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https://github.com/huggingface/transformers.git
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f4e04cd2c6
* Fixing roberta for slow-fast tests * WIP getting equivalence on pipelines * slow-to-fast equivalence - working on question-answering pipeline * optional FAISS tests * Pipeline Q&A * Move pipeline tests to their own test job again * update tokenizer to add sequence id methods * update to tokenizers 0.9.4 * set sentencepiecce as optional * clean up squad * clean up pipelines to use sequence_ids * style/quality * wording * Switch to use_fast = True by default * update tests for use_fast at True by default * fix rag tokenizer test * removing protobuf from required dependencies * fix NER test for use_fast = True by default * fixing example tests (Q&A examples use slow tokenizers for now) * protobuf in main deps extras["sentencepiece"] and example deps * fix protobug install test * try to fix seq2seq by switching to slow tokenizers for now * Update src/transformers/tokenization_utils_base.py Co-authored-by: Lysandre Debut <lysandre@huggingface.co> * Update src/transformers/tokenization_utils_base.py Co-authored-by: Lysandre Debut <lysandre@huggingface.co> Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
127 lines
4.1 KiB
Python
127 lines
4.1 KiB
Python
# coding=utf-8
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# Copyright 2020 The HuggingFace Inc. team, The Microsoft Research team.
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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 os
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import unittest
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from transformers.file_utils import cached_property
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from transformers.testing_utils import require_sentencepiece, slow
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from transformers.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
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from .test_tokenization_common import TokenizerTesterMixin
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SAMPLE_VOCAB = os.path.join(os.path.dirname(os.path.abspath(__file__)), "fixtures/test_sentencepiece.model")
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@require_sentencepiece
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class XLMProphetNetTokenizationTest(TokenizerTesterMixin, unittest.TestCase):
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tokenizer_class = XLMProphetNetTokenizer
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test_rust_tokenizer = False
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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 = XLMProphetNetTokenizer(SAMPLE_VOCAB, keep_accents=True)
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tokenizer.save_pretrained(self.tmpdirname)
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def test_full_tokenizer(self):
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tokenizer = XLMProphetNetTokenizer(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(
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tokenizer.convert_tokens_to_ids(tokens),
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[value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]],
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)
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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(
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ids,
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[
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value + tokenizer.fairseq_offset
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for value in [8, 21, 84, 55, 24, 19, 7, -9, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, -9, 4]
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],
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)
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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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@cached_property
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def big_tokenizer(self):
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return XLMProphetNetTokenizer.from_pretrained("microsoft/xprophetnet-large-wiki100-cased")
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@slow
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def test_tokenization_base_easy_symbols(self):
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symbols = "Hello World!"
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original_tokenizer_encodings = [35389, 6672, 49, 2]
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self.assertListEqual(original_tokenizer_encodings, self.big_tokenizer.encode(symbols))
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