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119 lines
4.3 KiB
119 lines
4.3 KiB
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# Modified from espnet(https://github.com/espnet/espnet)
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"""This module provides functions to calculate bleu score in different level.
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e.g. wer for word-level, cer for char-level.
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"""
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import numpy as np
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import sacrebleu
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__all__ = ['bleu', 'char_bleu', "ErrorCalculator"]
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def bleu(hypothesis, reference):
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"""Calculate BLEU. BLEU compares reference text and
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hypothesis text in word-level using scarebleu.
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:param reference: The reference sentences.
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:type reference: list[list[str]]
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:param hypothesis: The hypothesis sentence.
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:type hypothesis: list[str]
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:raises ValueError: If the reference length is zero.
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"""
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return sacrebleu.corpus_bleu(hypothesis, reference)
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def char_bleu(hypothesis, reference):
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"""Calculate BLEU. BLEU compares reference text and
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hypothesis text in char-level using scarebleu.
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:param reference: The reference sentences.
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:type reference: list[list[str]]
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:param hypothesis: The hypothesis sentence.
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:type hypothesis: list[str]
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:raises ValueError: If the reference number is zero.
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"""
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hypothesis = [' '.join(list(hyp.replace(' ', ''))) for hyp in hypothesis]
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reference = [[' '.join(list(ref_i.replace(' ', ''))) for ref_i in ref]
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for ref in reference]
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return sacrebleu.corpus_bleu(hypothesis, reference)
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class ErrorCalculator():
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"""Calculate BLEU for ST and MT models during training.
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:param y_hats: numpy array with predicted text
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:param y_pads: numpy array with true (target) text
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:param char_list: vocabulary list
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:param sym_space: space symbol
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:param sym_pad: pad symbol
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:param report_bleu: report BLUE score if True
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"""
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def __init__(self, char_list, sym_space, sym_pad, report_bleu=False):
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"""Construct an ErrorCalculator object."""
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super().__init__()
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self.char_list = char_list
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self.space = sym_space
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self.pad = sym_pad
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self.report_bleu = report_bleu
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if self.space in self.char_list:
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self.idx_space = self.char_list.index(self.space)
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else:
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self.idx_space = None
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def __call__(self, ys_hat, ys_pad):
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"""Calculate corpus-level BLEU score.
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:param torch.Tensor ys_hat: prediction (batch, seqlen)
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:param torch.Tensor ys_pad: reference (batch, seqlen)
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:return: corpus-level BLEU score in a mini-batch
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:rtype float
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"""
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bleu = None
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if not self.report_bleu:
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return bleu
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bleu = self.calculate_corpus_bleu(ys_hat, ys_pad)
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return bleu
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def calculate_corpus_bleu(self, ys_hat, ys_pad):
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"""Calculate corpus-level BLEU score in a mini-batch.
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:param torch.Tensor seqs_hat: prediction (batch, seqlen)
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:param torch.Tensor seqs_true: reference (batch, seqlen)
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:return: corpus-level BLEU score
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:rtype float
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"""
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seqs_hat, seqs_true = [], []
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for i, y_hat in enumerate(ys_hat):
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y_true = ys_pad[i]
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eos_true = np.where(y_true == -1)[0]
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ymax = eos_true[0] if len(eos_true) > 0 else len(y_true)
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# NOTE: padding index (-1) in y_true is used to pad y_hat
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# because y_hats is not padded with -1
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seq_hat = [self.char_list[int(idx)] for idx in y_hat[:ymax]]
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seq_true = [
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self.char_list[int(idx)] for idx in y_true if int(idx) != -1
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]
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seq_hat_text = "".join(seq_hat).replace(self.space, " ")
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seq_hat_text = seq_hat_text.replace(self.pad, "")
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seq_true_text = "".join(seq_true).replace(self.space, " ")
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seqs_hat.append(seq_hat_text)
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seqs_true.append(seq_true_text)
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bleu = sacrebleu.corpus_bleu(seqs_hat, [[ref] for ref in seqs_true])
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return bleu.score * 100
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