# coding=utf-8 # Copyright 2020 The HuggingFace Team. All rights reserved. # # 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 BigBirdTokenizer, BigBirdTokenizerFast from transformers.file_utils import cached_property from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow from .test_tokenization_common import TokenizerTesterMixin SPIECE_UNDERLINE = "▁" SAMPLE_VOCAB = os.path.join(os.path.dirname(os.path.abspath(__file__)), "fixtures/test_sentencepiece.model") @require_sentencepiece @require_tokenizers class BigBirdTokenizationTest(TokenizerTesterMixin, unittest.TestCase): tokenizer_class = BigBirdTokenizer rust_tokenizer_class = BigBirdTokenizerFast test_rust_tokenizer = True def setUp(self): super().setUp() tokenizer = BigBirdTokenizer(SAMPLE_VOCAB, keep_accents=True) tokenizer.save_pretrained(self.tmpdirname) 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() sequence = "I was born in 92000, and this is falsé." tokens = tokenizer.tokenize(sequence) rust_tokens = rust_tokenizer.tokenize(sequence) self.assertListEqual(tokens, rust_tokens) ids = tokenizer.encode(sequence, add_special_tokens=False) rust_ids = rust_tokenizer.encode(sequence, add_special_tokens=False) self.assertListEqual(ids, rust_ids) rust_tokenizer = self.get_rust_tokenizer() ids = tokenizer.encode(sequence) rust_ids = rust_tokenizer.encode(sequence) self.assertListEqual(ids, rust_ids) def test_full_tokenizer(self): tokenizer = BigBirdTokenizer(SAMPLE_VOCAB, keep_accents=True) tokens = tokenizer.tokenize("This is a test") self.assertListEqual(tokens, ["▁This", "▁is", "▁a", "▁t", "est"]) self.assertListEqual( tokenizer.convert_tokens_to_ids(tokens), [285, 46, 10, 170, 382], ) tokens = tokenizer.tokenize("I was born in 92000, and this is falsé.") self.assertListEqual( tokens, [ SPIECE_UNDERLINE + "I", SPIECE_UNDERLINE + "was", SPIECE_UNDERLINE + "b", "or", "n", SPIECE_UNDERLINE + "in", SPIECE_UNDERLINE + "", "9", "2", "0", "0", "0", ",", SPIECE_UNDERLINE + "and", SPIECE_UNDERLINE + "this", SPIECE_UNDERLINE + "is", SPIECE_UNDERLINE + "f", "al", "s", "é", ".", ], ) ids = tokenizer.convert_tokens_to_ids(tokens) self.assertListEqual( ids, [8, 21, 84, 55, 24, 19, 7, 0, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 0, 4], ) back_tokens = tokenizer.convert_ids_to_tokens(ids) self.assertListEqual( back_tokens, [ SPIECE_UNDERLINE + "I", SPIECE_UNDERLINE + "was", SPIECE_UNDERLINE + "b", "or", "n", SPIECE_UNDERLINE + "in", SPIECE_UNDERLINE + "", "", "2", "0", "0", "0", ",", SPIECE_UNDERLINE + "and", SPIECE_UNDERLINE + "this", SPIECE_UNDERLINE + "is", SPIECE_UNDERLINE + "f", "al", "s", "", ".", ], ) @cached_property def big_tokenizer(self): return BigBirdTokenizer.from_pretrained("google/bigbird-roberta-base") @slow def test_tokenization_base_easy_symbols(self): symbols = "Hello World!" original_tokenizer_encodings = [65, 18536, 2260, 101, 66] self.assertListEqual(original_tokenizer_encodings, self.big_tokenizer.encode(symbols)) @slow def test_tokenization_base_hard_symbols(self): symbols = 'This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) " [ ] ! : - . Also we will add words that should not exsist and be tokenized to , such as saoneuhaoesuth' # fmt: off original_tokenizer_encodings = [65, 871, 419, 358, 946, 991, 2521, 452, 358, 1357, 387, 7751, 3536, 112, 985, 456, 126, 865, 938, 5400, 5734, 458, 1368, 467, 786, 2462, 5246, 1159, 633, 865, 4519, 457, 582, 852, 2557, 427, 916, 508, 405, 34324, 497, 391, 408, 11342, 1244, 385, 100, 938, 985, 456, 574, 362, 12597, 3200, 3129, 1172, 66] # noqa: E231 # fmt: on self.assertListEqual(original_tokenizer_encodings, self.big_tokenizer.encode(symbols)) @require_torch @slow def test_torch_encode_plus_sent_to_model(self): import torch from transformers import BigBirdConfig, BigBirdModel # Build sequence first_ten_tokens = list(self.big_tokenizer.get_vocab().keys())[:10] sequence = " ".join(first_ten_tokens) encoded_sequence = self.big_tokenizer.encode_plus(sequence, return_tensors="pt", return_token_type_ids=False) batch_encoded_sequence = self.big_tokenizer.batch_encode_plus( [sequence + " " + sequence], return_tensors="pt", return_token_type_ids=False ) config = BigBirdConfig(attention_type="original_full") model = BigBirdModel(config) assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size with torch.no_grad(): model(**encoded_sequence) model(**batch_encoded_sequence) @slow def test_special_tokens(self): """ To reproduce: $ wget https://github.com/google-research/bigbird/blob/master/bigbird/vocab/gpt2.model?raw=true $ mv gpt2.model?raw=true gpt2.model ``` import tensorflow_text as tft import tensorflow as tf vocab_model_file = "./gpt2.model" tokenizer = tft.SentencepieceTokenizer(model=tf.io.gfile.GFile(vocab_model_file, "rb").read())) ids = tokenizer.tokenize("Paris is the [MASK].") ids = tf.concat([tf.constant([65]), ids, tf.constant([66])], axis=0) detokenized = tokenizer.detokenize(ids) # should give [CLS] Paris is the [MASK].[SEP] """ tokenizer = BigBirdTokenizer.from_pretrained("google/bigbird-roberta-base") decoded_text = tokenizer.decode(tokenizer("Paris is the [MASK].").input_ids) self.assertTrue(decoded_text == "[CLS] Paris is the [MASK].[SEP]")