"""simple docstring"""







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 		UpperCamelCase      (   unittest.TestCase						):



				@slow
				def  _lowercase					(self    :				Union[str, Any])   ->     Dict:
					__snake_case      :							Union[str, Any]						=			FlaxXLMRobertaModel.from_pretrained('xlm-roberta-base')
					__snake_case      :							Tuple						=			AutoTokenizer.from_pretrained('xlm-roberta-base')
					__snake_case      :							int						=			'The dog is cute and lives in the garden house'
					__snake_case      :							Dict						=			jnp.array([tokenizer.encode(_A)])

					__snake_case      :							Dict						=			(1, 12, 7_68)  # batch_size, sequence_length, embedding_vector_dim
					__snake_case      :							Tuple						=			jnp.array(
					    [[-0.0_101, 0.1_218, -0.0_803, 0.0_801, 0.1_327, 0.0_776, -0.1_215, 0.2_383, 0.3_338, 0.3_106, 0.0_300, 0.0_252]])

					__snake_case      :							Union[str, Any]						=			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))



"""simple docstring"""







import warnings

from ...utils import logging
from .image_processing_clip import CLIPImageProcessor


_a					:					Dict=			logging.get_logger(__name__)

class 		UpperCamelCase      (   lowercase						):



				def __init__(self    :				List[str]     ,  *_A    :				Dict     ,  **_A    :				Optional[Any])   ->     None:
					warnings.warn(
					    'The class CLIPFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'
					    ' use CLIPImageProcessor instead.'     ,  _A     ,  )
					super().__init__(*_A     ,  **_A)





