99 lines
3.2 KiB
Python
99 lines
3.2 KiB
Python
# coding=utf-8
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# Copyright 2020 The HuggingFace Team. 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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import json
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import os
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import unittest
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from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES, XLMTokenizer
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from transformers.testing_utils import slow
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from .test_tokenization_common import TokenizerTesterMixin
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class XLMTokenizationTest(TokenizerTesterMixin, unittest.TestCase):
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tokenizer_class = XLMTokenizer
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test_rust_tokenizer = False
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def setUp(self):
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super().setUp()
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# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
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vocab = [
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"l",
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"o",
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"w",
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"e",
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"r",
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"s",
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"t",
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"i",
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"d",
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"n",
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"w</w>",
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"r</w>",
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"t</w>",
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"lo",
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"low",
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"er</w>",
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"low</w>",
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"lowest</w>",
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"newer</w>",
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"wider</w>",
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"<unk>",
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]
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vocab_tokens = dict(zip(vocab, range(len(vocab))))
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merges = ["l o 123", "lo w 1456", "e r</w> 1789", ""]
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self.vocab_file = os.path.join(self.tmpdirname, VOCAB_FILES_NAMES["vocab_file"])
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self.merges_file = os.path.join(self.tmpdirname, VOCAB_FILES_NAMES["merges_file"])
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with open(self.vocab_file, "w") as fp:
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fp.write(json.dumps(vocab_tokens))
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with open(self.merges_file, "w") as fp:
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fp.write("\n".join(merges))
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def get_input_output_texts(self, tokenizer):
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input_text = "lower newer"
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output_text = "lower newer"
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return input_text, output_text
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def test_full_tokenizer(self):
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"""Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt"""
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tokenizer = XLMTokenizer(self.vocab_file, self.merges_file)
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text = "lower"
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bpe_tokens = ["low", "er</w>"]
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tokens = tokenizer.tokenize(text)
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self.assertListEqual(tokens, bpe_tokens)
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input_tokens = tokens + ["<unk>"]
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input_bpe_tokens = [14, 15, 20]
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self.assertListEqual(tokenizer.convert_tokens_to_ids(input_tokens), input_bpe_tokens)
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@slow
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def test_sequence_builders(self):
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tokenizer = XLMTokenizer.from_pretrained("xlm-mlm-en-2048")
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text = tokenizer.encode("sequence builders", add_special_tokens=False)
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text_2 = tokenizer.encode("multi-sequence build", add_special_tokens=False)
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encoded_sentence = tokenizer.build_inputs_with_special_tokens(text)
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encoded_pair = tokenizer.build_inputs_with_special_tokens(text, text_2)
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assert encoded_sentence == [0] + text + [1]
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assert encoded_pair == [0] + text + [1] + text_2 + [1]
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