"""simple docstring"""


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        lowerCAmelCase_				(		self   :    Any     )      -> List[Any]:
      __a      ,  __a			      =						self.prepare_init_args_and_inputs_for_common()

      __a			      =						self.model_class(**lowerCamelCase_     )
      __a			      =						model.init(inputs_dict["""prng_key"""]						,  inputs_dict["""sample"""]     )
      jax.lax.stop_gradient(lowerCamelCase_     )

      __a			      =						model.apply(lowerCamelCase_						,  inputs_dict["""sample"""]     )

      if isinstance(lowerCamelCase_						,  lowerCamelCase_     ):
          __a			      =						output.sample

      self.assertIsNotNone(lowerCamelCase_     )
      __a			      =						inputs_dict["""sample"""].shape
      self.assertEqual(output.shape						,  lowerCamelCase_						,  """Input and output shapes do not match"""     )



  def        lowerCAmelCase_				(		self   :    Union[str, Any]     )      -> Union[str, Any]:
      __a      ,  __a			      =						self.prepare_init_args_and_inputs_for_common()

      __a			      =						16
      __a			      =						(16, 32)

      __a			      =						self.model_class(**lowerCamelCase_     )
      __a			      =						model.init(inputs_dict["""prng_key"""]						,  inputs_dict["""sample"""]     )
      jax.lax.stop_gradient(lowerCamelCase_     )

      __a			      =						model.apply(lowerCamelCase_						,  inputs_dict["""sample"""]     )

      if isinstance(lowerCamelCase_						,  lowerCamelCase_     ):
          __a			      =						output.sample

      self.assertIsNotNone(lowerCamelCase_     )
      __a			      =						inputs_dict["""sample"""].shape
      self.assertEqual(output.shape						,  lowerCamelCase_						,  """Input and output shapes do not match"""     )



  def        lowerCAmelCase_				(		self   :    Optional[Any]     )      -> Optional[int]:
      __a			      =						"""kwargs""" in inspect.signature(self.model_class.__init__     ).parameters
      __a			      =						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>]`"""     )

"""simple docstring"""


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


__A       			=      {
    """configuration_realm""": ["""REALM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """RealmConfig"""],
    """tokenization_realm""": ["""RealmTokenizer"""],
}

try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __A       			=      ["""RealmTokenizerFast"""]

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __A       			=      [
     """REALM_PRETRAINED_MODEL_ARCHIVE_LIST""",
     """RealmEmbedder""",
     """RealmForOpenQA""",
     """RealmKnowledgeAugEncoder""",
     """RealmPreTrainedModel""",
     """RealmReader""",
     """RealmScorer""",
     """load_tf_weights_in_realm""",
 ]
 __A       			=      ["""RealmRetriever"""]


if TYPE_CHECKING:
 from .configuration_realm import REALM_PRETRAINED_CONFIG_ARCHIVE_MAP, RealmConfig
 from .tokenization_realm import RealmTokenizer

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_realm import RealmTokenizerFast

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_realm import (
      REALM_PRETRAINED_MODEL_ARCHIVE_LIST,
      RealmEmbedder,
      RealmForOpenQA,
      RealmKnowledgeAugEncoder,
      RealmPreTrainedModel,
      RealmReader,
      RealmScorer,
      load_tf_weights_in_realm,
  )
  from .retrieval_realm import RealmRetriever


else:
 import sys

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