


"""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 					__lowerCAmelCase					(   unittest.TestCase       ):


		'''simple docstring'''



		@slow
		def 			__UpperCAmelCase       (  self      ):
				__a           =			FlaxXLMRobertaModel.from_pretrained('''xlm-roberta-base'''      )
				__a           =			AutoTokenizer.from_pretrained('''xlm-roberta-base'''      )
				__a           =			'''The dog is cute and lives in the garden house'''
				__a           =			jnp.array([tokenizer.encode(_a      )]      )

				__a           =			(1, 12, 768)  # batch_size, sequence_length, embedding_vector_dim
				__a           =			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]]      )

				__a           =			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 numpy as np

def        lowercase							(		lowerCAmelCase__ :     np.ndarray    ,					lowerCAmelCase__ :     float			) ->      np.ndarray:
		return np.where(vector > 0    ,					lowerCAmelCase__    ,					(alpha * (np.exp(lowerCAmelCase__			) - 1))			)


if __name__ == "__main__":
				import doctest

				doctest.testmod()






