






'''simple docstring'''

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 						A__		(   self   )						->   Dict:



        """simple docstring"""






        UpperCamelCase       						=      TFXLMRobertaModel.from_pretrained("""jplu/tf-xlm-roberta-base"""   )

        UpperCamelCase       						=      {
            """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   ),
        }

        UpperCamelCase       						=      model(_SCREAMING_SNAKE_CASE   )["""last_hidden_state"""]
        UpperCamelCase       						=      tf.TensorShape((1, 6, 768)   )
        self.assertEqual(output.shape    ,	_SCREAMING_SNAKE_CASE   )
        # compare the actual values for a slice.
        UpperCamelCase       						=      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   )   )








'''simple docstring'''

import fire

from utils import calculate_rouge, save_json







def 					lowercase__				(   __UpperCamelCase	,		__UpperCamelCase	,		__UpperCamelCase=None	,		**__UpperCamelCase					)->				int:
      UpperCamelCase       						=      [x.strip() for x in open(__UpperCamelCase					).readlines()]
      UpperCamelCase       						=      [x.strip() for x in open(__UpperCamelCase					).readlines()][: len(__UpperCamelCase					)]
      UpperCamelCase       						=      calculate_rouge(__UpperCamelCase	,		__UpperCamelCase	,		**__UpperCamelCase					)
      if save_path is not None:
            save_json(__UpperCamelCase	,		__UpperCamelCase	,		indent=__UpperCamelCase					)
      return metrics  # these print nicely


if __name__ == "__main__":
     fire.Fire(calculate_rouge_path)
