# coding=utf-8 # Copyright 2018 The Google AI Language Team Authors. # # 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 json import os import unittest from transformers.tokenization_gpt2 import VOCAB_FILES_NAMES, GPT2Tokenizer, GPT2TokenizerFast from .test_tokenization_common import TokenizerTesterMixin class GPT2TokenizationTest(TokenizerTesterMixin, unittest.TestCase): tokenizer_class = GPT2Tokenizer test_rust_tokenizer = True def setUp(self): super().setUp() # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt vocab = [ "l", "o", "w", "e", "r", "s", "t", "i", "d", "n", "\u0120", "\u0120l", "\u0120n", "\u0120lo", "\u0120low", "er", "\u0120lowest", "\u0120newer", "\u0120wider", "", ] vocab_tokens = dict(zip(vocab, range(len(vocab)))) merges = ["#version: 0.2", "\u0120 l", "\u0120l o", "\u0120lo w", "e r", ""] self.special_tokens_map = {"unk_token": ""} self.vocab_file = os.path.join(self.tmpdirname, VOCAB_FILES_NAMES["vocab_file"]) self.merges_file = os.path.join(self.tmpdirname, VOCAB_FILES_NAMES["merges_file"]) with open(self.vocab_file, "w", encoding="utf-8") as fp: fp.write(json.dumps(vocab_tokens) + "\n") with open(self.merges_file, "w", encoding="utf-8") as fp: fp.write("\n".join(merges)) def get_tokenizer(self, **kwargs): kwargs.update(self.special_tokens_map) return GPT2Tokenizer.from_pretrained(self.tmpdirname, **kwargs) def get_rust_tokenizer(self, **kwargs): kwargs.update(self.special_tokens_map) return GPT2TokenizerFast.from_pretrained(self.tmpdirname, **kwargs) def get_input_output_texts(self): input_text = "lower newer" output_text = "lower newer" return input_text, output_text def test_full_tokenizer(self): tokenizer = GPT2Tokenizer(self.vocab_file, self.merges_file, **self.special_tokens_map) text = "lower newer" bpe_tokens = ["\u0120low", "er", "\u0120", "n", "e", "w", "er"] tokens = tokenizer.tokenize(text, add_prefix_space=True) self.assertListEqual(tokens, bpe_tokens) input_tokens = tokens + [tokenizer.unk_token] input_bpe_tokens = [14, 15, 10, 9, 3, 2, 15, 19] self.assertListEqual(tokenizer.convert_tokens_to_ids(input_tokens), input_bpe_tokens) def test_rust_and_python_full_tokenizers(self): if not self.test_rust_tokenizer: return tokenizer = self.get_tokenizer() rust_tokenizer = self.get_rust_tokenizer(add_special_tokens=False, add_prefix_space=True) sequence = "lower newer" # Testing tokenization tokens = tokenizer.tokenize(sequence, add_prefix_space=True) rust_tokens = rust_tokenizer.tokenize(sequence) self.assertListEqual(tokens, rust_tokens) # Testing conversion to ids without special tokens ids = tokenizer.encode(sequence, add_special_tokens=False, add_prefix_space=True) rust_ids = rust_tokenizer.encode(sequence) self.assertListEqual(ids, rust_ids) # Testing conversion to ids with special tokens rust_tokenizer = self.get_rust_tokenizer(add_prefix_space=True) ids = tokenizer.encode(sequence, add_prefix_space=True) rust_ids = rust_tokenizer.encode(sequence) self.assertListEqual(ids, rust_ids) # Testing the unknown token input_tokens = tokens + [rust_tokenizer.unk_token] input_bpe_tokens = [14, 15, 10, 9, 3, 2, 15, 19] self.assertListEqual(rust_tokenizer.convert_tokens_to_ids(input_tokens), input_bpe_tokens)