						,      encoding='utf-8'   ) as f:
										__a			:       Tuple					    =  f.read().splitlines()[1]
					__a			:       Tuple					    =  Csv(encoding='utf-8'						,      features=Features({'image': Image()}   )   )
					__a			:       Any					    =  csv._generate_tables([[csv_file_with_image]]   )
					__a			:       int					    =  pa.concat_tables([table for _, table in generator]   )
					assert pa_table.schema.field('image'   ).type == Image()()
					__a			:       Any					    =  pa_table.to_pydict()['image']
					assert generated_content == [{"path": image_file, "bytes": None}]






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   Union[str, Any]   ):
					with open(_SCREAMING_SNAKE_CASE						,      encoding='utf-8'   ) as f:
										__a			:       Tuple					    =  f.read().splitlines()[1:]
					__a			:       Optional[int]					    =  Csv(encoding='utf-8'						,      features=Features({'label': ClassLabel(names=['good', 'bad']   )}   )   )
					__a			:       List[str]					    =  csv._generate_tables([[csv_file_with_label]]   )
					__a			:       Dict					    =  pa.concat_tables([table for _, table in generator]   )
					assert pa_table.schema.field('label'   ).type == ClassLabel(names=['good', 'bad']   )()
					__a			:       int					    =  pa_table.to_pydict()['label']
					assert generated_content == [ClassLabel(names=['good', 'bad']   ).straint(_SCREAMING_SNAKE_CASE   ) for label in labels]






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   Optional[int]   ):
					__a			:       str					    =  Csv(encoding='utf-8'						,      sep=','						,      converters={'int_list': lambda _SCREAMING_SNAKE_CASE   : [int(_SCREAMING_SNAKE_CASE   ) for i in x.split()]}   )
					__a			:       Any					    =  csv._generate_tables([[csv_file_with_int_list]]   )
					__a			:       Any					    =  pa.concat_tables([table for _, table in generator]   )
					assert pa.types.is_list(pa_table.schema.field('int_list'   ).type   )
					__a			:       Tuple					    =  pa_table.to_pydict()['int_list']
					assert generated_content == [[1, 2, 3], [4, 5, 6], [7, 8, 9]]



