



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 TFXLMRobertaModel

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



       @slow
       def 		_lowerCamelCase			(		self							:     Any):


           '''simple docstring'''

           __a						       =				TFXLMRobertaModel.from_pretrained('''jplu/tf-xlm-roberta-base''')

           __a						       =				{
               '''input_ids''': tf.convert_to_tensor([[0, 2_646, 10_269, 83, 99_942, 2]]     ,		dtype=tf.intaa),  # "My dog is cute"
               '''attention_mask''': tf.convert_to_tensor([[1, 1, 1, 1, 1, 1]]     ,		dtype=tf.intaa),
           }

           __a						       =				model(__lowerCAmelCase)['''last_hidden_state''']
           __a						       =				tf.TensorShape((1, 6, 768))
           self.assertEqual(output.shape     ,		__lowerCAmelCase)
           # compare the actual values for a slice.
           __a						       =				tf.convert_to_tensor(
               [
                   [
                       [0.0_68_17_62, 0.10_89_44_51, 0.06_77_25_04],
                       [-0.06_42_36_68, 0.02_36_66_15, 0.04_32_93_44],
                       [-0.06_05_72_95, 0.09_97_41_35, -0.00_07_05_84],
                   ]
               ]     ,		dtype=tf.floataa     ,		)

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






'''simple docstring'''

import requests

__a: str          =   """https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey="""
def 			__UpperCamelCase       (   UpperCAmelCase     ):
 # fetching a list of articles in json format
 lowercase__				:    Optional[Any]  =					requests.get(_NEWS_API + bbc_news_api_key     ).json()
 # each article in the list is a dict
 for i, article in enumerate(bbc_news_page['''articles''']		,     1     ):
  print(F"""{i}.) {article['title']}"""     )


if __name__ == "__main__":
  fetch_bbc_news(bbc_news_api_key="""<Your BBC News API key goes here>""")

