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transformers/tests/models/auto/test_tokenization_auto.py
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524
transformers/tests/models/auto/test_tokenization_auto.py
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# Copyright 2020 The HuggingFace Team. All rights reserved.
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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 json
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import os
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import shutil
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import sys
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import tempfile
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import unittest
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from pathlib import Path
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import pytest
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import transformers
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from transformers import (
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AutoTokenizer,
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BertConfig,
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BertTokenizer,
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BertTokenizerFast,
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CTRLTokenizer,
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GPT2Tokenizer,
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GPT2TokenizerFast,
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PreTrainedTokenizerFast,
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RobertaTokenizer,
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RobertaTokenizerFast,
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is_tokenizers_available,
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)
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from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
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from transformers.models.auto.tokenization_auto import (
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TOKENIZER_MAPPING,
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get_tokenizer_config,
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tokenizer_class_from_name,
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)
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from transformers.models.roberta.configuration_roberta import RobertaConfig
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from transformers.testing_utils import (
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DUMMY_DIFF_TOKENIZER_IDENTIFIER,
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DUMMY_UNKNOWN_IDENTIFIER,
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SMALL_MODEL_IDENTIFIER,
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RequestCounter,
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is_flaky,
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require_tokenizers,
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slow,
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)
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sys.path.append(str(Path(__file__).parent.parent.parent.parent / "utils"))
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from test_module.custom_configuration import CustomConfig # noqa E402
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from test_module.custom_tokenization import CustomTokenizer # noqa E402
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if is_tokenizers_available():
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from test_module.custom_tokenization_fast import CustomTokenizerFast
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class AutoTokenizerTest(unittest.TestCase):
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def setUp(self):
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transformers.dynamic_module_utils.TIME_OUT_REMOTE_CODE = 0
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@slow
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def test_tokenizer_from_pretrained(self):
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for model_name in ("google-bert/bert-base-uncased", "google-bert/bert-base-cased"):
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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self.assertIsNotNone(tokenizer)
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self.assertIsInstance(tokenizer, (BertTokenizer, BertTokenizerFast))
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self.assertGreater(len(tokenizer), 0)
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for model_name in ["openai-community/gpt2", "openai-community/gpt2-medium"]:
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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self.assertIsNotNone(tokenizer)
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self.assertIsInstance(tokenizer, (GPT2Tokenizer, GPT2TokenizerFast))
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self.assertGreater(len(tokenizer), 0)
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def test_tokenizer_from_pretrained_identifier(self):
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tokenizer = AutoTokenizer.from_pretrained(SMALL_MODEL_IDENTIFIER)
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self.assertIsInstance(tokenizer, (BertTokenizer, BertTokenizerFast))
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self.assertEqual(tokenizer.vocab_size, 12)
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def test_tokenizer_from_model_type(self):
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tokenizer = AutoTokenizer.from_pretrained(DUMMY_UNKNOWN_IDENTIFIER)
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self.assertIsInstance(tokenizer, (RobertaTokenizer, RobertaTokenizerFast))
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self.assertEqual(tokenizer.vocab_size, 20)
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def test_tokenizer_from_tokenizer_class(self):
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config = AutoConfig.from_pretrained(DUMMY_DIFF_TOKENIZER_IDENTIFIER)
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self.assertIsInstance(config, RobertaConfig)
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# Check that tokenizer_type ≠ model_type
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tokenizer = AutoTokenizer.from_pretrained(DUMMY_DIFF_TOKENIZER_IDENTIFIER, config=config)
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self.assertIsInstance(tokenizer, (BertTokenizer, BertTokenizerFast))
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self.assertEqual(tokenizer.vocab_size, 12)
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def test_tokenizer_from_type(self):
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with tempfile.TemporaryDirectory() as tmp_dir:
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shutil.copy("./tests/fixtures/vocab.txt", os.path.join(tmp_dir, "vocab.txt"))
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tokenizer = AutoTokenizer.from_pretrained(tmp_dir, tokenizer_type="bert", use_fast=False)
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self.assertIsInstance(tokenizer, BertTokenizer)
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with tempfile.TemporaryDirectory() as tmp_dir:
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shutil.copy("./tests/fixtures/vocab.json", os.path.join(tmp_dir, "vocab.json"))
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shutil.copy("./tests/fixtures/merges.txt", os.path.join(tmp_dir, "merges.txt"))
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tokenizer = AutoTokenizer.from_pretrained(tmp_dir, tokenizer_type="gpt2", use_fast=False)
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self.assertIsInstance(tokenizer, GPT2Tokenizer)
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@require_tokenizers
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def test_tokenizer_from_type_fast(self):
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with tempfile.TemporaryDirectory() as tmp_dir:
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shutil.copy("./tests/fixtures/vocab.txt", os.path.join(tmp_dir, "vocab.txt"))
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tokenizer = AutoTokenizer.from_pretrained(tmp_dir, tokenizer_type="bert")
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self.assertIsInstance(tokenizer, BertTokenizerFast)
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with tempfile.TemporaryDirectory() as tmp_dir:
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shutil.copy("./tests/fixtures/vocab.json", os.path.join(tmp_dir, "vocab.json"))
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shutil.copy("./tests/fixtures/merges.txt", os.path.join(tmp_dir, "merges.txt"))
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tokenizer = AutoTokenizer.from_pretrained(tmp_dir, tokenizer_type="gpt2")
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self.assertIsInstance(tokenizer, GPT2TokenizerFast)
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def test_tokenizer_from_type_incorrect_name(self):
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with pytest.raises(ValueError):
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AutoTokenizer.from_pretrained("./", tokenizer_type="xxx")
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@require_tokenizers
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def test_tokenizer_identifier_with_correct_config(self):
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for tokenizer_class in [BertTokenizer, BertTokenizerFast, AutoTokenizer]:
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tokenizer = tokenizer_class.from_pretrained("wietsedv/bert-base-dutch-cased")
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self.assertIsInstance(tokenizer, (BertTokenizer, BertTokenizerFast))
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if isinstance(tokenizer, BertTokenizer):
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self.assertEqual(tokenizer.basic_tokenizer.do_lower_case, False)
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else:
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self.assertEqual(tokenizer.do_lower_case, False)
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self.assertEqual(tokenizer.model_max_length, 512)
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@require_tokenizers
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@is_flaky() # This one is flaky even with the new retry logic because it raises an unusual error
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def test_tokenizer_identifier_non_existent(self):
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for tokenizer_class in [BertTokenizer, BertTokenizerFast, AutoTokenizer]:
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with self.assertRaisesRegex(
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EnvironmentError,
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"julien-c/herlolip-not-exists is not a local folder and is not a valid model identifier",
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):
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_ = tokenizer_class.from_pretrained("julien-c/herlolip-not-exists")
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def test_model_name_edge_cases_in_mappings(self):
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# tests: https://github.com/huggingface/transformers/pull/13251
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# 1. models with `-`, e.g. xlm-roberta -> xlm_roberta
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# 2. models that don't remap 1-1 from model-name to model file, e.g., openai-gpt -> openai
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tokenizers = TOKENIZER_MAPPING.values()
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tokenizer_names = []
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for slow_tok, fast_tok in tokenizers:
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if slow_tok is not None:
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tokenizer_names.append(slow_tok.__name__)
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if fast_tok is not None:
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tokenizer_names.append(fast_tok.__name__)
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for tokenizer_name in tokenizer_names:
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# must find the right class
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tokenizer_class_from_name(tokenizer_name)
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@require_tokenizers
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def test_from_pretrained_use_fast_toggle(self):
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self.assertIsInstance(
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AutoTokenizer.from_pretrained("google-bert/bert-base-cased", use_fast=False), BertTokenizer
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)
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self.assertIsInstance(AutoTokenizer.from_pretrained("google-bert/bert-base-cased"), BertTokenizerFast)
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@require_tokenizers
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def test_do_lower_case(self):
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tokenizer = AutoTokenizer.from_pretrained("distilbert/distilbert-base-uncased", do_lower_case=False)
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sample = "Hello, world. How are you?"
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tokens = tokenizer.tokenize(sample)
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self.assertEqual("[UNK]", tokens[0])
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tokenizer = AutoTokenizer.from_pretrained("microsoft/mpnet-base", do_lower_case=False)
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tokens = tokenizer.tokenize(sample)
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self.assertEqual("[UNK]", tokens[0])
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@require_tokenizers
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def test_PreTrainedTokenizerFast_from_pretrained(self):
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tokenizer = AutoTokenizer.from_pretrained("robot-test/dummy-tokenizer-fast-with-model-config")
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self.assertEqual(type(tokenizer), PreTrainedTokenizerFast)
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self.assertEqual(tokenizer.model_max_length, 512)
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self.assertEqual(tokenizer.vocab_size, 30000)
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self.assertEqual(tokenizer.unk_token, "[UNK]")
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self.assertEqual(tokenizer.padding_side, "right")
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self.assertEqual(tokenizer.truncation_side, "right")
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def test_auto_tokenizer_from_local_folder(self):
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tokenizer = AutoTokenizer.from_pretrained(SMALL_MODEL_IDENTIFIER)
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self.assertIsInstance(tokenizer, (BertTokenizer, BertTokenizerFast))
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with tempfile.TemporaryDirectory() as tmp_dir:
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tokenizer.save_pretrained(tmp_dir)
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tokenizer2 = AutoTokenizer.from_pretrained(tmp_dir)
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self.assertIsInstance(tokenizer2, tokenizer.__class__)
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self.assertEqual(tokenizer2.vocab_size, 12)
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def test_auto_tokenizer_fast_no_slow(self):
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tokenizer = AutoTokenizer.from_pretrained("Salesforce/ctrl")
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# There is no fast CTRL so this always gives us a slow tokenizer.
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self.assertIsInstance(tokenizer, CTRLTokenizer)
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def test_get_tokenizer_config(self):
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# Check we can load the tokenizer config of an online model.
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config = get_tokenizer_config("google-bert/bert-base-cased")
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_ = config.pop("_commit_hash", None)
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# If we ever update google-bert/bert-base-cased tokenizer config, this dict here will need to be updated.
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self.assertEqual(config, {"do_lower_case": False, "model_max_length": 512})
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# This model does not have a tokenizer_config so we get back an empty dict.
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config = get_tokenizer_config(SMALL_MODEL_IDENTIFIER)
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self.assertDictEqual(config, {})
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# A tokenizer saved with `save_pretrained` always creates a tokenizer config.
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tokenizer = AutoTokenizer.from_pretrained(SMALL_MODEL_IDENTIFIER)
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with tempfile.TemporaryDirectory() as tmp_dir:
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tokenizer.save_pretrained(tmp_dir)
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config = get_tokenizer_config(tmp_dir)
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# Check the class of the tokenizer was properly saved (note that it always saves the slow class).
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self.assertEqual(config["tokenizer_class"], "BertTokenizer")
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def test_new_tokenizer_registration(self):
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try:
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AutoConfig.register("custom", CustomConfig)
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AutoTokenizer.register(CustomConfig, slow_tokenizer_class=CustomTokenizer)
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# Trying to register something existing in the Transformers library will raise an error
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with self.assertRaises(ValueError):
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AutoTokenizer.register(BertConfig, slow_tokenizer_class=BertTokenizer)
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tokenizer = CustomTokenizer.from_pretrained(SMALL_MODEL_IDENTIFIER)
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with tempfile.TemporaryDirectory() as tmp_dir:
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tokenizer.save_pretrained(tmp_dir)
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new_tokenizer = AutoTokenizer.from_pretrained(tmp_dir)
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self.assertIsInstance(new_tokenizer, CustomTokenizer)
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finally:
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if "custom" in CONFIG_MAPPING._extra_content:
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del CONFIG_MAPPING._extra_content["custom"]
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if CustomConfig in TOKENIZER_MAPPING._extra_content:
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del TOKENIZER_MAPPING._extra_content[CustomConfig]
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@require_tokenizers
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def test_new_tokenizer_fast_registration(self):
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try:
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AutoConfig.register("custom", CustomConfig)
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# Can register in two steps
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AutoTokenizer.register(CustomConfig, slow_tokenizer_class=CustomTokenizer)
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self.assertEqual(TOKENIZER_MAPPING[CustomConfig], (CustomTokenizer, None))
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AutoTokenizer.register(CustomConfig, fast_tokenizer_class=CustomTokenizerFast)
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self.assertEqual(TOKENIZER_MAPPING[CustomConfig], (CustomTokenizer, CustomTokenizerFast))
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del TOKENIZER_MAPPING._extra_content[CustomConfig]
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# Can register in one step
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AutoTokenizer.register(
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CustomConfig, slow_tokenizer_class=CustomTokenizer, fast_tokenizer_class=CustomTokenizerFast
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)
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self.assertEqual(TOKENIZER_MAPPING[CustomConfig], (CustomTokenizer, CustomTokenizerFast))
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# Trying to register something existing in the Transformers library will raise an error
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with self.assertRaises(ValueError):
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AutoTokenizer.register(BertConfig, fast_tokenizer_class=BertTokenizerFast)
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# We pass through a bert tokenizer fast cause there is no converter slow to fast for our new toknizer
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# and that model does not have a tokenizer.json
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with tempfile.TemporaryDirectory() as tmp_dir:
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bert_tokenizer = BertTokenizerFast.from_pretrained(SMALL_MODEL_IDENTIFIER)
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bert_tokenizer.save_pretrained(tmp_dir)
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tokenizer = CustomTokenizerFast.from_pretrained(tmp_dir)
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with tempfile.TemporaryDirectory() as tmp_dir:
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tokenizer.save_pretrained(tmp_dir)
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new_tokenizer = AutoTokenizer.from_pretrained(tmp_dir)
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self.assertIsInstance(new_tokenizer, CustomTokenizerFast)
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new_tokenizer = AutoTokenizer.from_pretrained(tmp_dir, use_fast=False)
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self.assertIsInstance(new_tokenizer, CustomTokenizer)
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finally:
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if "custom" in CONFIG_MAPPING._extra_content:
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del CONFIG_MAPPING._extra_content["custom"]
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if CustomConfig in TOKENIZER_MAPPING._extra_content:
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del TOKENIZER_MAPPING._extra_content[CustomConfig]
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def test_from_pretrained_dynamic_tokenizer(self):
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# If remote code is not set, we will time out when asking whether to load the model.
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with self.assertRaises(ValueError):
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tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/test_dynamic_tokenizer")
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# If remote code is disabled, we can't load this config.
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with self.assertRaises(ValueError):
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tokenizer = AutoTokenizer.from_pretrained(
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"hf-internal-testing/test_dynamic_tokenizer", trust_remote_code=False
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)
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tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/test_dynamic_tokenizer", trust_remote_code=True)
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self.assertTrue(tokenizer.special_attribute_present)
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# Test the dynamic module is loaded only once.
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reloaded_tokenizer = AutoTokenizer.from_pretrained(
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"hf-internal-testing/test_dynamic_tokenizer", trust_remote_code=True
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)
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self.assertIs(tokenizer.__class__, reloaded_tokenizer.__class__)
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# Test tokenizer can be reloaded.
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with tempfile.TemporaryDirectory() as tmp_dir:
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tokenizer.save_pretrained(tmp_dir)
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reloaded_tokenizer = AutoTokenizer.from_pretrained(tmp_dir, trust_remote_code=True)
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self.assertTrue(reloaded_tokenizer.special_attribute_present)
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if is_tokenizers_available():
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self.assertEqual(tokenizer.__class__.__name__, "NewTokenizerFast")
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self.assertEqual(reloaded_tokenizer.__class__.__name__, "NewTokenizerFast")
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# Test we can also load the slow version
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tokenizer = AutoTokenizer.from_pretrained(
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"hf-internal-testing/test_dynamic_tokenizer", trust_remote_code=True, use_fast=False
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)
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self.assertTrue(tokenizer.special_attribute_present)
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self.assertEqual(tokenizer.__class__.__name__, "NewTokenizer")
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# Test tokenizer can be reloaded.
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with tempfile.TemporaryDirectory() as tmp_dir:
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tokenizer.save_pretrained(tmp_dir)
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reloaded_tokenizer = AutoTokenizer.from_pretrained(tmp_dir, trust_remote_code=True, use_fast=False)
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self.assertTrue(
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os.path.exists(os.path.join(tmp_dir, "tokenization.py"))
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) # Assert we saved tokenizer code
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self.assertEqual(reloaded_tokenizer._auto_class, "AutoTokenizer")
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with open(os.path.join(tmp_dir, "tokenizer_config.json"), "r") as f:
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tokenizer_config = json.load(f)
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# Assert we're pointing at local code and not another remote repo
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self.assertEqual(tokenizer_config["auto_map"]["AutoTokenizer"], ["tokenization.NewTokenizer", None])
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self.assertEqual(reloaded_tokenizer.__class__.__name__, "NewTokenizer")
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self.assertTrue(reloaded_tokenizer.special_attribute_present)
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else:
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self.assertEqual(tokenizer.__class__.__name__, "NewTokenizer")
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self.assertEqual(reloaded_tokenizer.__class__.__name__, "NewTokenizer")
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# Test the dynamic module is reloaded if we force it.
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reloaded_tokenizer = AutoTokenizer.from_pretrained(
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"hf-internal-testing/test_dynamic_tokenizer", trust_remote_code=True, force_download=True
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)
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self.assertIsNot(tokenizer.__class__, reloaded_tokenizer.__class__)
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self.assertTrue(reloaded_tokenizer.special_attribute_present)
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@require_tokenizers
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def test_from_pretrained_dynamic_tokenizer_conflict(self):
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class NewTokenizer(BertTokenizer):
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special_attribute_present = False
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class NewTokenizerFast(BertTokenizerFast):
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slow_tokenizer_class = NewTokenizer
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special_attribute_present = False
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||||
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try:
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AutoConfig.register("custom", CustomConfig)
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AutoTokenizer.register(CustomConfig, slow_tokenizer_class=NewTokenizer)
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AutoTokenizer.register(CustomConfig, fast_tokenizer_class=NewTokenizerFast)
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# If remote code is not set, the default is to use local
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tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/test_dynamic_tokenizer")
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self.assertEqual(tokenizer.__class__.__name__, "NewTokenizerFast")
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self.assertFalse(tokenizer.special_attribute_present)
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tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/test_dynamic_tokenizer", use_fast=False)
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self.assertEqual(tokenizer.__class__.__name__, "NewTokenizer")
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self.assertFalse(tokenizer.special_attribute_present)
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# If remote code is disabled, we load the local one.
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||||
tokenizer = AutoTokenizer.from_pretrained(
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"hf-internal-testing/test_dynamic_tokenizer", trust_remote_code=False
|
||||
)
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||||
self.assertEqual(tokenizer.__class__.__name__, "NewTokenizerFast")
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||||
self.assertFalse(tokenizer.special_attribute_present)
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||||
tokenizer = AutoTokenizer.from_pretrained(
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||||
"hf-internal-testing/test_dynamic_tokenizer", trust_remote_code=False, use_fast=False
|
||||
)
|
||||
self.assertEqual(tokenizer.__class__.__name__, "NewTokenizer")
|
||||
self.assertFalse(tokenizer.special_attribute_present)
|
||||
|
||||
# If remote is enabled, we load from the Hub
|
||||
tokenizer = AutoTokenizer.from_pretrained(
|
||||
"hf-internal-testing/test_dynamic_tokenizer", trust_remote_code=True
|
||||
)
|
||||
self.assertEqual(tokenizer.__class__.__name__, "NewTokenizerFast")
|
||||
self.assertTrue(tokenizer.special_attribute_present)
|
||||
tokenizer = AutoTokenizer.from_pretrained(
|
||||
"hf-internal-testing/test_dynamic_tokenizer", trust_remote_code=True, use_fast=False
|
||||
)
|
||||
self.assertEqual(tokenizer.__class__.__name__, "NewTokenizer")
|
||||
self.assertTrue(tokenizer.special_attribute_present)
|
||||
|
||||
finally:
|
||||
if "custom" in CONFIG_MAPPING._extra_content:
|
||||
del CONFIG_MAPPING._extra_content["custom"]
|
||||
if CustomConfig in TOKENIZER_MAPPING._extra_content:
|
||||
del TOKENIZER_MAPPING._extra_content[CustomConfig]
|
||||
|
||||
def test_from_pretrained_dynamic_tokenizer_legacy_format(self):
|
||||
tokenizer = AutoTokenizer.from_pretrained(
|
||||
"hf-internal-testing/test_dynamic_tokenizer_legacy", trust_remote_code=True
|
||||
)
|
||||
self.assertTrue(tokenizer.special_attribute_present)
|
||||
if is_tokenizers_available():
|
||||
self.assertEqual(tokenizer.__class__.__name__, "NewTokenizerFast")
|
||||
|
||||
# Test we can also load the slow version
|
||||
tokenizer = AutoTokenizer.from_pretrained(
|
||||
"hf-internal-testing/test_dynamic_tokenizer_legacy", trust_remote_code=True, use_fast=False
|
||||
)
|
||||
self.assertTrue(tokenizer.special_attribute_present)
|
||||
self.assertEqual(tokenizer.__class__.__name__, "NewTokenizer")
|
||||
else:
|
||||
self.assertEqual(tokenizer.__class__.__name__, "NewTokenizer")
|
||||
|
||||
def test_repo_not_found(self):
|
||||
with self.assertRaisesRegex(
|
||||
EnvironmentError, "bert-base is not a local folder and is not a valid model identifier"
|
||||
):
|
||||
_ = AutoTokenizer.from_pretrained("bert-base")
|
||||
|
||||
def test_revision_not_found(self):
|
||||
with self.assertRaisesRegex(
|
||||
EnvironmentError, r"aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)"
|
||||
):
|
||||
_ = AutoTokenizer.from_pretrained(DUMMY_UNKNOWN_IDENTIFIER, revision="aaaaaa")
|
||||
|
||||
@unittest.skip("This test is failing on main") # TODO Matt/ydshieh, fix this test!
|
||||
def test_cached_tokenizer_has_minimum_calls_to_head(self):
|
||||
# Make sure we have cached the tokenizer.
|
||||
_ = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-bert")
|
||||
with RequestCounter() as counter:
|
||||
_ = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-bert")
|
||||
self.assertEqual(counter["GET"], 0)
|
||||
self.assertEqual(counter["HEAD"], 1)
|
||||
self.assertEqual(counter.total_calls, 1)
|
||||
|
||||
def test_init_tokenizer_with_trust(self):
|
||||
nop_tokenizer_code = """
|
||||
import transformers
|
||||
|
||||
class NopTokenizer(transformers.PreTrainedTokenizer):
|
||||
def get_vocab(self):
|
||||
return {}
|
||||
"""
|
||||
|
||||
nop_config_code = """
|
||||
from transformers import PretrainedConfig
|
||||
|
||||
class NopConfig(PretrainedConfig):
|
||||
model_type = "test_unregistered_dynamic"
|
||||
|
||||
def __init__(self, **kwargs):
|
||||
super().__init__(**kwargs)
|
||||
"""
|
||||
|
||||
with tempfile.TemporaryDirectory() as tmp_dir:
|
||||
fake_model_id = "hf-internal-testing/test_unregistered_dynamic"
|
||||
fake_repo = os.path.join(tmp_dir, fake_model_id)
|
||||
os.makedirs(fake_repo)
|
||||
|
||||
tokenizer_src_file = os.path.join(fake_repo, "tokenizer.py")
|
||||
with open(tokenizer_src_file, "w") as wfp:
|
||||
wfp.write(nop_tokenizer_code)
|
||||
|
||||
model_config_src_file = os.path.join(fake_repo, "config.py")
|
||||
with open(model_config_src_file, "w") as wfp:
|
||||
wfp.write(nop_config_code)
|
||||
|
||||
config = {
|
||||
"model_type": "test_unregistered_dynamic",
|
||||
"auto_map": {"AutoConfig": f"{fake_model_id}--config.NopConfig"},
|
||||
}
|
||||
|
||||
config_file = os.path.join(fake_repo, "config.json")
|
||||
with open(config_file, "w") as wfp:
|
||||
json.dump(config, wfp, indent=2)
|
||||
|
||||
tokenizer_config = {
|
||||
"auto_map": {
|
||||
"AutoTokenizer": [
|
||||
f"{fake_model_id}--tokenizer.NopTokenizer",
|
||||
None,
|
||||
]
|
||||
}
|
||||
}
|
||||
|
||||
tokenizer_config_file = os.path.join(fake_repo, "tokenizer_config.json")
|
||||
with open(tokenizer_config_file, "w") as wfp:
|
||||
json.dump(tokenizer_config, wfp, indent=2)
|
||||
|
||||
prev_dir = os.getcwd()
|
||||
try:
|
||||
# it looks like subdir= is broken in the from_pretrained also, so this is necessary
|
||||
os.chdir(tmp_dir)
|
||||
|
||||
# this should work because we trust the code
|
||||
_ = AutoTokenizer.from_pretrained(fake_model_id, local_files_only=True, trust_remote_code=True)
|
||||
try:
|
||||
# this should fail because we don't trust and we're not at a terminal for interactive response
|
||||
_ = AutoTokenizer.from_pretrained(fake_model_id, local_files_only=True, trust_remote_code=False)
|
||||
self.fail("AutoTokenizer.from_pretrained with trust_remote_code=False should raise ValueException")
|
||||
except ValueError:
|
||||
pass
|
||||
finally:
|
||||
os.chdir(prev_dir)
|
||||
Reference in New Issue
Block a user