





from typing import TYPE_CHECKING

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


__A				:    Optional[int]       =   {
    'configuration_rag': ['RagConfig'],
    'retrieval_rag': ['RagRetriever'],
    'tokenization_rag': ['RagTokenizer'],
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__A				:    str       =   [
				    'RagModel',
				    'RagPreTrainedModel',
				    'RagSequenceForGeneration',
				    'RagTokenForGeneration',
				]

try:
				if not is_tf_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__A				:    List[str]       =   [
				    'TFRagModel',
				    'TFRagPreTrainedModel',
				    'TFRagSequenceForGeneration',
				    'TFRagTokenForGeneration',
				]


if TYPE_CHECKING:
				from .configuration_rag import RagConfig
				from .retrieval_rag import RagRetriever
				from .tokenization_rag import RagTokenizer

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_rag import RagModel, RagPreTrainedModel, RagSequenceForGeneration, RagTokenForGeneration

				try:
								if not is_tf_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_tf_rag import (
								    TFRagModel,
								    TFRagPreTrainedModel,
								    TFRagSequenceForGeneration,
								    TFRagTokenForGeneration,
								)

else:
				import sys

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






'''simple docstring'''



import unittest

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

from .test_modeling_common_flax import FlaxModelTesterMixin


if is_flax_available():
  import jax







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



 """simple docstring"""



 lowerCAmelCase__  					=      FlaxAutoencoderKL
 @property
 def       UpperCAmelCase__		(		self					:       Tuple			)  -> List[str]:


      """simple docstring"""




      __SCREAMING_SNAKE_CASE     =      4
      __SCREAMING_SNAKE_CASE     =      3
      __SCREAMING_SNAKE_CASE     =      (32, 32)

      __SCREAMING_SNAKE_CASE     =      jax.random.PRNGKey(0			)
      __SCREAMING_SNAKE_CASE     =      jax.random.uniform(__SCREAMING_SNAKE_CASE					,							((batch_size, num_channels) + sizes)			)

      return {"sample": image, "prng_key": prng_key}


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


      """simple docstring"""




      __SCREAMING_SNAKE_CASE     =      {
          """block_out_channels""": [32, 64],
          """in_channels""": 3,
          """out_channels""": 3,
          """down_block_types""": ["""DownEncoderBlock2D""", """DownEncoderBlock2D"""],
          """up_block_types""": ["""UpDecoderBlock2D""", """UpDecoderBlock2D"""],
          """latent_channels""": 4,
      }
      __SCREAMING_SNAKE_CASE     =      self.dummy_input
      return init_dict, inputs_dict






