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| # coding=utf-8 | |
| # Copyright 2020 HuggingFace Inc. team. | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| import os | |
| import unittest | |
| from transformers import FunnelTokenizer, FunnelTokenizerFast | |
| from transformers.models.funnel.tokenization_funnel import VOCAB_FILES_NAMES | |
| from transformers.testing_utils import require_tokenizers | |
| from ...test_tokenization_common import TokenizerTesterMixin | |
| class FunnelTokenizationTest(TokenizerTesterMixin, unittest.TestCase): | |
| tokenizer_class = FunnelTokenizer | |
| rust_tokenizer_class = FunnelTokenizerFast | |
| test_rust_tokenizer = True | |
| space_between_special_tokens = True | |
| def setUp(self): | |
| super().setUp() | |
| vocab_tokens = [ | |
| "<unk>", | |
| "<cls>", | |
| "<sep>", | |
| "want", | |
| "##want", | |
| "##ed", | |
| "wa", | |
| "un", | |
| "runn", | |
| "##ing", | |
| ",", | |
| "low", | |
| "lowest", | |
| ] | |
| self.vocab_file = os.path.join(self.tmpdirname, VOCAB_FILES_NAMES["vocab_file"]) | |
| with open(self.vocab_file, "w", encoding="utf-8") as vocab_writer: | |
| vocab_writer.write("".join([x + "\n" for x in vocab_tokens])) | |
| def get_tokenizer(self, **kwargs): | |
| return FunnelTokenizer.from_pretrained(self.tmpdirname, **kwargs) | |
| def get_rust_tokenizer(self, **kwargs): | |
| return FunnelTokenizerFast.from_pretrained(self.tmpdirname, **kwargs) | |
| def get_input_output_texts(self, tokenizer): | |
| input_text = "UNwant\u00E9d,running" | |
| output_text = "unwanted, running" | |
| return input_text, output_text | |
| def test_full_tokenizer(self): | |
| tokenizer = self.tokenizer_class(self.vocab_file) | |
| tokens = tokenizer.tokenize("UNwant\u00E9d,running") | |
| self.assertListEqual(tokens, ["un", "##want", "##ed", ",", "runn", "##ing"]) | |
| self.assertListEqual(tokenizer.convert_tokens_to_ids(tokens), [7, 4, 5, 10, 8, 9]) | |
| def test_token_type_ids(self): | |
| tokenizers = self.get_tokenizers(do_lower_case=False) | |
| for tokenizer in tokenizers: | |
| inputs = tokenizer("UNwant\u00E9d,running") | |
| sentence_len = len(inputs["input_ids"]) - 1 | |
| self.assertListEqual(inputs["token_type_ids"], [2] + [0] * sentence_len) | |
| inputs = tokenizer("UNwant\u00E9d,running", "UNwant\u00E9d,running") | |
| self.assertListEqual(inputs["token_type_ids"], [2] + [0] * sentence_len + [1] * sentence_len) | |