mindspore.train.BleuScore

class mindspore.train.BleuScore(n_gram=4, smooth=False)

Calculates the BLEU score. BLEU (bilingual evaluation understudy) is a metric for evaluating the quality of text translated by machine.

Parameters

• n_gram (int) – The n_gram value ranges from 1 to 4. Default: 4.

• smooth (bool) – Whether or not to apply smoothing. Default: False.

Raises

ValueError – If the value range of n_gram is not from 1 to 4.

Supported Platforms:

Ascend GPU CPU

Examples

>>> from mindspore.train import BleuScore
>>>
>>> candidate_corpus = [['i', 'have', 'a', 'pen', 'on', 'my', 'desk']]
>>> reference_corpus = [[['i', 'have', 'a', 'pen', 'in', 'my', 'desk'],
...                      ['there', 'is', 'a', 'pen', 'on', 'the', 'desk']]]
>>> metric = BleuScore()
>>> metric.clear()
>>> metric.update(candidate_corpus, reference_corpus)
>>> bleu_score = metric.eval()
>>> print(bleu_score)
0.5946035575013605

clear()

Clear the internal evaluation result.

eval()

Computes the bleu score.

Returns

numpy.float64, the bleu score.

Raises

RuntimeError – If the update method is not called first, an error will be reported.

update(*inputs)

Updates the internal evaluation result with candidate_corpus and reference_corpus.

Parameters

inputs (iterator) – Input candidate_corpus and reference_corpus. candidate_corpus and reference_corpus are both a list. The candidate_corpus is an iterable of machine translated corpus. The reference_corpus is an iterable object of iterables of reference corpus.

Raises

• ValueError – If the number of inputs is not 2.

• ValueError – If the lengths of candidate_corpus and reference_corpus are not equal.