





import inspect

from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax


if is_flax_available():
  import jax

@require_flax
class 						__a							:



       def        A							(   self		:      Tuple	):
           lowerCAmelCase_						,						lowerCAmelCase_    :		Any 						=      self.prepare_init_args_and_inputs_for_common()

           lowerCAmelCase_    :		int 						=      self.model_class(**_lowercase	)
           lowerCAmelCase_    :		Optional[int] 						=      model.init(inputs_dict["""prng_key"""]    ,	inputs_dict["""sample"""]	)
           jax.lax.stop_gradient(_lowercase	)

           lowerCAmelCase_    :		Dict 						=      model.apply(_lowercase    ,	inputs_dict["""sample"""]	)

           if isinstance(_lowercase    ,	_lowercase	):
               lowerCAmelCase_    :		List[str] 						=      output.sample

           self.assertIsNotNone(_lowercase	)
           lowerCAmelCase_    :		Tuple 						=      inputs_dict["""sample"""].shape
           self.assertEqual(output.shape    ,	_lowercase    ,	"""Input and output shapes do not match"""	)



       def        A							(   self		:      Optional[int]	):
           lowerCAmelCase_						,						lowerCAmelCase_    :		Optional[int] 						=      self.prepare_init_args_and_inputs_for_common()

           lowerCAmelCase_    :		Tuple 						=      16
           lowerCAmelCase_    :		int 						=      (16, 32)

           lowerCAmelCase_    :		List[str] 						=      self.model_class(**_lowercase	)
           lowerCAmelCase_    :		List[Any] 						=      model.init(inputs_dict["""prng_key"""]    ,	inputs_dict["""sample"""]	)
           jax.lax.stop_gradient(_lowercase	)

           lowerCAmelCase_    :		List[Any] 						=      model.apply(_lowercase    ,	inputs_dict["""sample"""]	)

           if isinstance(_lowercase    ,	_lowercase	):
               lowerCAmelCase_    :		Optional[Any] 						=      output.sample

           self.assertIsNotNone(_lowercase	)
           lowerCAmelCase_    :		Union[str, Any] 						=      inputs_dict["""sample"""].shape
           self.assertEqual(output.shape    ,	_lowercase    ,	"""Input and output shapes do not match"""	)



       def        A							(   self		:      int	):
           lowerCAmelCase_    :		List[str] 						=      """kwargs""" in inspect.signature(self.model_class.__init__	).parameters
           lowerCAmelCase_    :		Tuple 						=      len(self.model_class._deprecated_kwargs	) > 0

           if has_kwarg_in_model_class and not has_deprecated_kwarg:
               raise ValueError(
                   F'{self.model_class} has `**kwargs` in its __init__ method but has not defined any deprecated kwargs'
                   """ under the `_deprecated_kwargs` class attribute. Make sure to either remove `**kwargs` if there are"""
                   """ no deprecated arguments or add the deprecated argument with `_deprecated_kwargs ="""
                   """ [<deprecated_argument>]`"""	)

           if not has_kwarg_in_model_class and has_deprecated_kwarg:
               raise ValueError(
                   F'{self.model_class} doesn\'t have `**kwargs` in its __init__ method but has defined deprecated kwargs'
                   """ under the `_deprecated_kwargs` class attribute. Make sure to either add the `**kwargs` argument to"""
                   F' {self.model_class}.__init__ if there are deprecated arguments or remove the deprecated argument'
                   """ from `_deprecated_kwargs = [<deprecated_argument>]`"""	)









from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_snake_case				= {"""configuration_dinat""": ["""DINAT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """DinatConfig"""]}


try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _snake_case				= [
      """DINAT_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """DinatForImageClassification""",
      """DinatModel""",
      """DinatPreTrainedModel""",
      """DinatBackbone""",
  ]

if TYPE_CHECKING:
  from .configuration_dinat import DINAT_PRETRAINED_CONFIG_ARCHIVE_MAP, DinatConfig

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_dinat import (
        DINAT_PRETRAINED_MODEL_ARCHIVE_LIST,
        DinatBackbone,
        DinatForImageClassification,
        DinatModel,
        DinatPreTrainedModel,
    )

else:
  import sys

  _snake_case				= _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)






