wehub-resource-sync
163 lines
7.2 KiB
Python
163 lines
7.2 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 unittest
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from paddlenlp.transformers import DebertaV2Tokenizer
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from ...testing_utils import get_tests_dir
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from ..test_tokenizer_common import TokenizerTesterMixin
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SAMPLE_VOCAB = get_tests_dir("fixtures/spiece.model")
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class DebertaV2TokenizationTest(TokenizerTesterMixin, unittest.TestCase):
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tokenizer_class = DebertaV2Tokenizer
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from_pretrained_kwargs = {"add_prefix_space": True}
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test_seq2seq = False
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from_pretrained_vocab_key = "sentencepiece_model_file"
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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 = DebertaV2Tokenizer(SAMPLE_VOCAB, unk_token="<unk>")
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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 = "this is a test"
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output_text = "this is a test"
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return input_text, output_text
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def test_convert_token_and_id(self):
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"""Test ``_convert_token_to_id`` and ``_convert_id_to_token``."""
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token = "<pad>"
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token_id = 0
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self.assertEqual(self.get_tokenizer()._convert_token_to_id(token), token_id)
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self.assertEqual(self.get_tokenizer()._convert_id_to_token(token_id), token)
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def test_get_vocab(self):
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vocab_keys = list(self.get_tokenizer().get_vocab().keys())
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self.assertEqual(vocab_keys[0], "<pad>")
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self.assertEqual(vocab_keys[1], "<unk>")
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self.assertEqual(vocab_keys[-1], "[PAD]")
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self.assertEqual(len(vocab_keys), 30_001)
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def test_vocab_size(self):
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self.assertEqual(self.get_tokenizer().vocab_size, 30_000)
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def test_do_lower_case(self):
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# fmt: off
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sequence = " \tHeLLo!how \n Are yoU? "
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tokens_target = ["▁hello", "!", "how", "▁are", "▁you", "?"]
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# fmt: on
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tokenizer = DebertaV2Tokenizer(SAMPLE_VOCAB, do_lower_case=True)
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tokens = tokenizer.convert_ids_to_tokens(tokenizer.encode(sequence, add_special_tokens=False)["input_ids"])
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self.assertListEqual(tokens, tokens_target)
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@unittest.skip("There is an inconsistency between slow and fast tokenizer due to a bug in the fast one.")
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def test_sentencepiece_tokenize_and_convert_tokens_to_string(self):
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pass
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@unittest.skip("There is an inconsistency between slow and fast tokenizer due to a bug in the fast one.")
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def test_sentencepiece_tokenize_and_decode(self):
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pass
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def test_split_by_punct(self):
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# fmt: off
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sequence = "I was born in 92000, and this is falsé."
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tokens_target = ["▁", "<unk>", "▁was", "▁born", "▁in", "▁9", "2000", "▁", ",", "▁and", "▁this", "▁is", "▁fal", "s", "<unk>", "▁", ".", ]
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# fmt: on
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tokenizer = DebertaV2Tokenizer(SAMPLE_VOCAB, split_by_punct=True)
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tokens = tokenizer.convert_ids_to_tokens(tokenizer.encode(sequence, add_special_tokens=False)["input_ids"])
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self.assertListEqual(tokens, tokens_target)
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def test_do_lower_case_split_by_punct(self):
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# fmt: off
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sequence = "I was born in 92000, and this is falsé."
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tokens_target = ["▁i", "▁was", "▁born", "▁in", "▁9", "2000", "▁", ",", "▁and", "▁this", "▁is", "▁fal", "s", "<unk>", "▁", ".", ]
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# fmt: on
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tokenizer = DebertaV2Tokenizer(SAMPLE_VOCAB, do_lower_case=True, split_by_punct=True)
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tokens = tokenizer.convert_ids_to_tokens(tokenizer.encode(sequence, add_special_tokens=False)["input_ids"])
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self.assertListEqual(tokens, tokens_target)
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def test_do_lower_case_split_by_punct_false(self):
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# fmt: off
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sequence = "I was born in 92000, and this is falsé."
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tokens_target = ["▁i", "▁was", "▁born", "▁in", "▁9", "2000", ",", "▁and", "▁this", "▁is", "▁fal", "s", "<unk>", ".", ]
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# fmt: on
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tokenizer = DebertaV2Tokenizer(SAMPLE_VOCAB, do_lower_case=True, split_by_punct=False)
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tokens = tokenizer.convert_ids_to_tokens(tokenizer.encode(sequence, add_special_tokens=False)["input_ids"])
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self.assertListEqual(tokens, tokens_target)
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def test_do_lower_case_false_split_by_punct(self):
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# fmt: off
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sequence = "I was born in 92000, and this is falsé."
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tokens_target = ["▁", "<unk>", "▁was", "▁born", "▁in", "▁9", "2000", "▁", ",", "▁and", "▁this", "▁is", "▁fal", "s", "<unk>", "▁", ".", ]
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# fmt: on
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tokenizer = DebertaV2Tokenizer(SAMPLE_VOCAB, do_lower_case=False, split_by_punct=True)
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tokens = tokenizer.convert_ids_to_tokens(tokenizer.encode(sequence, add_special_tokens=False)["input_ids"])
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self.assertListEqual(tokens, tokens_target)
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def test_do_lower_case_false_split_by_punct_false(self):
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# fmt: off
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sequence = " \tHeLLo!how \n Are yoU? "
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tokens_target = ["▁", "<unk>", "e", "<unk>", "o", "!", "how", "▁", "<unk>", "re", "▁yo", "<unk>", "?"]
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# fmt: on
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tokenizer = DebertaV2Tokenizer(SAMPLE_VOCAB, do_lower_case=False, split_by_punct=False)
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tokens = tokenizer.convert_ids_to_tokens(tokenizer.encode(sequence, add_special_tokens=False)["input_ids"])
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self.assertListEqual(tokens, tokens_target)
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def test_full_tokenizer(self):
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sequence = "This is a test"
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ids_target = [13, 1, 4398, 25, 21, 1289]
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tokens_target = ["▁", "T", "his", "▁is", "▁a", "▁test"]
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back_tokens_target = ["▁", "<unk>", "his", "▁is", "▁a", "▁test"]
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tokenizer = DebertaV2Tokenizer(SAMPLE_VOCAB, keep_accents=True)
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ids = tokenizer.encode(sequence, add_special_tokens=False)["input_ids"]
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self.assertListEqual(ids, ids_target)
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tokens = tokenizer.tokenize(sequence)
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self.assertListEqual(tokens, tokens_target)
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back_tokens = tokenizer.convert_ids_to_tokens(ids)
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self.assertListEqual(back_tokens, back_tokens_target)
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# fmt: off
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sequence = "I was born in 92000, and this is falsé."
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ids_target = [13, 1, 23, 386, 19, 561, 3050, 15, 17, 48, 25, 8256, 18, 1, 9]
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tokens_target = ["▁", "I", "▁was", "▁born", "▁in", "▁9", "2000", ",", "▁and", "▁this", "▁is", "▁fal", "s", "é", ".", ]
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back_tokens_target = ["▁", "<unk>", "▁was", "▁born", "▁in", "▁9", "2000", ",", "▁and", "▁this", "▁is", "▁fal", "s", "<unk>", ".", ]
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# fmt: on
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ids = tokenizer.encode(sequence, add_special_tokens=False)["input_ids"]
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self.assertListEqual(ids, ids_target)
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tokens = tokenizer.tokenize(sequence)
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self.assertListEqual(tokens, tokens_target)
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back_tokens = tokenizer.convert_ids_to_tokens(ids)
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self.assertListEqual(back_tokens, back_tokens_target)
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