wehub-resource-sync
139 lines
4.9 KiB
Python
139 lines
4.9 KiB
Python
# Copyright (c) 2023 PaddlePaddle Authors. 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 shutil
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import tempfile
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import unittest
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from paddlenlp.transformers import LayoutXLMTokenizer
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from ...testing_utils import get_tests_dir
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from ...transformers.test_tokenizer_common import (
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TokenizerTesterMixin,
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filter_non_english,
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)
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SAMPLE_VOCAB = get_tests_dir("fixtures/test_sentencepiece.model")
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class LayoutXLMTokenizationTest(TokenizerTesterMixin, unittest.TestCase):
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tokenizer_class = LayoutXLMTokenizer
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space_between_special_tokens = True
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from_pretrained_filter = filter_non_english
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test_seq2seq = False
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def get_words_and_boxes(self):
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words = ["a", "weirdly", "test"]
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boxes = [[423, 237, 440, 251], [427, 272, 441, 287], [419, 115, 437, 129]]
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return words, boxes
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def get_words_and_boxes_batch(self):
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words = [["a", "weirdly", "test"], ["hello", "my", "name", "is", "bob"]]
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boxes = [
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[[423, 237, 440, 251], [427, 272, 441, 287], [419, 115, 437, 129]],
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[[961, 885, 992, 912], [256, 38, 330, 58], [256, 38, 330, 58], [336, 42, 353, 57], [34, 42, 66, 69]],
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]
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return words, boxes
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def get_question_words_and_boxes(self):
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question = "what's his name?"
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words = ["a", "weirdly", "test"]
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boxes = [[423, 237, 440, 251], [427, 272, 441, 287], [419, 115, 437, 129]]
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return question, words, boxes
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def get_question_words_and_boxes_batch(self):
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questions = ["what's his name?", "how is he called?"]
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words = [["a", "weirdly", "test"], ["what", "a", "laif", "gastn"]]
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boxes = [
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[[423, 237, 440, 251], [427, 272, 441, 287], [419, 115, 437, 129]],
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[[256, 38, 330, 58], [256, 38, 330, 58], [336, 42, 353, 57], [34, 42, 66, 69]],
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]
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return questions, words, boxes
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def setUp(self):
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super().setUp()
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# We have a SentencePiece fixture for testing
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tokenizer = LayoutXLMTokenizer(SAMPLE_VOCAB, keep_accents=True)
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tokenizer.save_pretrained(self.tmpdirname)
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def get_input_output_texts(self, tokenizer):
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input_text = "UNwant\u00E9d,running"
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output_text = "unwanted, running"
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return input_text, output_text
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# override test in `test_tokenization_common.py` because of the required input format of the `__call__`` method of
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# this tokenizer
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def test_save_sentencepiece_tokenizer(self) -> None:
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if not self.test_sentencepiece:
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return
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# We want to verify that we will be able to save the tokenizer even if the original files that were used to
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# build the tokenizer have been deleted in the meantime.
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words, boxes = self.get_words_and_boxes()
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tokenizer_slow_1 = self.get_tokenizer()
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encoding_tokenizer_slow_1 = tokenizer_slow_1(
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words,
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boxes=boxes,
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)
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tmpdirname_1 = tempfile.mkdtemp()
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tmpdirname_2 = tempfile.mkdtemp()
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tokenizer_slow_1.save_pretrained(tmpdirname_1)
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tokenizer_slow_2 = self.tokenizer_class.from_pretrained(tmpdirname_1)
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encoding_tokenizer_slow_2 = tokenizer_slow_2(
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words,
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boxes=boxes,
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)
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shutil.rmtree(tmpdirname_1)
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tokenizer_slow_2.save_pretrained(tmpdirname_2)
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tokenizer_slow_3 = self.tokenizer_class.from_pretrained(tmpdirname_2)
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encoding_tokenizer_slow_3 = tokenizer_slow_3(
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words,
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boxes=boxes,
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)
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shutil.rmtree(tmpdirname_2)
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self.assertEqual(encoding_tokenizer_slow_1, encoding_tokenizer_slow_2)
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self.assertEqual(encoding_tokenizer_slow_1, encoding_tokenizer_slow_3)
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def test_offsets_mapping(self):
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pass
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def test_internal_consistency(self):
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tokenizers = self.get_tokenizers()
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for tokenizer in tokenizers:
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with self.subTest(f"{tokenizer.__class__.__name__}"):
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words, boxes = self.get_words_and_boxes()
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tokens = []
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for word in words:
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tokens.extend(tokenizer.tokenize(word))
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ids = tokenizer.convert_tokens_to_ids(tokens)
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tokens_2 = tokenizer.convert_ids_to_tokens(ids)
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self.assertNotEqual(len(tokens_2), 0)
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text_2 = tokenizer.decode(ids)
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self.assertIsInstance(text_2, str)
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output_text = "a weirdly test"
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self.assertEqual(text_2, output_text)
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