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| # coding=utf-8 | |
| # Copyright 2020 The HuggingFace Inc. team, The Microsoft Research 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 import BatchEncoding | |
| from transformers.models.bert.tokenization_bert import ( | |
| BasicTokenizer, | |
| WordpieceTokenizer, | |
| _is_control, | |
| _is_punctuation, | |
| _is_whitespace, | |
| ) | |
| from transformers.models.prophetnet.tokenization_prophetnet import VOCAB_FILES_NAMES, ProphetNetTokenizer | |
| from transformers.testing_utils import require_torch, slow | |
| from ...test_tokenization_common import TokenizerTesterMixin | |
| class ProphetNetTokenizationTest(TokenizerTesterMixin, unittest.TestCase): | |
| tokenizer_class = ProphetNetTokenizer | |
| test_rust_tokenizer = False | |
| def setUp(self): | |
| super().setUp() | |
| vocab_tokens = [ | |
| "[UNK]", | |
| "[CLS]", | |
| "[SEP]", | |
| "[PAD]", | |
| "[MASK]", | |
| "want", | |
| "##want", | |
| "##ed", | |
| "wa", | |
| "un", | |
| "runn", | |
| "##ing", | |
| ",", | |
| "low", | |
| "lowest", | |
| ] | |
| 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 get_input_output_texts(self, tokenizer): | |
| input_text = "UNwant\u00E9d,running" | |
| output_text = "unwanted, running" | |
| return input_text, output_text | |
| def test_full_tokenizer(self): | |
| tokenizer = self.tokenizer_class(self.vocab_file) | |
| tokens = tokenizer.tokenize("UNwant\u00E9d,running") | |
| self.assertListEqual(tokens, ["un", "##want", "##ed", ",", "runn", "##ing"]) | |
| self.assertListEqual(tokenizer.convert_tokens_to_ids(tokens), [9, 6, 7, 12, 10, 11]) | |
| def test_chinese(self): | |
| tokenizer = BasicTokenizer() | |
| self.assertListEqual(tokenizer.tokenize("ah\u535A\u63A8zz"), ["ah", "\u535A", "\u63A8", "zz"]) | |
| def test_basic_tokenizer_lower(self): | |
| tokenizer = BasicTokenizer(do_lower_case=True) | |
| self.assertListEqual( | |
| tokenizer.tokenize(" \tHeLLo!how \n Are yoU? "), ["hello", "!", "how", "are", "you", "?"] | |
| ) | |
| self.assertListEqual(tokenizer.tokenize("H\u00E9llo"), ["hello"]) | |
| def test_basic_tokenizer_lower_strip_accents_false(self): | |
| tokenizer = BasicTokenizer(do_lower_case=True, strip_accents=False) | |
| self.assertListEqual( | |
| tokenizer.tokenize(" \tHäLLo!how \n Are yoU? "), ["hällo", "!", "how", "are", "you", "?"] | |
| ) | |
| self.assertListEqual(tokenizer.tokenize("H\u00E9llo"), ["h\u00E9llo"]) | |
| def test_basic_tokenizer_lower_strip_accents_true(self): | |
| tokenizer = BasicTokenizer(do_lower_case=True, strip_accents=True) | |
| self.assertListEqual( | |
| tokenizer.tokenize(" \tHäLLo!how \n Are yoU? "), ["hallo", "!", "how", "are", "you", "?"] | |
| ) | |
| self.assertListEqual(tokenizer.tokenize("H\u00E9llo"), ["hello"]) | |
| def test_basic_tokenizer_lower_strip_accents_default(self): | |
| tokenizer = BasicTokenizer(do_lower_case=True) | |
| self.assertListEqual( | |
| tokenizer.tokenize(" \tHäLLo!how \n Are yoU? "), ["hallo", "!", "how", "are", "you", "?"] | |
| ) | |
| self.assertListEqual(tokenizer.tokenize("H\u00E9llo"), ["hello"]) | |
| def test_basic_tokenizer_no_lower(self): | |
| tokenizer = BasicTokenizer(do_lower_case=False) | |
| self.assertListEqual( | |
| tokenizer.tokenize(" \tHeLLo!how \n Are yoU? "), ["HeLLo", "!", "how", "Are", "yoU", "?"] | |
| ) | |
| def test_basic_tokenizer_no_lower_strip_accents_false(self): | |
| tokenizer = BasicTokenizer(do_lower_case=False, strip_accents=False) | |
| self.assertListEqual( | |
| tokenizer.tokenize(" \tHäLLo!how \n Are yoU? "), ["HäLLo", "!", "how", "Are", "yoU", "?"] | |
| ) | |
| def test_basic_tokenizer_no_lower_strip_accents_true(self): | |
| tokenizer = BasicTokenizer(do_lower_case=False, strip_accents=True) | |
| self.assertListEqual( | |
| tokenizer.tokenize(" \tHäLLo!how \n Are yoU? "), ["HaLLo", "!", "how", "Are", "yoU", "?"] | |
| ) | |
| def test_basic_tokenizer_respects_never_split_tokens(self): | |
| tokenizer = BasicTokenizer(do_lower_case=False, never_split=["[UNK]"]) | |
| self.assertListEqual( | |
| tokenizer.tokenize(" \tHeLLo!how \n Are yoU? [UNK]"), ["HeLLo", "!", "how", "Are", "yoU", "?", "[UNK]"] | |
| ) | |
| def test_wordpiece_tokenizer(self): | |
| vocab_tokens = ["[UNK]", "[CLS]", "[SEP]", "want", "##want", "##ed", "wa", "un", "runn", "##ing"] | |
| vocab = {} | |
| for i, token in enumerate(vocab_tokens): | |
| vocab[token] = i | |
| tokenizer = WordpieceTokenizer(vocab=vocab, unk_token="[UNK]") | |
| self.assertListEqual(tokenizer.tokenize(""), []) | |
| self.assertListEqual(tokenizer.tokenize("unwanted running"), ["un", "##want", "##ed", "runn", "##ing"]) | |
| self.assertListEqual(tokenizer.tokenize("unwantedX running"), ["[UNK]", "runn", "##ing"]) | |
| def test_prepare_batch(self): | |
| tokenizer = self.tokenizer_class.from_pretrained("microsoft/prophetnet-large-uncased") | |
| src_text = ["A long paragraph for summarization.", "Another paragraph for summarization."] | |
| expected_src_tokens = [1037, 2146, 20423, 2005, 7680, 7849, 3989, 1012, 102] | |
| batch = tokenizer(src_text, padding=True, return_tensors="pt") | |
| self.assertIsInstance(batch, BatchEncoding) | |
| result = list(batch.input_ids.numpy()[0]) | |
| self.assertListEqual(expected_src_tokens, result) | |
| self.assertEqual((2, 9), batch.input_ids.shape) | |
| self.assertEqual((2, 9), batch.attention_mask.shape) | |
| def test_is_whitespace(self): | |
| self.assertTrue(_is_whitespace(" ")) | |
| self.assertTrue(_is_whitespace("\t")) | |
| self.assertTrue(_is_whitespace("\r")) | |
| self.assertTrue(_is_whitespace("\n")) | |
| self.assertTrue(_is_whitespace("\u00A0")) | |
| self.assertFalse(_is_whitespace("A")) | |
| self.assertFalse(_is_whitespace("-")) | |
| def test_is_control(self): | |
| self.assertTrue(_is_control("\u0005")) | |
| self.assertFalse(_is_control("A")) | |
| self.assertFalse(_is_control(" ")) | |
| self.assertFalse(_is_control("\t")) | |
| self.assertFalse(_is_control("\r")) | |
| def test_is_punctuation(self): | |
| self.assertTrue(_is_punctuation("-")) | |
| self.assertTrue(_is_punctuation("$")) | |
| self.assertTrue(_is_punctuation("`")) | |
| self.assertTrue(_is_punctuation(".")) | |
| self.assertFalse(_is_punctuation("A")) | |
| self.assertFalse(_is_punctuation(" ")) | |
| def test_sequence_builders(self): | |
| tokenizer = self.tokenizer_class.from_pretrained("microsoft/prophetnet-large-uncased") | |
| text = tokenizer.encode("sequence builders", add_special_tokens=False) | |
| text_2 = tokenizer.encode("multi-sequence build", add_special_tokens=False) | |
| encoded_sentence = tokenizer.build_inputs_with_special_tokens(text) | |
| encoded_pair = tokenizer.build_inputs_with_special_tokens(text, text_2) | |
| assert encoded_sentence == text + [102] | |
| assert encoded_pair == text + [102] + text_2 + [102] | |