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* fix test for bart. Order is correct now let's skip BPEs * ouf * styling * fix bert.... * slow refactoring * current updates * massive refactoring * update * NICE! * update to see where I am at * updates * update * update * revert * updates * updates * start supporting legacy_save * styling * big update * revert some changes * nits * nniiiiiice * small fixes * kinda fix t5 with new behaviour * major update * fixup * fix copies * today's updates * fix byt5 * upfate * update * update * updates * update vocab size test * Barthez does not use not need the fairseq offset ids * super calll must be after * calll super * move all super init * move other super init * fixup * nits * more fixes * nits * more fixes * nits * more fix * remove useless files * ouch all of them are affected * and more! * small imporvements * no more sanitize token * more changes around unique no split tokens * partially fix more things * keep legacy save but add warning * so... more fixes * updates * guess deberta tokenizer could be nuked * fixup * fixup did some bad things * nuke it if it breaks * remove prints and pretrain fast from slow with new format. * fixups * Apply suggestions from code review Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * fiou * nit * by default specials should not be normalized? * update * remove brakpoint * updates * a lot of updates * fixup * fixes revert some changes to match fast * small nits * that makes it cleaner * fix camembert accordingly * update * some lest breaking changes * update * fixup * fix byt5 and whisper mostly * some more fixes, canine's byte vocab * fix gpt2 * fix most of the perceiver tests (4 left) * fix layout lmv3 * fixup * fix copies for gpt2 style * make sure to only warn once * fix perciever and gpt2 tests * some more backward compatibility: also read special tokens map because some ppl use it........////..... * fixup * add else when reading * nits * fresh updates * fix copies * will this make everything faster? * fixes * more fixes * update * more fixes * fixup * is the source of truth right? * sorry camembert for the troubles * current updates * fixup * update led * update * fix regression * fix single word * more model specific fixes * fix t5 tests * fixup * more comments * update * fix nllb * rstrip removed * small fixes * better handle additional_special_tokens and vocab sizes * fixing * styling * fix 4 / 21 * fixup * fix nlbb's tests * some fixes * fix t5 * fixes * style * fix canine tests * damn this is nice * nits * m2m100 nit * fixups * fixes! * fixup * stash * fix merge * revert bad change * fixup * correct order for code Llama * fix speecht5 post merge * styling * revert source of 11 fails * small nits * all changes in one go * fnet hack * fix 2 more tests * update based on main branch of tokenizers * fixup * fix VITS issues * more fixes * fix mgp test * fix camembert issues * oups camembert still has 2 failing tests * mluke fixes * decode fixes * small nits * nits * fix llama and vits * fix camembert * smal nits * more fixes when initialising a fast from a slow and etc * fix one of the last test * fix CPM tokenizer test * fixups * fix pop2piano * fixup * ⚠️ Change tokenizers required version ⚠️ * ⚠️ Change tokenizers required version ⚠️ * "tokenizers>=0.14,<0.15", don't forget smaller than * fix musicgen tests and pretraiendtokenizerfast * fix owlvit and all * update t5 * fix 800 red * fix tests * fix the fix of the fix of t5 * styling * documentation nits * cache _added_tokens_encoder * fixups * Nit * fix red tests * one last nit! * make eveything a lot simpler * Now it's over 😉 * few small nits * Apply suggestions from code review Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * updates that work for now * tests that should no be skipped / changed and fixed next * fixup * i am ashamed * pushe the fix * update * fixups * nits * fix added_tokens_encoder * fix canine test * fix pegasus vocab * fix transfoXL * fixup * whisper needs to be fixed for train new * pegasus nits * more pegasus fixes * minor update * better error message in failed test * fix whisper failing test * fix whisper failing test * fix pegasus * fixup * fix **** pegasus * reset things * remove another file * attempts to fix the strange custome encoder and offset * nits here and there * update * fixup * nit * fix the whisper test * nits nits * Apply suggestions from code review Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * updates based on review * some small update to potentially remove * nits * import rlu cache * Update src/transformers/tokenization_utils_base.py Co-authored-by: Lysandre Debut <hi@lysand.re> * move warning to `from_pretrained` * update tests results now that the special tokens are always added --------- Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> Co-authored-by: Lysandre Debut <hi@lysand.re>
211 lines
10 KiB
Python
211 lines
10 KiB
Python
# coding=utf-8
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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 transformers import SPIECE_UNDERLINE, XLNetTokenizer, XLNetTokenizerFast
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from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
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from ...test_tokenization_common import TokenizerTesterMixin
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SAMPLE_VOCAB = get_tests_dir("fixtures/test_sentencepiece.model")
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@require_sentencepiece
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@require_tokenizers
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class XLNetTokenizationTest(TokenizerTesterMixin, unittest.TestCase):
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tokenizer_class = XLNetTokenizer
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rust_tokenizer_class = XLNetTokenizerFast
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test_rust_tokenizer = True
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test_sentencepiece = True
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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 = XLNetTokenizer(SAMPLE_VOCAB, keep_accents=True)
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tokenizer.save_pretrained(self.tmpdirname)
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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 = "<s>"
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token_id = 1
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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], "<unk>")
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self.assertEqual(vocab_keys[1], "<s>")
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self.assertEqual(vocab_keys[-1], "<eod>")
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self.assertEqual(len(vocab_keys), 1_006)
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def test_vocab_size(self):
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self.assertEqual(self.get_tokenizer().vocab_size, 1_000)
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def test_full_tokenizer(self):
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tokenizer = XLNetTokenizer(SAMPLE_VOCAB, keep_accents=True)
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tokens = tokenizer.tokenize("This is a test")
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self.assertListEqual(tokens, ["▁This", "▁is", "▁a", "▁t", "est"])
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self.assertListEqual(tokenizer.convert_tokens_to_ids(tokens), [285, 46, 10, 170, 382])
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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,
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[
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SPIECE_UNDERLINE + "I",
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SPIECE_UNDERLINE + "was",
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SPIECE_UNDERLINE + "b",
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"or",
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"n",
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SPIECE_UNDERLINE + "in",
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SPIECE_UNDERLINE + "",
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"9",
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"2",
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"0",
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"0",
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"0",
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",",
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SPIECE_UNDERLINE + "and",
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SPIECE_UNDERLINE + "this",
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SPIECE_UNDERLINE + "is",
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SPIECE_UNDERLINE + "f",
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"al",
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"s",
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"é",
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".",
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],
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)
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ids = tokenizer.convert_tokens_to_ids(tokens)
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self.assertListEqual(ids, [8, 21, 84, 55, 24, 19, 7, 0, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 0, 4])
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back_tokens = tokenizer.convert_ids_to_tokens(ids)
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self.assertListEqual(
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back_tokens,
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[
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SPIECE_UNDERLINE + "I",
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SPIECE_UNDERLINE + "was",
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SPIECE_UNDERLINE + "b",
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"or",
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"n",
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SPIECE_UNDERLINE + "in",
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SPIECE_UNDERLINE + "",
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"<unk>",
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"2",
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"0",
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"0",
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"0",
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",",
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SPIECE_UNDERLINE + "and",
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SPIECE_UNDERLINE + "this",
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SPIECE_UNDERLINE + "is",
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SPIECE_UNDERLINE + "f",
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"al",
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"s",
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"<unk>",
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".",
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],
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)
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def test_tokenizer_lower(self):
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tokenizer = XLNetTokenizer(SAMPLE_VOCAB, do_lower_case=True)
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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,
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[
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SPIECE_UNDERLINE + "",
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"i",
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SPIECE_UNDERLINE + "was",
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SPIECE_UNDERLINE + "b",
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"or",
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"n",
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SPIECE_UNDERLINE + "in",
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SPIECE_UNDERLINE + "",
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"9",
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"2",
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"0",
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"0",
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"0",
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",",
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SPIECE_UNDERLINE + "and",
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SPIECE_UNDERLINE + "this",
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SPIECE_UNDERLINE + "is",
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SPIECE_UNDERLINE + "f",
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"al",
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"se",
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".",
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],
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)
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self.assertListEqual(tokenizer.tokenize("H\u00E9llo"), ["▁he", "ll", "o"])
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def test_tokenizer_no_lower(self):
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tokenizer = XLNetTokenizer(SAMPLE_VOCAB, do_lower_case=False)
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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,
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[
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SPIECE_UNDERLINE + "I",
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SPIECE_UNDERLINE + "was",
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SPIECE_UNDERLINE + "b",
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"or",
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"n",
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SPIECE_UNDERLINE + "in",
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SPIECE_UNDERLINE + "",
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"9",
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"2",
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"0",
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"0",
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"0",
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",",
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SPIECE_UNDERLINE + "and",
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SPIECE_UNDERLINE + "this",
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SPIECE_UNDERLINE + "is",
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SPIECE_UNDERLINE + "f",
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"al",
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"se",
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".",
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],
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)
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@slow
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def test_sequence_builders(self):
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tokenizer = XLNetTokenizer.from_pretrained("xlnet-base-cased")
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text = tokenizer.encode("sequence builders", add_special_tokens=False)
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text_2 = tokenizer.encode("multi-sequence build", add_special_tokens=False)
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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 == text + [4, 3]
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assert encoded_pair == text + [4] + text_2 + [4, 3]
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@slow
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def test_tokenizer_integration(self):
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# fmt: off
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expected_encoding = {'input_ids': [[17, 21442, 270, 17, 10, 14645, 318, 34, 17, 4546, 3145, 787, 13, 7752, 22018, 23, 21, 17, 4546, 3145, 787, 13, 3352, 14431, 13, 5500, 11, 1176, 580, 13, 16819, 4797, 23, 17, 10, 17135, 658, 19, 457, 7932, 13, 184, 19, 3154, 17135, 6468, 19, 1404, 12269, 19, 4229, 5356, 16264, 46, 19, 17, 20545, 10395, 9, 9, 9, 11, 28, 6421, 9531, 20729, 17, 10, 353, 17022, 11, 21, 6421, 9531, 16949, 17, 10, 11509, 753, 11, 33, 95, 2421, 7385, 956, 14431, 2626, 25, 842, 7385, 4836, 21, 1429, 2272, 9855, 3120, 161, 24738, 19, 13203, 658, 218, 787, 21, 430, 18482, 847, 2637, 9, 4, 3], [5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 322, 22178, 27, 1064, 22, 956, 13, 11101, 1429, 5854, 24313, 18953, 40, 422, 24366, 68, 1758, 37, 10483, 14257, 31, 207, 263, 21, 203, 3773, 25, 71, 9735, 9, 4, 3], [5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 32, 2049, 3442, 17, 13894, 3380, 23, 95, 18, 17634, 2288, 9, 4, 3]], 'token_type_ids': [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2], [3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2], [3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2]], 'attention_mask': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]} # noqa: E501
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# fmt: on
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self.tokenizer_integration_test_util(
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expected_encoding=expected_encoding,
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model_name="xlnet-base-cased",
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revision="c841166438c31ec7ca9a106dee7bb312b73ae511",
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)
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