wehub-resource-sync
135 lines
6.6 KiB
Python
135 lines
6.6 KiB
Python
# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
|
|
# Copyright 2019 Hugging Face inc.
|
|
#
|
|
# 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 tempfile
|
|
import unittest
|
|
|
|
import paddlenlp
|
|
from paddlenlp.transformers import AutoTokenizer
|
|
from paddlenlp.transformers.auto.configuration import CONFIG_MAPPING, AutoConfig
|
|
from paddlenlp.transformers.auto.tokenizer import TOKENIZER_MAPPING
|
|
from paddlenlp.transformers.bert.configuration import BertConfig
|
|
from paddlenlp.transformers.bert.tokenizer import BertTokenizer
|
|
from paddlenlp.transformers.bert.tokenizer_fast import BertTokenizerFast
|
|
from paddlenlp.utils.env import TOKENIZER_CONFIG_NAME
|
|
|
|
from ...utils.test_module.custom_configuration import CustomConfig
|
|
from ...utils.test_module.custom_tokenizer import CustomTokenizer
|
|
from ...utils.test_module.custom_tokenizer_fast import (
|
|
CustomTokenizerFast,
|
|
CustomTokenizerFastWithoutSlow,
|
|
)
|
|
|
|
|
|
class AutoTokenizerTest(unittest.TestCase):
|
|
@unittest.skip("skipping due to connection error!")
|
|
def test_from_aistudio(self):
|
|
tokenizer = AutoTokenizer.from_pretrained("PaddleNLP/tiny-random-bert", from_aistudio=True)
|
|
self.assertIsInstance(tokenizer, paddlenlp.transformers.BertTokenizer)
|
|
|
|
def test_from_pretrained_cache_dir(self):
|
|
model_name = "__internal_testing__/tiny-random-bert"
|
|
with tempfile.TemporaryDirectory() as tempdir:
|
|
AutoTokenizer.from_pretrained(model_name, cache_dir=tempdir)
|
|
self.assertTrue(os.path.exists(os.path.join(tempdir, model_name, TOKENIZER_CONFIG_NAME)))
|
|
# check against double appending model_name in cache_dir
|
|
self.assertFalse(os.path.exists(os.path.join(tempdir, model_name, model_name)))
|
|
|
|
def test_from_pretrained_tokenizer_fast(self):
|
|
tokenizer = AutoTokenizer.from_pretrained("intfloat/e5-base-v2", use_fast=True)
|
|
self.assertIsInstance(tokenizer, BertTokenizerFast)
|
|
|
|
def test_new_tokenizer_registration(self):
|
|
try:
|
|
AutoConfig.register("custom", CustomConfig)
|
|
|
|
AutoTokenizer.register(CustomConfig, slow_tokenizer_class=CustomTokenizer)
|
|
# Trying to register something existing in the PaddleNLP library will raise an error
|
|
with self.assertRaises(ValueError):
|
|
AutoTokenizer.register(BertConfig, slow_tokenizer_class=BertTokenizer)
|
|
|
|
tokenizer = CustomTokenizer.from_pretrained("julien-c/bert-xsmall-dummy")
|
|
with tempfile.TemporaryDirectory() as tmp_dir:
|
|
tokenizer.save_pretrained(tmp_dir)
|
|
|
|
new_tokenizer = AutoTokenizer.from_pretrained(tmp_dir)
|
|
self.assertIsInstance(new_tokenizer, CustomTokenizer)
|
|
|
|
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_new_tokenizer_fast_registration(self):
|
|
try:
|
|
# Trying to register nothing
|
|
with self.assertRaises(ValueError):
|
|
AutoTokenizer.register(CustomConfig)
|
|
# Trying to register tokenizer with wrong type
|
|
with self.assertRaises(ValueError):
|
|
AutoTokenizer.register(CustomConfig, fast_tokenizer_class=CustomTokenizer)
|
|
with self.assertRaises(ValueError):
|
|
AutoTokenizer.register(CustomConfig, slow_tokenizer_class=CustomTokenizerFast)
|
|
with self.assertRaises(ValueError):
|
|
AutoTokenizer.register(
|
|
CustomConfig,
|
|
slow_tokenizer_class=CustomTokenizer,
|
|
fast_tokenizer_class=CustomTokenizerFastWithoutSlow,
|
|
)
|
|
AutoConfig.register("custom", CustomConfig)
|
|
|
|
# Can register in two steps
|
|
AutoTokenizer.register(CustomConfig, slow_tokenizer_class=CustomTokenizer)
|
|
self.assertEqual(TOKENIZER_MAPPING[CustomConfig], (CustomTokenizer, None))
|
|
AutoTokenizer.register(CustomConfig, fast_tokenizer_class=CustomTokenizerFast)
|
|
self.assertEqual(TOKENIZER_MAPPING[CustomConfig], (CustomTokenizer, CustomTokenizerFast))
|
|
|
|
del TOKENIZER_MAPPING._extra_content[CustomConfig]
|
|
# Can register in one step
|
|
AutoTokenizer.register(
|
|
CustomConfig, slow_tokenizer_class=CustomTokenizer, fast_tokenizer_class=CustomTokenizerFast
|
|
)
|
|
self.assertEqual(TOKENIZER_MAPPING[CustomConfig], (CustomTokenizer, CustomTokenizerFast))
|
|
|
|
# Trying to register something existing in the PaddleNLP library will raise an error
|
|
with self.assertRaises(ValueError):
|
|
AutoTokenizer.register(BertConfig, fast_tokenizer_class=BertTokenizerFast)
|
|
with self.assertRaises(ValueError):
|
|
AutoTokenizer.register(BertConfig, slow_tokenizer_class=BertTokenizer)
|
|
|
|
# We pass through a llama tokenizer fast cause there is no converter slow to fast for our new toknizer
|
|
# and that model does not have a tokenizer.json
|
|
with tempfile.TemporaryDirectory() as tmp_dir:
|
|
llama_tokenizer = BertTokenizerFast.from_pretrained("julien-c/bert-xsmall-dummy", from_hf_hub=True)
|
|
llama_tokenizer.save_pretrained(tmp_dir)
|
|
tokenizer = CustomTokenizerFast.from_pretrained(tmp_dir)
|
|
|
|
with tempfile.TemporaryDirectory() as tmp_dir:
|
|
tokenizer.save_pretrained(tmp_dir, legacy_format=True)
|
|
|
|
new_tokenizer = AutoTokenizer.from_pretrained(tmp_dir, use_fast=True)
|
|
self.assertIsInstance(new_tokenizer, CustomTokenizerFast)
|
|
|
|
# TODO: fix this test. Now keep loaded tokenizer type
|
|
# new_tokenizer = AutoTokenizer.from_pretrained(tmp_dir, use_fast=False)
|
|
# self.assertIsInstance(new_tokenizer, CustomTokenizer)
|
|
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]
|