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* Renamed num_added_tokens to num_special_tokens_to_add Signed-off-by: Morgan Funtowicz <morgan@huggingface.co> * Cherry-Pick: Partially fix space only input without special tokens added to the output #3091 Signed-off-by: Morgan Funtowicz <morgan@huggingface.co> * Added property is_fast on PretrainedTokenizer and PretrainedTokenizerFast Signed-off-by: Morgan Funtowicz <morgan@huggingface.co> * Make fast tokenizers unittests work on Windows. * Entirely refactored unittest for tokenizers fast. * Remove ABC class for CommonFastTokenizerTest * Added embeded_special_tokens tests from allenai @dirkgr * Make embeded_special_tokens tests from allenai more generic * Uniformize vocab_size as a property for both Fast and normal tokenizers * Move special tokens handling out of PretrainedTokenizer (SpecialTokensMixin) * Ensure providing None input raise the same ValueError than Python tokenizer + tests. * Fix invalid input for assert_padding when testing batch_encode_plus * Move add_special_tokens from constructor to tokenize/encode/[batch_]encode_plus methods parameter. * Ensure tokenize() correctly forward add_special_tokens to rust. * Adding None checking on top on encode / encode_batch for TransfoXLTokenizerFast. Avoid stripping on None values. * unittests ensure tokenize() also throws a ValueError if provided None * Added add_special_tokens unittest for all supported models. * Style * Make sure TransfoXL test run only if PyTorch is provided. * Split up tokenizers tests for each model type. * Fix invalid unittest with new tokenizers API. * Filter out Roberta openai detector models from unittests. * Introduce BatchEncoding on fast tokenizers path. This new structure exposes all the mappings retrieved from Rust. It also keeps the current behavior with model forward. * Introduce BatchEncoding on slow tokenizers path. Backward compatibility. * Improve error message on BatchEncoding for slow path * Make add_prefix_space True by default on Roberta fast to match Python in majority of cases. * Style and format. * Added typing on all methods for PretrainedTokenizerFast * Style and format * Added path for feeding pretokenized (List[str]) input to PretrainedTokenizerFast. * Style and format * encode_plus now supports pretokenized inputs. * Remove user warning about add_special_tokens when working on pretokenized inputs. * Always go through the post processor. * Added support for pretokenized input pairs on encode_plus * Added is_pretokenized flag on encode_plus for clarity and improved error message on input TypeError. * Added pretokenized inputs support on batch_encode_plus * Update BatchEncoding methods name to match Encoding. * Bump setup.py tokenizers dependency to 0.7.0rc1 * Remove unused parameters in BertTokenizerFast * Make sure Roberta returns token_type_ids for unittests. * Added missing typings * Update add_tokens prototype to match tokenizers side and allow AddedToken * Bumping tokenizers to 0.7.0rc2 * Added documentation for BatchEncoding * Added (unused) is_pretokenized parameter on PreTrainedTokenizer encode_plus/batch_encode_plus methods. * Added higher-level typing for tokenize / encode_plus / batch_encode_plus. * Fix unittests failing because add_special_tokens was defined as a constructor parameter on Rust Tokenizers. * Fix text-classification pipeline using the wrong tokenizer * Make pipelines works with BatchEncoding * Turn off add_special_tokens on tokenize by default. Signed-off-by: Morgan Funtowicz <morgan@huggingface.co> * Remove add_prefix_space from tokenize call in unittest. Signed-off-by: Morgan Funtowicz <morgan@huggingface.co> * Style and quality Signed-off-by: Morgan Funtowicz <morgan@huggingface.co> * Correct message for batch_encode_plus none input exception. Signed-off-by: Morgan Funtowicz <morgan@huggingface.co> * Fix invalid list comprehension for offset_mapping overriding content every iteration. Signed-off-by: Morgan Funtowicz <morgan@huggingface.co> * TransfoXL uses Strip normalizer. Signed-off-by: Morgan Funtowicz <morgan@huggingface.co> * Bump tokenizers dependency to 0.7.0rc3 Signed-off-by: Morgan Funtowicz <morgan@huggingface.co> * Support AddedTokens for special_tokens and use left stripping on mask for Roberta. Signed-off-by: Morgan Funtowicz <morgan@huggingface.co> * SpecilaTokenMixin can use slots to faster access to underlying attributes. Signed-off-by: Morgan Funtowicz <morgan@huggingface.co> * Remove update_special_tokens from fast tokenizers. * Ensure TransfoXL unittests are run only when torch is available. * Style. Signed-off-by: Morgan Funtowicz <morgan@huggingface.co> * Style * Style 🙏🙏 * Remove slots on SpecialTokensMixin, need deep dive into pickle protocol. * Remove Roberta warning on __init__. * Move documentation to Google style. Co-authored-by: LysandreJik <lysandre.debut@reseau.eseo.fr>
121 lines
4.3 KiB
Python
121 lines
4.3 KiB
Python
# coding=utf-8
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# Copyright 2018 The Google AI Language Team Authors.
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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.tokenization_gpt2 import VOCAB_FILES_NAMES, GPT2Tokenizer, GPT2TokenizerFast
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from .test_tokenization_common import TokenizerTesterMixin
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class GPT2TokenizationTest(TokenizerTesterMixin, unittest.TestCase):
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tokenizer_class = GPT2Tokenizer
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test_rust_tokenizer = True
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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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"\u0120",
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"\u0120l",
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"\u0120n",
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"\u0120lo",
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"\u0120low",
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"er",
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"\u0120lowest",
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"\u0120newer",
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"\u0120wider",
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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 = ["#version: 0.2", "\u0120 l", "\u0120l o", "\u0120lo w", "e r", ""]
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self.special_tokens_map = {"unk_token": "<unk>"}
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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", encoding="utf-8") as fp:
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fp.write(json.dumps(vocab_tokens) + "\n")
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with open(self.merges_file, "w", encoding="utf-8") as fp:
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fp.write("\n".join(merges))
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def get_tokenizer(self, **kwargs):
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kwargs.update(self.special_tokens_map)
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return GPT2Tokenizer.from_pretrained(self.tmpdirname, **kwargs)
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def get_rust_tokenizer(self, **kwargs):
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kwargs.update(self.special_tokens_map)
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return GPT2TokenizerFast.from_pretrained(self.tmpdirname, **kwargs)
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def get_input_output_texts(self):
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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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tokenizer = GPT2Tokenizer(self.vocab_file, self.merges_file, **self.special_tokens_map)
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text = "lower newer"
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bpe_tokens = ["\u0120low", "er", "\u0120", "n", "e", "w", "er"]
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tokens = tokenizer.tokenize(text, add_prefix_space=True)
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self.assertListEqual(tokens, bpe_tokens)
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input_tokens = tokens + [tokenizer.unk_token]
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input_bpe_tokens = [14, 15, 10, 9, 3, 2, 15, 19]
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self.assertListEqual(tokenizer.convert_tokens_to_ids(input_tokens), input_bpe_tokens)
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def test_rust_and_python_full_tokenizers(self):
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if not self.test_rust_tokenizer:
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return
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tokenizer = self.get_tokenizer()
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rust_tokenizer = self.get_rust_tokenizer(add_prefix_space=True)
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sequence = "lower newer"
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# Testing tokenization
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tokens = tokenizer.tokenize(sequence, add_prefix_space=True)
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rust_tokens = rust_tokenizer.tokenize(sequence)
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self.assertListEqual(tokens, rust_tokens)
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# Testing conversion to ids without special tokens
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ids = tokenizer.encode(sequence, add_special_tokens=False, add_prefix_space=True)
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rust_ids = rust_tokenizer.encode(sequence, add_special_tokens=False)
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self.assertListEqual(ids, rust_ids)
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# Testing conversion to ids with special tokens
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rust_tokenizer = self.get_rust_tokenizer(add_prefix_space=True)
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ids = tokenizer.encode(sequence, add_prefix_space=True)
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rust_ids = rust_tokenizer.encode(sequence)
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self.assertListEqual(ids, rust_ids)
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# Testing the unknown token
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input_tokens = tokens + [rust_tokenizer.unk_token]
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input_bpe_tokens = [14, 15, 10, 9, 3, 2, 15, 19]
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self.assertListEqual(rust_tokenizer.convert_tokens_to_ids(input_tokens), input_bpe_tokens)
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