import json import os import unittest from transformers.testing_utils import slow from transformers.tokenization_blenderbot import VOCAB_FILES_NAMES, BlenderbotTokenizer, BlenderbotSmallTokenizer from .test_tokenization_common import TokenizerTesterMixin class BlenderbotSmallTokenizerTest(TokenizerTesterMixin, unittest.TestCase): tokenizer_class = BlenderbotSmallTokenizer def setUp(self): super().setUp() # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt vocab = ["adapt", "react", "read@@", "ap@@", "t", "__unk__", "__start__", "__end__", "__null__"] vocab_tokens = dict(zip(vocab, range(len(vocab)))) merges = ["#version: 0.2", "a p", "ap t", "r e", "a d", "ad apt", ""] self.special_tokens_map = {"bos_token": "__start", "eos_token": "__end__", "pad_token": "__null__", "unk_token": "__unk__"} 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 BlenderbotSmallTokenizer.from_pretrained(self.tmpdirname, **kwargs) def get_input_output_texts(self, tokenizer): input_text = "adapt react readapt apt" output_text = "adapt react readapt apt" return input_text, output_text def test_full_blenderbot_small_tokenizer(self): tokenizer = BlenderbotSmallTokenizer(self.vocab_file, self.merges_file, **self.special_tokens_map) text = "adapt react readapt apt" bpe_tokens = ['adapt', 'react', 'read@@', 'ap@@', 't', 'ap@@', 't'] tokens = tokenizer.tokenize(text) self.assertListEqual(tokens, bpe_tokens) input_tokens = [tokenizer.bos_token] + tokens + [tokenizer.eos_token] print(input_tokens) # input_bpe_tokens = [0, 1, 2, 4, 5, 1, 0, 3, 6] # self.assertListEqual(tokenizer.convert_tokens_to_ids(input_tokens), input_bpe_tokens)