68 lines
2.6 KiB
Python
68 lines
2.6 KiB
Python
# coding=utf-8
|
|
# Copyright 2021 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.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
|
|
from transformers.testing_utils import get_tests_dir
|
|
|
|
from ...test_tokenization_common import TokenizerTesterMixin
|
|
|
|
|
|
SAMPLE_VOCAB = get_tests_dir("fixtures/test_sentencepiece_bpe.model")
|
|
|
|
|
|
class BartphoTokenizerTest(TokenizerTesterMixin, unittest.TestCase):
|
|
from_pretrained_id = "vinai/bartpho-syllable"
|
|
tokenizer_class = BartphoTokenizer
|
|
test_rust_tokenizer = False
|
|
test_sentencepiece = True
|
|
|
|
def setUp(self):
|
|
super().setUp()
|
|
|
|
vocab = ["▁This", "▁is", "▁a", "▁t", "est"]
|
|
vocab_tokens = dict(zip(vocab, range(len(vocab))))
|
|
self.special_tokens_map = {"unk_token": "<unk>"}
|
|
|
|
self.monolingual_vocab_file = os.path.join(self.tmpdirname, VOCAB_FILES_NAMES["monolingual_vocab_file"])
|
|
with open(self.monolingual_vocab_file, "w", encoding="utf-8") as fp:
|
|
for token in vocab_tokens:
|
|
fp.write(f"{token} {vocab_tokens[token]}\n")
|
|
|
|
tokenizer = BartphoTokenizer(SAMPLE_VOCAB, self.monolingual_vocab_file, **self.special_tokens_map)
|
|
tokenizer.save_pretrained(self.tmpdirname)
|
|
|
|
def get_tokenizer(self, **kwargs):
|
|
kwargs.update(self.special_tokens_map)
|
|
return BartphoTokenizer.from_pretrained(self.tmpdirname, **kwargs)
|
|
|
|
def get_input_output_texts(self, tokenizer):
|
|
input_text = "This is a là test"
|
|
output_text = "This is a<unk><unk> test"
|
|
return input_text, output_text
|
|
|
|
def test_full_tokenizer(self):
|
|
tokenizer = BartphoTokenizer(SAMPLE_VOCAB, self.monolingual_vocab_file, **self.special_tokens_map)
|
|
text = "This is a là test"
|
|
bpe_tokens = "▁This ▁is ▁a ▁l à ▁t est".split()
|
|
tokens = tokenizer.tokenize(text)
|
|
self.assertListEqual(tokens, bpe_tokens)
|
|
|
|
input_tokens = tokens + [tokenizer.unk_token]
|
|
input_bpe_tokens = [4, 5, 6, 3, 3, 7, 8, 3]
|
|
self.assertListEqual(tokenizer.convert_tokens_to_ids(input_tokens), input_bpe_tokens)
|