

'''simple docstring'''



from __future__ import annotations

import unittest

from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow


if is_tf_available():
   import numpy as np
   import tensorflow as tf

   from transformers import TFCamembertModel

@require_tf
@require_sentencepiece
@require_tokenizers
class       SCREAMING_SNAKE_CASE       (				unittest.TestCase       ):






      '''simple docstring'''






      @slow
      def 						__UpperCAmelCase      (       self			:		Dict ):



          """simple docstring"""





          _snake_case			:			Optional[Any]				       =		TFCamembertModel.from_pretrained('jplu/tf-camembert-base' )

          _snake_case			:			List[Any]				       =		tf.convert_to_tensor(
              [[5, 121, 11, 660, 16, 730, 25543, 110, 83, 6]]  ,       dtype=tf.intaa  ,       )  # J'aime le camembert !"

          _snake_case			:			int				       =		model(_lowercase )['last_hidden_state']
          _snake_case			:			Optional[int]				       =		tf.TensorShape((1, 10, 768) )
          self.assertEqual(output.shape  ,       _lowercase )
          # compare the actual values for a slice.
          _snake_case			:			str				       =		tf.convert_to_tensor(
              [[[-0.0254, 0.0235, 0.1027], [0.0606, -0.1811, -0.0418], [-0.1561, -0.1127, 0.2687]]]  ,       dtype=tf.floataa  ,       )
          # camembert = torch.hub.load('pytorch/fairseq', 'camembert.v0')
          # camembert.eval()
          # expected_slice = roberta.model.forward(input_ids)[0][:, :3, :3].detach()

          self.assertTrue(np.allclose(output[:, :3, :3].numpy()  ,       expected_slice.numpy()  ,       atol=1e-4 ) )





'''simple docstring'''



from ...utils import (
    OptionalDependencyNotAvailable,
    is_torch_available,
    is_transformers_available,
    is_transformers_version,
)


try:
						if not (is_transformers_available() and is_torch_available()):
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						from ...utils.dummy_torch_and_transformers_objects import (
						    ImageTextPipelineOutput,
						    UniDiffuserPipeline,
						)
else:
						from .modeling_text_decoder import UniDiffuserTextDecoder
						from .modeling_uvit import UniDiffuserModel, UTransformeraDModel
						from .pipeline_unidiffuser import ImageTextPipelineOutput, UniDiffuserPipeline
