
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     _SCREAMING_SNAKE_CASE     (      unittest.TestCase						):



	@slow
	def     SCREAMING_SNAKE_CASE_(    self )				->       Dict:
					lowerCamelCase_						=			TFXLMRobertaModel.from_pretrained("jplu/tf-xlm-roberta-base" )

					lowerCamelCase_						=			{
					    "input_ids": tf.convert_to_tensor([[0, 2646, 10269, 83, 99942, 2]]						,  dtype=tf.intaa ),  # "My dog is cute"
					    "attention_mask": tf.convert_to_tensor([[1, 1, 1, 1, 1, 1]]						,  dtype=tf.intaa ),
					}

					lowerCamelCase_						=			model(lowercase )["last_hidden_state"]
					lowerCamelCase_						=			tf.TensorShape((1, 6, 768) )
					self.assertEqual(output.shape						,  lowercase )
					# compare the actual values for a slice.
					lowerCamelCase_						=			tf.convert_to_tensor(
					    [
					        [
					            [0.0_6_8_1_7_6_2, 0.1_0_8_9_4_4_5_1, 0.0_6_7_7_2_5_0_4],
					            [-0.0_6_4_2_3_6_6_8, 0.0_2_3_6_6_6_1_5, 0.0_4_3_2_9_3_4_4],
					            [-0.0_6_0_5_7_2_9_5, 0.0_9_9_7_4_1_3_5, -0.0_0_0_7_0_5_8_4],
					        ]
					    ]						,  dtype=tf.floataa						,  )

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




import requests

_A   =     "https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey="






def    lowerCamelCase__				(				__lowerCAmelCase  :  str				):




			"""simple docstring"""


			lowerCAmelCase_						=	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>")



