wehub-resource-sync
57 lines
2.3 KiB
Python
57 lines
2.3 KiB
Python
# Copyright (c) 2022 PaddlePaddle Authors. 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 os
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import unittest
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from tempfile import TemporaryDirectory
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from paddlenlp.transformers import BertModel
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from paddlenlp.utils.env import CONFIG_NAME, PADDLE_WEIGHTS_NAME
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from tests.testing_utils import slow
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def download_bert_model(model_name: str):
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"""set the global method: multiprocessing can not pickle local method
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Args:
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model_name (str): the model name
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"""
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model = BertModel.from_pretrained(model_name)
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# free the model resource
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del model
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class TestModeling(unittest.TestCase):
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"""Test PretrainedModel single time, not in Transformer models"""
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def test_from_pretrained_cache_dir_community_model(self):
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model_name = "__internal_testing__/bert"
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with TemporaryDirectory() as tempdir:
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BertModel.from_pretrained(model_name, cache_dir=tempdir)
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self.assertTrue(os.path.exists(os.path.join(tempdir, model_name, CONFIG_NAME)))
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self.assertTrue(os.path.exists(os.path.join(tempdir, model_name, PADDLE_WEIGHTS_NAME)))
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# check against double appending model_name in cache_dir
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self.assertFalse(os.path.exists(os.path.join(tempdir, model_name, model_name)))
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@slow
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def test_from_pretrained_cache_dir_pretrained_init(self):
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model_name = "bert-base-uncased"
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with TemporaryDirectory() as tempdir:
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BertModel.from_pretrained(model_name, cache_dir=tempdir)
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self.assertTrue(os.path.exists(os.path.join(tempdir, model_name, CONFIG_NAME)))
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self.assertTrue(os.path.exists(os.path.join(tempdir, model_name, PADDLE_WEIGHTS_NAME)))
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# check against double appending model_name in cache_dir
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self.assertFalse(os.path.exists(os.path.join(tempdir, model_name, model_name)))
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