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# coding=utf-8 | |
# Copyright 2022 The OpenBMB Team and The HuggingFace Inc. team. | |
# | |
# Licensed under the Apache License, Version 2.0 (the "License"); | |
# you may not use this file except in compliance with the License. | |
# You may obtain a copy of the License at | |
# | |
# http://www.apache.org/licenses/LICENSE-2.0 | |
# | |
# Unless required by applicable law or agreed to in writing, software | |
# distributed under the License is distributed on an "AS IS" BASIS, | |
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
# See the License for the specific language governing permissions and | |
# limitations under the License. | |
import os | |
import unittest | |
from transformers.models.cpmant.tokenization_cpmant import VOCAB_FILES_NAMES, CpmAntTokenizer | |
from transformers.testing_utils import require_jieba, tooslow | |
from ...test_tokenization_common import TokenizerTesterMixin | |
class CPMAntTokenizationTest(TokenizerTesterMixin, unittest.TestCase): | |
tokenizer_class = CpmAntTokenizer | |
test_rust_tokenizer = False | |
def setUp(self): | |
super().setUp() | |
vocab_tokens = [ | |
"<d>", | |
"</d>", | |
"<s>", | |
"</s>", | |
"</_>", | |
"<unk>", | |
"<pad>", | |
"</n>", | |
"我", | |
"是", | |
"C", | |
"P", | |
"M", | |
"A", | |
"n", | |
"t", | |
] | |
self.vocab_file = os.path.join(self.tmpdirname, VOCAB_FILES_NAMES["vocab_file"]) | |
with open(self.vocab_file, "w", encoding="utf-8") as vocab_writer: | |
vocab_writer.write("".join([x + "\n" for x in vocab_tokens])) | |
def test_pre_tokenization(self): | |
tokenizer = CpmAntTokenizer.from_pretrained("openbmb/cpm-ant-10b") | |
texts = "今天天气真好!" | |
jieba_tokens = ["今天", "天气", "真", "好", "!"] | |
tokens = tokenizer.tokenize(texts) | |
self.assertListEqual(tokens, jieba_tokens) | |
normalized_text = "今天天气真好!" | |
input_tokens = [tokenizer.bos_token] + tokens | |
input_jieba_tokens = [6, 9802, 14962, 2082, 831, 244] | |
self.assertListEqual(tokenizer.convert_tokens_to_ids(input_tokens), input_jieba_tokens) | |
reconstructed_text = tokenizer.decode(input_jieba_tokens) | |
self.assertEqual(reconstructed_text, normalized_text) | |