wehub-resource-sync
175 lines
8.2 KiB
Python
175 lines
8.2 KiB
Python
# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
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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 unittest
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from paddlenlp.transformers.ernie_layout.tokenizer import ErnieLayoutTokenizer
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from paddlenlp.transformers.tokenizer_utils import PretrainedTokenizer
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from ..test_tokenizer_common import TokenizerTesterMixin
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class ErnieLayoutEnglishTokenizationTest(TokenizerTesterMixin, unittest.TestCase):
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tokenizer_class = ErnieLayoutTokenizer
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space_between_special_tokens = True
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def get_tokenizer(self, **kwargs) -> PretrainedTokenizer:
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return ErnieLayoutTokenizer.from_pretrained("ernie-layoutx-base-uncased", **kwargs)
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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 = "[CLS]"
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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_full_tokenizer(self):
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tokenizer = self.get_tokenizer()
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tokens = tokenizer.tokenize("This is a test")
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self.assertListEqual(tokens, ["▁This", "▁is", "▁a", "▁test"])
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self.assertListEqual(tokenizer.convert_tokens_to_ids(tokens), [3293, 83, 10, 3034])
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tokens = tokenizer.tokenize("I was born in 92000, and this is falsé.")
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self.assertListEqual(
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tokens, ["▁I", "▁was", "▁born", "▁in", "▁9", "2000", ",", "▁and", "▁this", "▁is", "▁fals", "é", "."]
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)
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ids = tokenizer.convert_tokens_to_ids(tokens)
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self.assertListEqual(ids, [87, 509, 103122, 23, 483, 13821, 4, 136, 903, 83, 84047, 446, 5])
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back_tokens = tokenizer.convert_ids_to_tokens(ids)
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self.assertListEqual(back_tokens, tokens)
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def test_clean_text(self):
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tokenizer = self.get_tokenizer()
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# Example taken from the issue https://github.com/huggingface/tokenizers/issues/340
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self.assertListEqual(
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[tokenizer.tokenize(t) for t in ["Test", "\xad", "test"]], [["▁Test"], ["▁", "\xad"], ["▁test"]]
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)
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def test_sequence_builders(self):
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tokenizer = self.get_tokenizer()
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text = tokenizer.encode("sequence builders", return_token_type_ids=None, add_special_tokens=False)["input_ids"]
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text_2 = tokenizer.encode("multi-sequence build", return_token_type_ids=None, add_special_tokens=False)[
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"input_ids"
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]
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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 == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]
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assert encoded_pair == [tokenizer.cls_token_id] + text + [
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tokenizer.sep_token_id,
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tokenizer.sep_token_id,
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] + text_2 + [tokenizer.sep_token_id]
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def test_add_tokens(self):
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for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
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with self.subTest(f"{tokenizer.__class__.__name__} ({pretrained_name})"):
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tokenizer = self.tokenizer_class.from_pretrained(pretrained_name, **kwargs)
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vocab_size = len(tokenizer)
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self.assertEqual(tokenizer.add_tokens(""), 0)
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self.assertEqual(tokenizer.add_tokens("testoken"), 1)
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self.assertEqual(tokenizer.add_tokens(["testoken1", "testtoken2"]), 2)
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self.assertEqual(len(tokenizer), vocab_size + 3)
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self.assertEqual(tokenizer.add_special_tokens({}), 0)
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self.assertRaises(
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AssertionError, tokenizer.add_special_tokens, {"additional_special_tokens": "<testtoken1>"}
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)
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self.assertEqual(tokenizer.add_special_tokens({"additional_special_tokens": ["<testtoken2>"]}), 1)
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self.assertEqual(
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tokenizer.add_special_tokens({"additional_special_tokens": ["<testtoken3>", "<testtoken4>"]}), 2
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)
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self.assertIn("<testtoken3>", tokenizer.special_tokens_map["additional_special_tokens"])
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self.assertIsInstance(tokenizer.special_tokens_map["additional_special_tokens"], list)
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self.assertGreaterEqual(len(tokenizer.special_tokens_map["additional_special_tokens"]), 2)
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self.assertEqual(len(tokenizer), vocab_size + 6)
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def test_add_tokens_tokenizer(self):
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tokenizers = self.get_tokenizers(do_lower_case=False)
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for tokenizer in tokenizers:
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with self.subTest(f"{tokenizer.__class__.__name__}"):
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vocab_size = tokenizer.vocab_size
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all_size = len(tokenizer)
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self.assertNotEqual(vocab_size, 0)
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new_toks = ["aaaaa bbbbbb", "cccccccccdddddddd"]
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added_toks = tokenizer.add_tokens(new_toks)
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vocab_size_2 = tokenizer.vocab_size
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all_size_2 = len(tokenizer)
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self.assertNotEqual(vocab_size_2, 0)
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self.assertEqual(vocab_size, vocab_size_2)
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self.assertEqual(added_toks, len(new_toks))
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self.assertEqual(all_size_2, all_size + len(new_toks))
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tokens = tokenizer.encode(
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"aaaaa bbbbbb low cccccccccdddddddd l", return_token_type_ids=None, add_special_tokens=False
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)["input_ids"]
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self.assertGreaterEqual(len(tokens), 4)
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self.assertGreater(tokens[0], tokenizer.vocab_size - 1)
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self.assertGreater(tokens[-2], tokenizer.vocab_size - 1)
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def test_padding_to_multiple_of(self):
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tokenizers = self.get_tokenizers(model_max_length=64)
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for tokenizer in tokenizers:
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with self.subTest(f"{tokenizer.__class__.__name__}"):
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if tokenizer.pad_token is None:
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self.skipTest("No padding token.")
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else:
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empty_tokens = tokenizer("", padding=True, pad_to_multiple_of=8)
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normal_tokens = tokenizer("This is a sample input", padding=True, pad_to_multiple_of=8)
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for key, value in empty_tokens.items():
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self.assertEqual(len(value) % 8, 0, f"BatchEncoding.{key} is not multiple of 8")
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for key, value in normal_tokens.items():
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self.assertEqual(len(value) % 8, 0, f"BatchEncoding.{key} is not multiple of 8")
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normal_tokens = tokenizer("This", pad_to_multiple_of=8)
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for key, value in normal_tokens.items():
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self.assertNotEqual(len(value) % 8, 0, f"BatchEncoding.{key} is not multiple of 8")
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# Should also work with truncation
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normal_tokens = tokenizer("This", padding=True, truncation=True, pad_to_multiple_of=8)
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for key, value in normal_tokens.items():
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self.assertEqual(len(value) % 8, 0, f"BatchEncoding.{key} is not multiple of 8")
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# truncation to something which is not a multiple of pad_to_multiple_of raises an error
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self.assertRaises(
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ValueError,
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tokenizer.__call__,
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"This",
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padding=True,
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truncation=True,
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max_length=12,
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pad_to_multiple_of=8,
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)
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def test_token_type_ids(self):
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self.skipTest("Ernie-Layout model doesn't have token_type embedding. so skip this test")
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