當前位置: 首頁>>代碼示例>>Python>>正文

Python sequence_generator.SequenceGenerator方法代碼示例

本文整理匯總了Python中fairseq.sequence_generator.SequenceGenerator方法的典型用法代碼示例。如果您正苦於以下問題：Python sequence_generator.SequenceGenerator方法的具體用法？Python sequence_generator.SequenceGenerator怎麽用？Python sequence_generator.SequenceGenerator使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類fairseq.sequence_generator的用法示例。


在下文中一共展示了sequence_generator.SequenceGenerator方法的15個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。

示例1: test_with_normalization

# 需要導入模塊: from fairseq import sequence_generator [as 別名]
# 或者: from fairseq.sequence_generator import SequenceGenerator [as 別名]
def test_with_normalization(self):
        generator = SequenceGenerator([self.model], self.tgt_dict)
        hypos = generator.generate(self.src_tokens, self.src_lengths, beam_size=2)
        eos, w1, w2 = self.eos, self.w1, self.w2
        # sentence 1, beam 1
        self.assertHypoTokens(hypos[0][0], [w1, eos])
        self.assertHypoScore(hypos[0][0], [0.9, 1.0])
        # sentence 1, beam 2
        self.assertHypoTokens(hypos[0][1], [w2, w1, w2, eos])
        self.assertHypoScore(hypos[0][1], [0.1, 0.9, 0.9, 1.0])
        # sentence 2, beam 1
        self.assertHypoTokens(hypos[1][0], [w1, w2, w1, eos])
        self.assertHypoScore(hypos[1][0], [0.7, 0.4, 0.4, 1.0])
        # sentence 2, beam 2
        self.assertHypoTokens(hypos[1][1], [w1, w2, eos])
        self.assertHypoScore(hypos[1][1], [0.7, 0.4, 0.6])
開發者ID:nusnlp，項目名稱:crosentgec，代碼行數:18，代碼來源:test_sequence_generator.py

示例2: test_without_normalization

# 需要導入模塊: from fairseq import sequence_generator [as 別名]
# 或者: from fairseq.sequence_generator import SequenceGenerator [as 別名]
def test_without_normalization(self):
        # Sentence 1: unchanged from the normalized case
        # Sentence 2: beams swap order
        generator = SequenceGenerator([self.model], self.tgt_dict, normalize_scores=False)
        hypos = generator.generate(self.src_tokens, self.src_lengths, beam_size=2)
        eos, w1, w2 = self.eos, self.w1, self.w2
        # sentence 1, beam 1
        self.assertHypoTokens(hypos[0][0], [w1, eos])
        self.assertHypoScore(hypos[0][0], [0.9, 1.0], normalized=False)
        # sentence 1, beam 2
        self.assertHypoTokens(hypos[0][1], [w2, w1, w2, eos])
        self.assertHypoScore(hypos[0][1], [0.1, 0.9, 0.9, 1.0], normalized=False)
        # sentence 2, beam 1
        self.assertHypoTokens(hypos[1][0], [w1, w2, eos])
        self.assertHypoScore(hypos[1][0], [0.7, 0.4, 0.6], normalized=False)
        # sentence 2, beam 2
        self.assertHypoTokens(hypos[1][1], [w1, w2, w1, eos])
        self.assertHypoScore(hypos[1][1], [0.7, 0.4, 0.4, 1.0], normalized=False)
開發者ID:nusnlp，項目名稱:crosentgec，代碼行數:20，代碼來源:test_sequence_generator.py

示例3: test_with_lenpen_favoring_short_hypos

# 需要導入模塊: from fairseq import sequence_generator [as 別名]
# 或者: from fairseq.sequence_generator import SequenceGenerator [as 別名]
def test_with_lenpen_favoring_short_hypos(self):
        lenpen = 0.6
        generator = SequenceGenerator([self.model], self.tgt_dict, len_penalty=lenpen)
        hypos = generator.generate(self.src_tokens, self.src_lengths, beam_size=2)
        eos, w1, w2 = self.eos, self.w1, self.w2
        # sentence 1, beam 1
        self.assertHypoTokens(hypos[0][0], [w1, eos])
        self.assertHypoScore(hypos[0][0], [0.9, 1.0], lenpen=lenpen)
        # sentence 1, beam 2
        self.assertHypoTokens(hypos[0][1], [w2, w1, w2, eos])
        self.assertHypoScore(hypos[0][1], [0.1, 0.9, 0.9, 1.0], lenpen=lenpen)
        # sentence 2, beam 1
        self.assertHypoTokens(hypos[1][0], [w1, w2, eos])
        self.assertHypoScore(hypos[1][0], [0.7, 0.4, 0.6], lenpen=lenpen)
        # sentence 2, beam 2
        self.assertHypoTokens(hypos[1][1], [w1, w2, w1, eos])
        self.assertHypoScore(hypos[1][1], [0.7, 0.4, 0.4, 1.0], lenpen=lenpen)
開發者ID:nusnlp，項目名稱:crosentgec，代碼行數:19，代碼來源:test_sequence_generator.py

示例4: test_with_lenpen_favoring_long_hypos

# 需要導入模塊: from fairseq import sequence_generator [as 別名]
# 或者: from fairseq.sequence_generator import SequenceGenerator [as 別名]
def test_with_lenpen_favoring_long_hypos(self):
        lenpen = 5.0
        generator = SequenceGenerator([self.model], self.tgt_dict, len_penalty=lenpen)
        hypos = generator.generate(self.src_tokens, self.src_lengths, beam_size=2)
        eos, w1, w2 = self.eos, self.w1, self.w2
        # sentence 1, beam 1
        self.assertHypoTokens(hypos[0][0], [w2, w1, w2, eos])
        self.assertHypoScore(hypos[0][0], [0.1, 0.9, 0.9, 1.0], lenpen=lenpen)
        # sentence 1, beam 2
        self.assertHypoTokens(hypos[0][1], [w1, eos])
        self.assertHypoScore(hypos[0][1], [0.9, 1.0], lenpen=lenpen)
        # sentence 2, beam 1
        self.assertHypoTokens(hypos[1][0], [w1, w2, w1, eos])
        self.assertHypoScore(hypos[1][0], [0.7, 0.4, 0.4, 1.0], lenpen=lenpen)
        # sentence 2, beam 2
        self.assertHypoTokens(hypos[1][1], [w1, w2, eos])
        self.assertHypoScore(hypos[1][1], [0.7, 0.4, 0.6], lenpen=lenpen)
開發者ID:nusnlp，項目名稱:crosentgec，代碼行數:19，代碼來源:test_sequence_generator.py

示例5: test_maxlen

# 需要導入模塊: from fairseq import sequence_generator [as 別名]
# 或者: from fairseq.sequence_generator import SequenceGenerator [as 別名]
def test_maxlen(self):
        generator = SequenceGenerator([self.model], self.tgt_dict, maxlen=2)
        hypos = generator.generate(self.src_tokens, self.src_lengths, beam_size=2)
        eos, w1, w2 = self.eos, self.w1, self.w2
        # sentence 1, beam 1
        self.assertHypoTokens(hypos[0][0], [w1, eos])
        self.assertHypoScore(hypos[0][0], [0.9, 1.0])
        # sentence 1, beam 2
        self.assertHypoTokens(hypos[0][1], [w2, w2, eos])
        self.assertHypoScore(hypos[0][1], [0.1, 0.1, 0.6])
        # sentence 2, beam 1
        self.assertHypoTokens(hypos[1][0], [w1, w2, eos])
        self.assertHypoScore(hypos[1][0], [0.7, 0.4, 0.6])
        # sentence 2, beam 2
        self.assertHypoTokens(hypos[1][1], [w2, w2, eos])
        self.assertHypoScore(hypos[1][1], [0.3, 0.9, 0.01])
開發者ID:nusnlp，項目名稱:crosentgec，代碼行數:18，代碼來源:test_sequence_generator.py

示例6: test_with_normalization

# 需要導入模塊: from fairseq import sequence_generator [as 別名]
# 或者: from fairseq.sequence_generator import SequenceGenerator [as 別名]
def test_with_normalization(self):
        generator = SequenceGenerator([self.model], self.tgt_dict, beam_size=2)
        hypos = generator.forward(self.sample)
        eos, w1, w2 = self.tgt_dict.eos(), self.w1, self.w2
        # sentence 1, beam 1
        self.assertHypoTokens(hypos[0][0], [w1, eos])
        self.assertHypoScore(hypos[0][0], [0.9, 1.0])
        # sentence 1, beam 2
        self.assertHypoTokens(hypos[0][1], [w2, w1, w2, eos])
        self.assertHypoScore(hypos[0][1], [0.1, 0.9, 0.9, 1.0])
        # sentence 2, beam 1
        self.assertHypoTokens(hypos[1][0], [w1, w2, w1, eos])
        self.assertHypoScore(hypos[1][0], [0.7, 0.4, 0.4, 1.0])
        # sentence 2, beam 2
        self.assertHypoTokens(hypos[1][1], [w1, w2, eos])
        self.assertHypoScore(hypos[1][1], [0.7, 0.4, 0.6])
開發者ID:pytorch，項目名稱:fairseq，代碼行數:18，代碼來源:test_sequence_generator.py

示例7: test_without_normalization

# 需要導入模塊: from fairseq import sequence_generator [as 別名]
# 或者: from fairseq.sequence_generator import SequenceGenerator [as 別名]
def test_without_normalization(self):
        # Sentence 1: unchanged from the normalized case
        # Sentence 2: beams swap order
        generator = SequenceGenerator(
            [self.model], self.tgt_dict, beam_size=2, normalize_scores=False
        )
        hypos = generator.forward(self.sample)
        eos, w1, w2 = self.tgt_dict.eos(), self.w1, self.w2
        # sentence 1, beam 1
        self.assertHypoTokens(hypos[0][0], [w1, eos])
        self.assertHypoScore(hypos[0][0], [0.9, 1.0], normalized=False)
        # sentence 1, beam 2
        self.assertHypoTokens(hypos[0][1], [w2, w1, w2, eos])
        self.assertHypoScore(hypos[0][1], [0.1, 0.9, 0.9, 1.0], normalized=False)
        # sentence 2, beam 1
        self.assertHypoTokens(hypos[1][0], [w1, w2, eos])
        self.assertHypoScore(hypos[1][0], [0.7, 0.4, 0.6], normalized=False)
        # sentence 2, beam 2
        self.assertHypoTokens(hypos[1][1], [w1, w2, w1, eos])
        self.assertHypoScore(hypos[1][1], [0.7, 0.4, 0.4, 1.0], normalized=False)
開發者ID:pytorch，項目名稱:fairseq，代碼行數:22，代碼來源:test_sequence_generator.py

示例8: test_with_lenpen_favoring_short_hypos

# 需要導入模塊: from fairseq import sequence_generator [as 別名]
# 或者: from fairseq.sequence_generator import SequenceGenerator [as 別名]
def test_with_lenpen_favoring_short_hypos(self):
        lenpen = 0.6
        generator = SequenceGenerator(
            [self.model], self.tgt_dict, beam_size=2, len_penalty=lenpen
        )
        hypos = generator.forward(self.sample)
        eos, w1, w2 = self.tgt_dict.eos(), self.w1, self.w2
        # sentence 1, beam 1
        self.assertHypoTokens(hypos[0][0], [w1, eos])
        self.assertHypoScore(hypos[0][0], [0.9, 1.0], lenpen=lenpen)
        # sentence 1, beam 2
        self.assertHypoTokens(hypos[0][1], [w2, w1, w2, eos])
        self.assertHypoScore(hypos[0][1], [0.1, 0.9, 0.9, 1.0], lenpen=lenpen)
        # sentence 2, beam 1
        self.assertHypoTokens(hypos[1][0], [w1, w2, eos])
        self.assertHypoScore(hypos[1][0], [0.7, 0.4, 0.6], lenpen=lenpen)
        # sentence 2, beam 2
        self.assertHypoTokens(hypos[1][1], [w1, w2, w1, eos])
        self.assertHypoScore(hypos[1][1], [0.7, 0.4, 0.4, 1.0], lenpen=lenpen)
開發者ID:pytorch，項目名稱:fairseq，代碼行數:21，代碼來源:test_sequence_generator.py

示例9: test_with_lenpen_favoring_long_hypos

# 需要導入模塊: from fairseq import sequence_generator [as 別名]
# 或者: from fairseq.sequence_generator import SequenceGenerator [as 別名]
def test_with_lenpen_favoring_long_hypos(self):
        lenpen = 5.0
        generator = SequenceGenerator(
            [self.model], self.tgt_dict, beam_size=2, len_penalty=lenpen
        )
        hypos = generator.forward(self.sample)
        eos, w1, w2 = self.tgt_dict.eos(), self.w1, self.w2
        # sentence 1, beam 1
        self.assertHypoTokens(hypos[0][0], [w2, w1, w2, eos])
        self.assertHypoScore(hypos[0][0], [0.1, 0.9, 0.9, 1.0], lenpen=lenpen)
        # sentence 1, beam 2
        self.assertHypoTokens(hypos[0][1], [w1, eos])
        self.assertHypoScore(hypos[0][1], [0.9, 1.0], lenpen=lenpen)
        # sentence 2, beam 1
        self.assertHypoTokens(hypos[1][0], [w1, w2, w1, eos])
        self.assertHypoScore(hypos[1][0], [0.7, 0.4, 0.4, 1.0], lenpen=lenpen)
        # sentence 2, beam 2
        self.assertHypoTokens(hypos[1][1], [w1, w2, eos])
        self.assertHypoScore(hypos[1][1], [0.7, 0.4, 0.6], lenpen=lenpen)
開發者ID:pytorch，項目名稱:fairseq，代碼行數:21，代碼來源:test_sequence_generator.py

示例10: test_diverse_beam_search

# 需要導入模塊: from fairseq import sequence_generator [as 別名]
# 或者: from fairseq.sequence_generator import SequenceGenerator [as 別名]
def test_diverse_beam_search(self):
        search_strategy = search.DiverseBeamSearch(self.tgt_dict, num_groups=2, diversity_strength=0.)
        generator = SequenceGenerator(
            [self.model], self.tgt_dict, beam_size=2, search_strategy=search_strategy,
        )
        sample = {'net_input': {'src_tokens': self.src_tokens, 'src_lengths': self.src_lengths}}
        hypos = generator.forward(sample)
        eos, w1, w2 = self.eos, self.w1, self.w2
        # sentence 1, beam 1
        self.assertHypoTokens(hypos[0][0], [w1, w1, eos])
        self.assertHypoScore(hypos[0][0], [0.9, 0.6, 1.0])
        # sentence 1, beam 2
        self.assertHypoTokens(hypos[0][1], [w1, w1, eos])
        self.assertHypoScore(hypos[0][1], [0.9, 0.6, 1.0])
        # sentence 2, beam 1
        self.assertHypoTokens(hypos[1][0], [w1, w2, eos])
        self.assertHypoScore(hypos[1][0], [0.7, 0.4, 0.9])
        # sentence 2, beam 2
        self.assertHypoTokens(hypos[1][1], [w1, w2, eos])
        self.assertHypoScore(hypos[1][1], [0.7, 0.4, 0.9])
開發者ID:pytorch，項目名稱:fairseq，代碼行數:22，代碼來源:test_sequence_generator.py

示例11: build_generator

# 需要導入模塊: from fairseq import sequence_generator [as 別名]
# 或者: from fairseq.sequence_generator import SequenceGenerator [as 別名]
def build_generator(self, models, args):
        if getattr(args, 'score_reference', False):
            from fairseq.sequence_scorer import SequenceScorer
            return SequenceScorer(
                self.target_dictionary,
                eos=self.tgt_dict.index('[{}]'.format(self.args.target_lang))
            )
        else:
            from fairseq.sequence_generator import SequenceGenerator
            return SequenceGenerator(
                models,
                self.target_dictionary,
                beam_size=getattr(args, 'beam', 5),
                max_len_a=getattr(args, 'max_len_a', 0),
                max_len_b=getattr(args, 'max_len_b', 200),
                min_len=getattr(args, 'min_len', 1),
                normalize_scores=(not getattr(args, 'unnormalized', False)),
                len_penalty=getattr(args, 'lenpen', 1),
                unk_penalty=getattr(args, 'unkpen', 0),
                temperature=getattr(args, 'temperature', 1.),
                match_source_len=getattr(args, 'match_source_len', False),
                no_repeat_ngram_size=getattr(args, 'no_repeat_ngram_size', 0),
                eos=self.tgt_dict.index('[{}]'.format(self.args.target_lang))
            )
開發者ID:pytorch，項目名稱:fairseq，代碼行數:26，代碼來源:translation_from_pretrained_bart.py

示例12: build_generator

# 需要導入模塊: from fairseq import sequence_generator [as 別名]
# 或者: from fairseq.sequence_generator import SequenceGenerator [as 別名]
def build_generator(self, models, args):
        if getattr(args, 'score_reference', False):
            from fairseq.sequence_scorer import SequenceScorer
            return SequenceScorer(
                self.target_dictionary,
                eos=self.tgt_dict.index('[{}]'.format(self.target_lang))
            )
        else:
            from fairseq.sequence_generator import SequenceGenerator
            return SequenceGenerator(
                models,
                self.target_dictionary,
                beam_size=getattr(args, 'beam', 5),
                max_len_a=getattr(args, 'max_len_a', 0),
                max_len_b=getattr(args, 'max_len_b', 200),
                min_len=getattr(args, 'min_len', 1),
                normalize_scores=(not getattr(args, 'unnormalized', False)),
                len_penalty=getattr(args, 'lenpen', 1),
                unk_penalty=getattr(args, 'unkpen', 0),
                temperature=getattr(args, 'temperature', 1.),
                match_source_len=getattr(args, 'match_source_len', False),
                no_repeat_ngram_size=getattr(args, 'no_repeat_ngram_size', 0),
                eos=self.tgt_dict.index('[{}]'.format(self.args.target_lang))
            )
開發者ID:elbayadm，項目名稱:attn2d，代碼行數:26，代碼來源:translation_from_pretrained_bart.py

示例13: test_with_normalization

# 需要導入模塊: from fairseq import sequence_generator [as 別名]
# 或者: from fairseq.sequence_generator import SequenceGenerator [as 別名]
def test_with_normalization(self):
        generator = SequenceGenerator(self.tgt_dict, beam_size=2)
        hypos = generator.generate([self.model], self.sample)
        eos, w1, w2 = self.tgt_dict.eos(), self.w1, self.w2
        # sentence 1, beam 1
        self.assertHypoTokens(hypos[0][0], [w1, eos])
        self.assertHypoScore(hypos[0][0], [0.9, 1.0])
        # sentence 1, beam 2
        self.assertHypoTokens(hypos[0][1], [w2, w1, w2, eos])
        self.assertHypoScore(hypos[0][1], [0.1, 0.9, 0.9, 1.0])
        # sentence 2, beam 1
        self.assertHypoTokens(hypos[1][0], [w1, w2, w1, eos])
        self.assertHypoScore(hypos[1][0], [0.7, 0.4, 0.4, 1.0])
        # sentence 2, beam 2
        self.assertHypoTokens(hypos[1][1], [w1, w2, eos])
        self.assertHypoScore(hypos[1][1], [0.7, 0.4, 0.6])
開發者ID:kakaobrain，項目名稱:helo_word，代碼行數:18，代碼來源:test_sequence_generator.py

示例14: test_without_normalization

# 需要導入模塊: from fairseq import sequence_generator [as 別名]
# 或者: from fairseq.sequence_generator import SequenceGenerator [as 別名]
def test_without_normalization(self):
        # Sentence 1: unchanged from the normalized case
        # Sentence 2: beams swap order
        generator = SequenceGenerator(self.tgt_dict, beam_size=2, normalize_scores=False)
        hypos = generator.generate([self.model], self.sample)
        eos, w1, w2 = self.tgt_dict.eos(), self.w1, self.w2
        # sentence 1, beam 1
        self.assertHypoTokens(hypos[0][0], [w1, eos])
        self.assertHypoScore(hypos[0][0], [0.9, 1.0], normalized=False)
        # sentence 1, beam 2
        self.assertHypoTokens(hypos[0][1], [w2, w1, w2, eos])
        self.assertHypoScore(hypos[0][1], [0.1, 0.9, 0.9, 1.0], normalized=False)
        # sentence 2, beam 1
        self.assertHypoTokens(hypos[1][0], [w1, w2, eos])
        self.assertHypoScore(hypos[1][0], [0.7, 0.4, 0.6], normalized=False)
        # sentence 2, beam 2
        self.assertHypoTokens(hypos[1][1], [w1, w2, w1, eos])
        self.assertHypoScore(hypos[1][1], [0.7, 0.4, 0.4, 1.0], normalized=False)
開發者ID:kakaobrain，項目名稱:helo_word，代碼行數:20，代碼來源:test_sequence_generator.py

示例15: test_with_lenpen_favoring_short_hypos

# 需要導入模塊: from fairseq import sequence_generator [as 別名]
# 或者: from fairseq.sequence_generator import SequenceGenerator [as 別名]
def test_with_lenpen_favoring_short_hypos(self):
        lenpen = 0.6
        generator = SequenceGenerator(self.tgt_dict, beam_size=2, len_penalty=lenpen)
        hypos = generator.generate([self.model], self.sample)
        eos, w1, w2 = self.tgt_dict.eos(), self.w1, self.w2
        # sentence 1, beam 1
        self.assertHypoTokens(hypos[0][0], [w1, eos])
        self.assertHypoScore(hypos[0][0], [0.9, 1.0], lenpen=lenpen)
        # sentence 1, beam 2
        self.assertHypoTokens(hypos[0][1], [w2, w1, w2, eos])
        self.assertHypoScore(hypos[0][1], [0.1, 0.9, 0.9, 1.0], lenpen=lenpen)
        # sentence 2, beam 1
        self.assertHypoTokens(hypos[1][0], [w1, w2, eos])
        self.assertHypoScore(hypos[1][0], [0.7, 0.4, 0.6], lenpen=lenpen)
        # sentence 2, beam 2
        self.assertHypoTokens(hypos[1][1], [w1, w2, w1, eos])
        self.assertHypoScore(hypos[1][1], [0.7, 0.4, 0.4, 1.0], lenpen=lenpen)
開發者ID:kakaobrain，項目名稱:helo_word，代碼行數:19，代碼來源:test_sequence_generator.py


注：本文中的fairseq.sequence_generator.SequenceGenerator方法示例由純淨天空整理自Github/MSDocs等開源代碼及文檔管理平台，相關代碼片段篩選自各路編程大神貢獻的開源項目，源碼版權歸原作者所有，傳播和使用請參考對應項目的License；未經允許，請勿轉載。