




'''simple docstring'''



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 		lowercase_   (			unittest.TestCase       ):


   """simple docstring"""

   def __init__(   self :     Optional[int]  ,				__lowerCamelCase :     Tuple  ,				__lowerCamelCase :     List[str]=3  ,				__lowerCamelCase :     int=3_2  ,				__lowerCamelCase :     int=3  ,				__lowerCamelCase :     int=1_0  ,				__lowerCamelCase :     Union[str, Any]=[1_0, 2_0, 3_0, 4_0]  ,				__lowerCamelCase :     Optional[int]=[1, 1, 2, 1]  ,				__lowerCamelCase :     List[Any]=True  ,				__lowerCamelCase :     Dict=True  ,				__lowerCamelCase :     int="relu"  ,				__lowerCamelCase :     Optional[Any]=3  ,				__lowerCamelCase :     List[Any]=None  ,				):

      """simple docstring"""
      _SCREAMING_SNAKE_CASE	=				parent
      _SCREAMING_SNAKE_CASE	=				batch_size
      _SCREAMING_SNAKE_CASE	=				image_size
      _SCREAMING_SNAKE_CASE	=				num_channels
      _SCREAMING_SNAKE_CASE	=				embeddings_size
      _SCREAMING_SNAKE_CASE	=				hidden_sizes
      _SCREAMING_SNAKE_CASE	=				depths
      _SCREAMING_SNAKE_CASE	=				is_training
      _SCREAMING_SNAKE_CASE	=				use_labels
      _SCREAMING_SNAKE_CASE	=				hidden_act
      _SCREAMING_SNAKE_CASE	=				num_labels
      _SCREAMING_SNAKE_CASE	=				scope
      _SCREAMING_SNAKE_CASE	=				len(__lowerCamelCase   )



   def 							lowerCAmelCase_      (   self :     Optional[Any]   ):

      """simple docstring"""
      _SCREAMING_SNAKE_CASE	=				floats_tensor([self.batch_size, self.num_channels, self.image_size, self.image_size]   )

      _SCREAMING_SNAKE_CASE	=				self.get_config()

      return config, pixel_values



   def 							lowerCAmelCase_      (   self :     Tuple   ):

      """simple docstring"""
      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 							lowerCAmelCase_      (   self :     Tuple  ,				__lowerCamelCase :     List[str]  ,				__lowerCamelCase :     Dict   ):

      """simple docstring"""
      _SCREAMING_SNAKE_CASE	=				FlaxRegNetModel(config=__lowerCamelCase   )
      _SCREAMING_SNAKE_CASE	=				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 							lowerCAmelCase_      (   self :     Any  ,				__lowerCamelCase :     Tuple  ,				__lowerCamelCase :     str   ):

      """simple docstring"""
      _SCREAMING_SNAKE_CASE	=				self.num_labels
      _SCREAMING_SNAKE_CASE	=				FlaxRegNetForImageClassification(config=__lowerCamelCase   )
      _SCREAMING_SNAKE_CASE	=				model(__lowerCamelCase   )
      self.parent.assertEqual(result.logits.shape  ,				(self.batch_size, self.num_labels)   )



   def 							lowerCAmelCase_      (   self :     Tuple   ):

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







@require_flax
class 		lowercase_   (			__UpperCamelCase					,  unittest.TestCase       ):


   """simple docstring"""

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

   lowerCamelCase_      =						False
   lowerCamelCase_      =						False
   lowerCamelCase_      =						False



   def 							lowerCAmelCase_      (   self :     Any   ):

      """simple docstring"""
      _SCREAMING_SNAKE_CASE	=				FlaxRegNetModelTester(self   )
      _SCREAMING_SNAKE_CASE	=				ConfigTester(self  ,				config_class=__lowerCamelCase  ,				has_text_modality=__lowerCamelCase   )



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

      """simple docstring"""
      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 							lowerCAmelCase_      (   self :     Optional[Any]   ):

      """simple docstring"""
      return



   def 							lowerCAmelCase_      (   self :     Any   ):

      """simple docstring"""
      _SCREAMING_SNAKE_CASE	=				self.model_tester.prepare_config_and_inputs()
      self.model_tester.create_and_check_model(*__lowerCamelCase   )



   def 							lowerCAmelCase_      (   self :     Optional[int]   ):

      """simple docstring"""
      _SCREAMING_SNAKE_CASE	=				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 							lowerCAmelCase_      (   self :     Any   ):

      """simple docstring"""
      pass



   @unittest.skip(reason="RegNet does not support input and output embeddings"   )
   def 							lowerCAmelCase_      (   self :     Any   ):

      """simple docstring"""
      pass



   def 							lowerCAmelCase_      (   self :     Tuple   ):

      """simple docstring"""
      _SCREAMING_SNAKE_CASE	=				self.model_tester.prepare_config_and_inputs_for_common()

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

         _SCREAMING_SNAKE_CASE	=				["""pixel_values"""]
         self.assertListEqual(arg_names[:1]  ,				__lowerCamelCase   )



   def 							lowerCAmelCase_      (   self :     Optional[int]   ):

      """simple docstring"""
      def check_hidden_states_output(__lowerCamelCase :     Union[str, Any]  ,				__lowerCamelCase :     Dict  ,				__lowerCamelCase :     Tuple   ):
         _SCREAMING_SNAKE_CASE	=				model_class(__lowerCamelCase   )

         _SCREAMING_SNAKE_CASE	=				model(**self._prepare_for_class(__lowerCamelCase  ,				__lowerCamelCase   )   )

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

         _SCREAMING_SNAKE_CASE	=				self.model_tester.num_stages
         self.assertEqual(len(__lowerCamelCase   )  ,				expected_num_stages + 1   )

      _SCREAMING_SNAKE_CASE	=				self.model_tester.prepare_config_and_inputs_for_common()

      for model_class in self.all_model_classes:
         _SCREAMING_SNAKE_CASE	=				True
         check_hidden_states_output(__lowerCamelCase  ,				__lowerCamelCase  ,				__lowerCamelCase   )

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

         check_hidden_states_output(__lowerCamelCase  ,				__lowerCamelCase  ,				__lowerCamelCase   )



   def 							lowerCAmelCase_      (   self :     Dict   ):

      """simple docstring"""
      _SCREAMING_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__   ):
            _SCREAMING_SNAKE_CASE	=				self._prepare_for_class(__lowerCamelCase  ,				__lowerCamelCase   )
            _SCREAMING_SNAKE_CASE	=				model_class(__lowerCamelCase   )

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

            with self.subTest("JIT Enabled"   ):
               _SCREAMING_SNAKE_CASE	=				model_jitted(**__lowerCamelCase   ).to_tuple()

            with self.subTest("JIT Disabled"   ):
               with jax.disable_jit():
                  _SCREAMING_SNAKE_CASE	=				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 			SCREAMING_SNAKE_CASE_			(							)			->			Any:
   _SCREAMING_SNAKE_CASE	=				Image.open("./tests/fixtures/tests_samples/COCO/000000039769.png"  )
   return image







@require_flax
class 		lowercase_   (			unittest.TestCase       ):


   """simple docstring"""

   @cached_property
   def 							lowerCAmelCase_      (   self :     str   ):

      """simple docstring"""
      return AutoImageProcessor.from_pretrained("facebook/regnet-y-040"   ) if is_vision_available() else None



   @slow
   def 							lowerCAmelCase_      (   self :     str   ):

      """simple docstring"""
      _SCREAMING_SNAKE_CASE	=				FlaxRegNetForImageClassification.from_pretrained("facebook/regnet-y-040"   )

      _SCREAMING_SNAKE_CASE	=				self.default_image_processor
      _SCREAMING_SNAKE_CASE	=				prepare_img()
      _SCREAMING_SNAKE_CASE	=				image_processor(images=__lowerCamelCase  ,				return_tensors="np"   )

      _SCREAMING_SNAKE_CASE	=				model(**__lowerCamelCase   )

      # verify the logits
      _SCREAMING_SNAKE_CASE	=				(1, 1_0_0_0)
      self.assertEqual(outputs.logits.shape  ,				__lowerCamelCase   )

      _SCREAMING_SNAKE_CASE	=				jnp.array([-0.4_1_8_0, -1.5_0_5_1, -3.4_8_3_6]   )

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







'''simple docstring'''



# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run

import sys
import warnings
from os.path import abspath, dirname, join


# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' when switching between checkouts and running tests.
lowerCamelCase_			=						abspath(join(dirname(dirname(__file__)), 'src'))
sys.path.insert(1, git_repo_path)

# silence FutureWarning warnings in tests since often we can't act on them until
# they become normal warnings - i.e. the tests still need to test the current functionality
warnings.simplefilter(action='ignore', category=FutureWarning)
def 			SCREAMING_SNAKE_CASE_			(							__A    :			Dict  )			->			Dict:
   from diffusers.utils.testing_utils import pytest_addoption_shared

   pytest_addoption_shared(__A  )






def 			SCREAMING_SNAKE_CASE_			(							__A    :			List[Any]  )			->			str:
   from diffusers.utils.testing_utils import pytest_terminal_summary_main

   _SCREAMING_SNAKE_CASE	=				terminalreporter.config.getoption("--make-reports"  )
   if make_reports:
      pytest_terminal_summary_main(__A	,					id=__A  )

