コード例 #1
0
ファイル: test_spc_tokenizer.py プロジェクト: phymucs/NeMo
    def test_add_special_tokens(self):
        tokenizer = SentencePieceTokenizer("./tests/data/m_common.model")

        special_tokens = ["[CLS]", "[MASK]", "[SEP]"]
        tokenizer.add_special_tokens(special_tokens)

        self.assertTrue(tokenizer.vocab_size == tokenizer.original_vocab_size +
                        len(special_tokens))
    def test_ids_to_text(self):
        tokenizer = SentencePieceTokenizer("./tests/data/m_common.model")
        special_tokens = nemo_nlp.data.tokenizers.MODEL_SPECIAL_TOKENS['bert']
        tokenizer.add_special_tokens(special_tokens)

        text = "[CLS] a b c [MASK] e f [SEP] g h i [SEP]"
        ids = tokenizer.text_to_ids(text)
        result = tokenizer.ids_to_text(ids)

        self.assertTrue(text == result)
コード例 #3
0
ファイル: test_spc_tokenizer.py プロジェクト: phymucs/NeMo
    def test_ids_to_text(self):
        tokenizer = SentencePieceTokenizer("./tests/data/m_common.model")

        special_tokens = ["[CLS]", "[MASK]", "[SEP]"]
        tokenizer.add_special_tokens(special_tokens)

        text = "[CLS] a b c [MASK] e f [SEP] g h i [SEP]"
        ids = tokenizer.text_to_ids(text)
        result = tokenizer.ids_to_text(ids)

        self.assertTrue(text == result)
    def test_text_to_ids(self):
        tokenizer = SentencePieceTokenizer("./tests/data/m_common.model")
        special_tokens = nemo_nlp.data.tokenizers.MODEL_SPECIAL_TOKENS['bert']
        tokenizer.add_special_tokens(special_tokens)

        text = "[CLS] a b c [MASK] e f [SEP] g h i [SEP]"
        ids = tokenizer.text_to_ids(text)

        self.assertTrue(len(ids) == len(text.split()))
        self.assertTrue(ids.count(tokenizer.token_to_id("[CLS]")) == 1)
        self.assertTrue(ids.count(tokenizer.token_to_id("[MASK]")) == 1)
        self.assertTrue(ids.count(tokenizer.token_to_id("[SEP]")) == 2)
コード例 #5
0
ファイル: test_spc_tokenizer.py プロジェクト: phymucs/NeMo
    def test_text_to_ids(self):
        tokenizer = SentencePieceTokenizer("./tests/data/m_common.model")

        special_tokens = ["[CLS]", "[MASK]", "[SEP]"]
        tokenizer.add_special_tokens(special_tokens)

        text = "[CLS] a b c [MASK] e f [SEP] g h i [SEP]"
        ids = tokenizer.text_to_ids(text)

        self.assertTrue(len(ids) == len(text.split()))
        self.assertTrue(ids.count(tokenizer.special_tokens["[CLS]"]) == 1)
        self.assertTrue(ids.count(tokenizer.special_tokens["[MASK]"]) == 1)
        self.assertTrue(ids.count(tokenizer.special_tokens["[SEP]"]) == 2)
    def test_ids_to_tokens(self):
        tokenizer = SentencePieceTokenizer("./tests/data/m_common.model")
        special_tokens = nemo_nlp.data.tokenizers.MODEL_SPECIAL_TOKENS['bert']
        tokenizer.add_special_tokens(special_tokens)

        text = "[CLS] a b c [MASK] e f [SEP] g h i [SEP]"
        tokens = tokenizer.text_to_tokens(text)
        ids = tokenizer.tokens_to_ids(tokens)
        result = tokenizer.ids_to_tokens(ids)

        self.assertTrue(len(result) == len(tokens))

        for i in range(len(result)):
            self.assertTrue(result[i] == tokens[i])
コード例 #7
0
ファイル: test_spc_tokenizer.py プロジェクト: phymucs/NeMo
    def test_ids_to_tokens(self):
        tokenizer = SentencePieceTokenizer("./tests/data/m_common.model")

        special_tokens = ["[CLS]", "[MASK]", "[SEP]"]
        tokenizer.add_special_tokens(special_tokens)

        text = "[CLS] a b c [MASK] e f [SEP] g h i [SEP]"
        tokens = tokenizer.text_to_tokens(text)
        ids = tokenizer.tokens_to_ids(tokens)
        result = tokenizer.ids_to_tokens(ids)

        self.assertTrue(len(result) == len(tokens))

        for i in range(len(result)):
            self.assertTrue(result[i] == tokens[i])
 def test_add_special_tokens(self):
     tokenizer = SentencePieceTokenizer("./tests/data/m_common.model")
     special_tokens = nemo_nlp.data.tokenizers.MODEL_SPECIAL_TOKENS['bert']
     tokenizer.add_special_tokens(special_tokens)
     self.assertTrue(tokenizer.vocab_size == tokenizer.original_vocab_size + len(set(special_tokens.values())))