wehub-resource-sync
73 lines
2.7 KiB
Python
73 lines
2.7 KiB
Python
# Copyright (c) 2024 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 unittest
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import numpy as np
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import paddle
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from paddlenlp_ops import update_inputs_v2
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np.random.seed(2023)
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class GetUpdateInputsTest(unittest.TestCase):
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def test_update_inputs(self):
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tensor1 = paddle.to_tensor([[False]], dtype="bool", place=paddle.XPUPlace(0), stop_gradient=True)
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tensor2 = paddle.to_tensor([[32]], dtype="int64", place=paddle.XPUPlace(0), stop_gradient=True)
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tensor3 = paddle.to_tensor([True], dtype="bool", place=paddle.XPUPlace(0), stop_gradient=True)
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tensor4 = paddle.to_tensor([[1]], dtype="int32", place=paddle.XPUPlace(0), stop_gradient=True)
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tensor5 = paddle.to_tensor([[0]], dtype="int32", place=paddle.XPUPlace(0), stop_gradient=True)
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tensor6 = paddle.to_tensor([[44]], dtype="int32", place=paddle.XPUPlace(0), stop_gradient=True)
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tensor7 = paddle.to_tensor([[200]], dtype="int64", place=paddle.XPUPlace(0), stop_gradient=True)
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tensor8 = paddle.to_tensor(
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[[2160, 5726, 25, 100001, 100001, 100001]], dtype="int64", place=paddle.XPUPlace(0), stop_gradient=True
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)
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tensor9 = paddle.to_tensor([1], dtype="int64", place=paddle.XPUPlace(0), stop_gradient=True)
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tensor10 = paddle.to_tensor([[100001]], dtype="int64", place=paddle.XPUPlace(0), stop_gradient=True)
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tensor11 = paddle.to_tensor([False], dtype="bool", place=paddle.XPUPlace(0), stop_gradient=True)
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tensor12 = paddle.to_tensor([[100001]], dtype="int64", place=paddle.XPUPlace(0), stop_gradient=True)
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tensor13 = paddle.to_tensor([[2160]], dtype="int64", place=paddle.XPUPlace(0), stop_gradient=True)
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# 将 Tensors 合并到一个列表中
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arg = [
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tensor1,
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tensor2,
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tensor3,
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tensor4,
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tensor5,
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tensor6,
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tensor7,
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tensor8,
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tensor9,
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tensor10,
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tensor11,
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tensor12,
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tensor13,
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]
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print(arg)
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print("---------------")
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update_inputs_v2(*arg)
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print(arg)
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assert tensor1 is True
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assert tensor3 is False
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if __name__ == "__main__":
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unittest.main()
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