import unittest

from transformers import AutoTokenizer, is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, slow


if is_flax_available():
						import jax.numpy as jnp

						from transformers import FlaxXLMRobertaModel

@require_sentencepiece
@require_tokenizers
@require_flax
class       snake_case					(      unittest.TestCase						):




		@slow
		def 	__lowercase(      self     :	Dict				)->       Dict:




							"""simple docstring"""
							SCREAMING_SNAKE_CASE__				:				Optional[int]			=		FlaxXLMRobertaModel.from_pretrained('xlm-roberta-base'				)
							SCREAMING_SNAKE_CASE__				:				Optional[int]			=		AutoTokenizer.from_pretrained('xlm-roberta-base'				)
							SCREAMING_SNAKE_CASE__				:				Dict			=		'''The dog is cute and lives in the garden house'''
							SCREAMING_SNAKE_CASE__				:				List[str]			=		jnp.array([tokenizer.encode(a_				)]				)

							SCREAMING_SNAKE_CASE__				:				int			=		(1, 12, 768)  # batch_size, sequence_length, embedding_vector_dim
							SCREAMING_SNAKE_CASE__				:				Dict			=		jnp.array(
							    [[-0.0101, 0.1218, -0.0803, 0.0801, 0.1327, 0.0776, -0.1215, 0.2383, 0.3338, 0.3106, 0.0300, 0.0252]]				)

							SCREAMING_SNAKE_CASE__				:				str			=		model(a_				)['''last_hidden_state''']
							self.assertEqual(output.shape     , a_				)
							# compare the actual values for a slice of last dim
							self.assertTrue(jnp.allclose(output[:, :, -1]     , a_     , atol=1e-3				)				)




from packaging import version

from .import_utils import is_accelerate_available


if is_accelerate_available():
      import accelerate







def     _a				(      lowercase__  :			List[str] ):







     '''simple docstring'''


     if not is_accelerate_available():
          return method
     SCREAMING_SNAKE_CASE__				:				str			=		version.parse(accelerate.__version__ ).base_version
     if version.parse(lowercase__ ) < version.parse('0.17.0' ):
          return method

     def wrapper(self  :			Optional[int]     ,  *lowercase__  :			int     ,  **lowercase__  :			Tuple ):
          if hasattr(self     ,  '_hf_hook' ) and hasattr(self._hf_hook     ,  'pre_forward' ):
               self._hf_hook.pre_forward(self )
          return method(self     ,  *lowercase__     ,  **lowercase__ )

     return wrapper



