'''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 				_lowercase     (				unittest.TestCase			):


 '''simple docstring'''






 def __init__(      self   :	List[str]      ,       SCREAMING_SNAKE_CASE__   :	Dict      ,       SCREAMING_SNAKE_CASE__   :	Any=13      ,       SCREAMING_SNAKE_CASE__   :	Any=30      ,       SCREAMING_SNAKE_CASE__   :	Union[str, Any]=2      ,       SCREAMING_SNAKE_CASE__   :	Dict=3      ,       SCREAMING_SNAKE_CASE__   :	int=True      ,       SCREAMING_SNAKE_CASE__   :	Dict=True      ,       SCREAMING_SNAKE_CASE__   :	int=32      ,       SCREAMING_SNAKE_CASE__   :	int=5      ,       SCREAMING_SNAKE_CASE__   :	Tuple=4      ,       SCREAMING_SNAKE_CASE__   :	List[Any]=37      ,       SCREAMING_SNAKE_CASE__   :	List[Any]="gelu"      ,       SCREAMING_SNAKE_CASE__   :	Any=0.1      ,       SCREAMING_SNAKE_CASE__   :	List[Any]=0.1      ,       SCREAMING_SNAKE_CASE__   :	Dict=10      ,       SCREAMING_SNAKE_CASE__   :	List[str]=0.0_2      ,       )  ->    List[Any]:
  __lowerCAmelCase											=						parent
  __lowerCAmelCase											=						batch_size
  __lowerCAmelCase											=						image_size
  __lowerCAmelCase											=						patch_size
  __lowerCAmelCase											=						num_channels
  __lowerCAmelCase											=						is_training
  __lowerCAmelCase											=						use_labels
  __lowerCAmelCase											=						hidden_size
  __lowerCAmelCase											=						num_hidden_layers
  __lowerCAmelCase											=						num_attention_heads
  __lowerCAmelCase											=						intermediate_size
  __lowerCAmelCase											=						hidden_act
  __lowerCAmelCase											=						hidden_dropout_prob
  __lowerCAmelCase											=						attention_probs_dropout_prob
  __lowerCAmelCase											=						type_sequence_label_size
  __lowerCAmelCase											=						initializer_range

  # in ViT, the seq length equals the number of patches + 1 (we add 1 for the [CLS] token)
  __lowerCAmelCase											=						(image_size // patch_size) ** 2
  __lowerCAmelCase											=						num_patches + 1
 def a					(      self   :	List[Any]							)  ->    List[str]:
  __lowerCAmelCase											=						floats_tensor([self.batch_size, self.num_channels, self.image_size, self.image_size]							)

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

  # test greyscale images
  __lowerCAmelCase											=						1
  __lowerCAmelCase											=						FlaxViTForImageClassification(UpperCamelCase__							)

  __lowerCAmelCase											=						floats_tensor([self.batch_size, 1, self.image_size, self.image_size]							)
  __lowerCAmelCase											=						model(UpperCamelCase__							)





 def a					(      self   :	Union[str, Any]							)  ->    int:
  __lowerCAmelCase											=						self.prepare_config_and_inputs()
  (
      __lowerCAmelCase      
  )											=						config_and_inputs
  __lowerCAmelCase											=						{"pixel_values": pixel_values}
  return config, inputs_dict







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


 '''simple docstring'''






 _SCREAMING_SNAKE_CASE     :       Optional[int]      	=					(FlaxViTModel, FlaxViTForImageClassification) if is_flax_available() else ()
 def a					(      self   :	List[str]							)  ->    None:
  __lowerCAmelCase											=						FlaxViTModelTester(self							)
  __lowerCAmelCase											=						ConfigTester(self      ,       config_class=UpperCamelCase__      ,       has_text_modality=UpperCamelCase__      ,       hidden_size=37							)
 def a					(      self   :	Tuple							)  ->    int:
  self.config_tester.run_common_tests()
 def a					(      self   :	Any							)  ->    Union[str, Any]:
  __lowerCAmelCase											=						self.model_tester.prepare_config_and_inputs()
  self.model_tester.create_and_check_model(*UpperCamelCase__							)
 def a					(      self   :	str							)  ->    Dict:
  __lowerCAmelCase											=						self.model_tester.prepare_config_and_inputs()
  self.model_tester.create_and_check_for_image_classification(*UpperCamelCase__							)
 def a					(      self   :	str							)  ->    Dict:
  __lowerCAmelCase											=						self.model_tester.prepare_config_and_inputs_for_common()

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

   __lowerCAmelCase											=						["pixel_values"]
   self.assertListEqual(arg_names[:1]      ,       UpperCamelCase__							)
 def a					(      self   :	Optional[Any]							)  ->    Dict:
  __lowerCAmelCase											=						self.model_tester.prepare_config_and_inputs_for_common()

  for model_class in self.all_model_classes:
   with self.subTest(model_class.__name__							):
    __lowerCAmelCase											=						self._prepare_for_class(UpperCamelCase__      ,       UpperCamelCase__							)
    __lowerCAmelCase											=						model_class(UpperCamelCase__							)

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

    with self.subTest("""JIT Enabled"""							):
     __lowerCAmelCase											=						model_jitted(**UpperCamelCase__							).to_tuple()

    with self.subTest("""JIT Disabled"""							):
     with jax.disable_jit():
      __lowerCAmelCase											=						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 a					(      self   :	Tuple							)  ->    List[Any]:
  for model_class_name in self.all_model_classes:
   __lowerCAmelCase											=						model_class_name.from_pretrained("""google/vit-base-patch16-224"""							)
   __lowerCAmelCase											=						model(np.ones((1, 3, 2_24, 2_24)							)							)
   self.assertIsNotNone(UpperCamelCase__							)












import argparse
import os
import re


SCREAMING_SNAKE_CASE__       :      List[Any]  =   'src/transformers/models/auto'


# re pattern that matches mapping introductions:
#    SUPER_MODEL_MAPPING_NAMES = OrderedDict or SUPER_MODEL_MAPPING = OrderedDict
SCREAMING_SNAKE_CASE__       :      Optional[int]  =   re.compile(r'[A-Z_]+_MAPPING(\s+|_[A-Z_]+\s+)=\s+OrderedDict')
# re pattern that matches identifiers in mappings
SCREAMING_SNAKE_CASE__       :      Tuple  =   re.compile(r'\s*\(\s*"(\S[^"]+)"')

def      A      (      _SCREAMING_SNAKE_CASE ,_SCREAMING_SNAKE_CASE = False    )	-> int:
       with open(_SCREAMING_SNAKE_CASE ,"r" ,encoding="utf-8"    ) as f:
              lowerCamelCase   :      List[Any]			 =					f.read()

       lowerCamelCase   :      str			 =					content.split("\n"    )
       lowerCamelCase   :      int			 =					[]
       lowerCamelCase   :      List[Any]			 =					0
       while line_idx < len(_SCREAMING_SNAKE_CASE    ):
              if _re_intro_mapping.search(lines[line_idx]    ) is not None:
                     lowerCamelCase   :      Optional[int]			 =					len(re.search(r"^(\s*)\S" ,lines[line_idx]    ).groups()[0]    ) + 8
                     # Start of a new mapping!
                     while not lines[line_idx].startswith(" " * indent + "("    ):
                            new_lines.append(lines[line_idx]    )
                            line_idx += 1

                     lowerCamelCase   :      Optional[int]			 =					[]
                     while lines[line_idx].strip() != "]":
                            # Blocks either fit in one line or not
                            if lines[line_idx].strip() == "(":
                                   lowerCamelCase   :      List[str]			 =					line_idx
                                   while not lines[line_idx].startswith(" " * indent + ")"    ):
                                          line_idx += 1
                                   blocks.append("\n".join(lines[start_idx : line_idx + 1]    )    )
                            else:
                                   blocks.append(lines[line_idx]    )
                            line_idx += 1

                     # Sort blocks by their identifiers
                     lowerCamelCase   :      Union[str, Any]			 =					sorted(_SCREAMING_SNAKE_CASE ,key=lambda _SCREAMING_SNAKE_CASE    : _re_identifier.search(_SCREAMING_SNAKE_CASE    ).groups()[0]    )
                     new_lines += blocks
              else:
                     new_lines.append(lines[line_idx]    )
                     line_idx += 1

       if overwrite:
              with open(_SCREAMING_SNAKE_CASE ,"w" ,encoding="utf-8"    ) as f:
                     f.write("\n".join(_SCREAMING_SNAKE_CASE    )    )
       elif "\n".join(_SCREAMING_SNAKE_CASE    ) != content:
              return True

def      A      (      _SCREAMING_SNAKE_CASE = False    )	-> List[str]:
       lowerCamelCase   :      str			 =					[os.path.join(_SCREAMING_SNAKE_CASE ,_SCREAMING_SNAKE_CASE    ) for f in os.listdir(_SCREAMING_SNAKE_CASE    ) if f.endswith(".py"    )]
       lowerCamelCase   :      Union[str, Any]			 =					[sort_auto_mapping(_SCREAMING_SNAKE_CASE ,overwrite=_SCREAMING_SNAKE_CASE    ) for fname in fnames]

       if not overwrite and any(_SCREAMING_SNAKE_CASE    ):
              lowerCamelCase   :      str			 =					[f for f, d in zip(_SCREAMING_SNAKE_CASE ,_SCREAMING_SNAKE_CASE    ) if d]
              raise ValueError(
                  f'''The following files have auto mappings that need sorting: {", ".join(_SCREAMING_SNAKE_CASE    )}. Run `make style` to fix'''
                  " this."    )


if __name__ == "__main__":
       SCREAMING_SNAKE_CASE__       :      List[str]  =   argparse.ArgumentParser()
       parser.add_argument('--check_only', action='store_true', help='Whether to only check or fix style.')
       SCREAMING_SNAKE_CASE__       :      List[str]  =   parser.parse_args()

       sort_all_auto_mappings(not args.check_only)






