


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 _lowerCamelCase(		unittest.TestCase     ):
       @slow
       def     UpperCamelCase  (      self) ->     Tuple:




           """simple docstring"""

           _lowercase :							Tuple   	=	TFXLMRobertaModel.from_pretrained('jplu/tf-xlm-roberta-base')

           _lowercase :							Union[str, Any]   	=	{
               'input_ids': tf.convert_to_tensor([[0, 26_46, 1_02_69, 83, 9_99_42, 2]],   dtype=tf.intaa),  # "My dog is cute"
               'attention_mask': tf.convert_to_tensor([[1, 1, 1, 1, 1, 1]],   dtype=tf.intaa),
           }

           _lowercase :							Dict   	=	model(lowerCamelCase)['last_hidden_state']
           _lowercase :							int   	=	tf.TensorShape((1, 6, 7_68))
           self.assertEqual(output.shape,   lowerCamelCase)
           # compare the actual values for a slice.
           _lowercase :							Union[str, Any]   	=	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))






from __future__ import annotations

import requests



def        UpperCamelCase_(   lowerCamelCase_				)					->		dict:
    _lowercase :							Dict   	=	F'''https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty'''
    return requests.get(lowerCamelCase_				).json()



def        UpperCamelCase_(   lowerCamelCase_ = 10				)					->		list[dict]:
    _lowercase :							Dict   	=	'https://hacker-news.firebaseio.com/v0/topstories.json?print=pretty'
    _lowercase :							Dict   	=	requests.get(lowerCamelCase_				).json()[:max_stories]
    return [get_hackernews_story(lowerCamelCase_				) for story_id in story_ids]



def        UpperCamelCase_(   lowerCamelCase_ = 10				)					->		str:
    _lowercase :							Optional[int]   	=	hackernews_top_stories(lowerCamelCase_				)
    return "\n".join('* [{title}]({url})'.format(**lowerCamelCase_				) for story in stories				)


if __name__ == "__main__":
 print(hackernews_top_stories_as_markdown())


