





import inspect
import unittest

from transformers import RegNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available

from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor


if is_flax_available():
     import jax
     import jax.numpy as jnp

     from transformers.models.regnet.modeling_flax_regnet import FlaxRegNetForImageClassification, FlaxRegNetModel

if is_vision_available():
     from PIL import Image

     from transformers import AutoImageProcessor



class 							_UpperCAmelCase       (       unittest.TestCase       ):

  """simple docstring"""


  def __init__(							self					:						List[str]   ,    lowerCAmelCase_					:						Optional[int]   ,    lowerCAmelCase_					:						Optional[int]=3   ,    lowerCAmelCase_					:						Dict=3_2   ,    lowerCAmelCase_					:						Tuple=3   ,    lowerCAmelCase_					:						Union[str, Any]=1_0   ,    lowerCAmelCase_					:						List[str]=[1_0, 2_0, 3_0, 4_0]   ,    lowerCAmelCase_					:						Optional[int]=[1, 1, 2, 1]   ,    lowerCAmelCase_					:						Union[str, Any]=True   ,    lowerCAmelCase_					:						Any=True   ,    lowerCAmelCase_					:						Tuple="relu"   ,    lowerCAmelCase_					:						Union[str, Any]=3   ,    lowerCAmelCase_					:						Optional[int]=None   ,    )				->		int:
     __lowerCAmelCase				      =      parent
     __lowerCAmelCase				      =      batch_size
     __lowerCAmelCase				      =      image_size
     __lowerCAmelCase				      =      num_channels
     __lowerCAmelCase				      =      embeddings_size
     __lowerCAmelCase				      =      hidden_sizes
     __lowerCAmelCase				      =      depths
     __lowerCAmelCase				      =      is_training
     __lowerCAmelCase				      =      use_labels
     __lowerCAmelCase				      =      hidden_act
     __lowerCAmelCase				      =      num_labels
     __lowerCAmelCase				      =      scope
     __lowerCAmelCase				      =      len(lowerCAmelCase_	)






  def 							lowercase						(							self					:						Optional[int]	)				->		List[Any]:
     __lowerCAmelCase				      =      floats_tensor([self.batch_size, self.num_channels, self.image_size, self.image_size]	)

     __lowerCAmelCase				      =      self.get_config()

     return config, pixel_values






  def 							lowercase						(							self					:						Tuple	)				->		List[Any]:
     return RegNetConfig(
         num_channels=self.num_channels   ,    embeddings_size=self.embeddings_size   ,    hidden_sizes=self.hidden_sizes   ,    depths=self.depths   ,    hidden_act=self.hidden_act   ,    num_labels=self.num_labels   ,    image_size=self.image_size   ,    )






  def 							lowercase						(							self					:						List[str]   ,    lowerCAmelCase_					:						List[str]   ,    lowerCAmelCase_					:						List[str]	)				->		str:
     __lowerCAmelCase				      =      FlaxRegNetModel(config=lowerCAmelCase_	)
     __lowerCAmelCase				      =      model(lowerCAmelCase_	)

     # Output shape (b, c, h, w)
     self.parent.assertEqual(
         result.last_hidden_state.shape   ,    (self.batch_size, self.hidden_sizes[-1], self.image_size // 3_2, self.image_size // 3_2)   ,    )






  def 							lowercase						(							self					:						str   ,    lowerCAmelCase_					:						Optional[int]   ,    lowerCAmelCase_					:						int	)				->		Tuple:
     __lowerCAmelCase				      =      self.num_labels
     __lowerCAmelCase				      =      FlaxRegNetForImageClassification(config=lowerCAmelCase_	)
     __lowerCAmelCase				      =      model(lowerCAmelCase_	)
     self.parent.assertEqual(result.logits.shape   ,    (self.batch_size, self.num_labels)	)






  def 							lowercase						(							self					:						List[Any]	)				->		Optional[Any]:
     __lowerCAmelCase				      =      self.prepare_config_and_inputs()
     __lowerCAmelCase      ,      __lowerCAmelCase				      =      config_and_inputs
     __lowerCAmelCase				      =      {'pixel_values': pixel_values}
     return config, inputs_dict





@require_flax
class 							_UpperCAmelCase       (       _UpperCamelCase						,       unittest.TestCase       ):

  """simple docstring"""


  a_              =					(FlaxRegNetModel, FlaxRegNetForImageClassification) if is_flax_available() else ()

  a_              =					False
  a_              =					False
  a_              =					False






  def 							lowercase						(							self					:						Dict	)				->		None:
     __lowerCAmelCase				      =      FlaxRegNetModelTester(self	)
     __lowerCAmelCase				      =      ConfigTester(self   ,    config_class=lowerCAmelCase_   ,    has_text_modality=lowerCAmelCase_	)






  def 							lowercase						(							self					:						int	)				->		Optional[int]:
     self.create_and_test_config_common_properties()
     self.config_tester.create_and_test_config_to_json_string()
     self.config_tester.create_and_test_config_to_json_file()
     self.config_tester.create_and_test_config_from_and_save_pretrained()
     self.config_tester.create_and_test_config_with_num_labels()
     self.config_tester.check_config_can_be_init_without_params()
     self.config_tester.check_config_arguments_init()






  def 							lowercase						(							self					:						str	)				->		Union[str, Any]:
     return






  def 							lowercase						(							self					:						Dict	)				->		str:
     __lowerCAmelCase				      =      self.model_tester.prepare_config_and_inputs()
     self.model_tester.create_and_check_model(*lowerCAmelCase_	)






  def 							lowercase						(							self					:						Union[str, Any]	)				->		Tuple:
     __lowerCAmelCase				      =      self.model_tester.prepare_config_and_inputs()
     self.model_tester.create_and_check_for_image_classification(*lowerCAmelCase_	)






  @unittest.skip(reason='RegNet does not use inputs_embeds'	)
  def 							lowercase						(							self					:						Union[str, Any]	)				->		Any:
     pass






  @unittest.skip(reason='RegNet does not support input and output embeddings'	)
  def 							lowercase						(							self					:						Tuple	)				->		Tuple:
     pass






  def 							lowercase						(							self					:						Optional[Any]	)				->		str:
     __lowerCAmelCase      ,      __lowerCAmelCase				      =      self.model_tester.prepare_config_and_inputs_for_common()

     for model_class in self.all_model_classes:
        __lowerCAmelCase				      =      model_class(lowerCAmelCase_	)
        __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]   ,    lowerCAmelCase_	)






  def 							lowercase						(							self					:						List[Any]	)				->		Union[str, Any]:
     def check_hidden_states_output(lowerCAmelCase_					:						Any   ,    lowerCAmelCase_					:						Tuple   ,    lowerCAmelCase_					:						Tuple	):
        __lowerCAmelCase				      =      model_class(lowerCAmelCase_	)

        __lowerCAmelCase				      =      model(**self._prepare_for_class(lowerCAmelCase_   ,    lowerCAmelCase_	)	)

        __lowerCAmelCase				      =      outputs.encoder_hidden_states if config.is_encoder_decoder else outputs.hidden_states

        __lowerCAmelCase				      =      self.model_tester.num_stages
        self.assertEqual(len(lowerCAmelCase_	)   ,    expected_num_stages + 1	)

     __lowerCAmelCase      ,      __lowerCAmelCase				      =      self.model_tester.prepare_config_and_inputs_for_common()

     for model_class in self.all_model_classes:
        __lowerCAmelCase				      =      True
        check_hidden_states_output(lowerCAmelCase_   ,    lowerCAmelCase_   ,    lowerCAmelCase_	)

        # check that output_hidden_states also work using config
        del inputs_dict["output_hidden_states"]
        __lowerCAmelCase				      =      True

        check_hidden_states_output(lowerCAmelCase_   ,    lowerCAmelCase_   ,    lowerCAmelCase_	)






  def 							lowercase						(							self					:						str	)				->		str:
     __lowerCAmelCase      ,      __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(lowerCAmelCase_   ,    lowerCAmelCase_	)
           __lowerCAmelCase				      =      model_class(lowerCAmelCase_	)

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

           with self.subTest('JIT Enabled'	):
              __lowerCAmelCase				      =      model_jitted(**lowerCAmelCase_	).to_tuple()

           with self.subTest('JIT Disabled'	):
              with jax.disable_jit():
                 __lowerCAmelCase				      =      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	)





def     a_       (					):
   __lowerCAmelCase				      =      Image.open('./tests/fixtures/tests_samples/COCO/000000039769.png'      )
   return image




@require_flax
class 							_UpperCAmelCase       (       unittest.TestCase       ):

  """simple docstring"""


  @cached_property
  def 							lowercase						(							self					:						Union[str, Any]	)				->		Optional[Any]:
     return AutoImageProcessor.from_pretrained('facebook/regnet-y-040'	) if is_vision_available() else None






  @slow
  def 							lowercase						(							self					:						Optional[Any]	)				->		Union[str, Any]:
     __lowerCAmelCase				      =      FlaxRegNetForImageClassification.from_pretrained('facebook/regnet-y-040'	)

     __lowerCAmelCase				      =      self.default_image_processor
     __lowerCAmelCase				      =      prepare_img()
     __lowerCAmelCase				      =      image_processor(images=lowerCAmelCase_   ,    return_tensors='np'	)

     __lowerCAmelCase				      =      model(**lowerCAmelCase_	)

     # verify the logits
     __lowerCAmelCase				      =      (1, 1_0_0_0)
     self.assertEqual(outputs.logits.shape   ,    lowerCAmelCase_	)

     __lowerCAmelCase				      =      jnp.array([-0.41_80, -1.50_51, -3.48_36]	)

     self.assertTrue(jnp.allclose(outputs.logits[0, :3]   ,    lowerCAmelCase_   ,    atol=1e-4	)	)








"""simple docstring"""





import re
def 					__A  (_SCREAMING_SNAKE_CASE     )   ->list:





  """simple docstring"""


  return [char.split() for char in re.split(r'[^ a-z A-Z 0-9 \s]'	,  str_     )]
def 					__A  (_SCREAMING_SNAKE_CASE     )   ->str:





  """simple docstring"""


  lowerCAmelCase__     :Optional[Any]											=				split_input(str_     )
  return "".join(
      [''.join([char.capitalize() for char in sub_str]     ) for sub_str in string_split]     )
def 					__A  (_SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE     )   ->str:





  """simple docstring"""


  try:
    lowerCAmelCase__     :Any											=				split_input(_SCREAMING_SNAKE_CASE     )
    if upper:
      lowerCAmelCase__     :str											=				''.join(
          [
              separator.join([char.upper() for char in sub_str]     )
              for sub_str in string_split
          ]     )
    else:
      lowerCAmelCase__     :int											=				''.join(
          [
              separator.join([char.lower() for char in sub_str]     )
              for sub_str in string_split
          ]     )
    return res_str
  except IndexError:
    return "not valid string"
def 					__A  (_SCREAMING_SNAKE_CASE     )   ->str:





  """simple docstring"""


  return to_simple_case(_SCREAMING_SNAKE_CASE     )
def 					__A  (_SCREAMING_SNAKE_CASE     )   ->str:





  """simple docstring"""


  try:
    lowerCAmelCase__     :str											=				to_simple_case(_SCREAMING_SNAKE_CASE     )
    return res_str[0].lower() + res_str[1:]
  except IndexError:
    return "not valid string"
def 					__A  (_SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE     )   ->str:





  """simple docstring"""


  return to_complex_case(_SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE	,  '_'     )
def 					__A  (_SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE     )   ->str:





  """simple docstring"""


  return to_complex_case(_SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE	,  '-'     )


if __name__ == "__main__":
  __import__("""doctest""").testmod()
