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64 lines
2.2 KiB
64 lines
2.2 KiB
# Copyright (c) 2020 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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from __future__ import print_function
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import unittest
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import numpy as np
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from op_test import OpTest, randomize_probability
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import paddle.fluid as fluid
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import paddle.fluid.layers as layers
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import paddle
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@unittest.skipIf(not paddle.is_compiled_with_xpu(),
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"core is not compiled with XPU")
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class TestLoadOpXpu(unittest.TestCase):
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""" Test load operator.
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"""
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def setUp(self):
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self.ones = np.ones((4, 4)).astype('float32')
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main_prog = fluid.Program()
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start_prog = fluid.Program()
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with fluid.program_guard(main_prog, start_prog):
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input = fluid.data('input', shape=[-1, 4], dtype='float32')
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output = layers.fc(
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input,
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4,
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param_attr=fluid.ParamAttr(
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name='w',
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initializer=fluid.initializer.NumpyArrayInitializer(
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self.ones)))
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exe = fluid.Executor(fluid.XPUPlace(0))
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exe.run(start_prog)
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fluid.io.save_persistables(
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exe, dirname="./model", main_program=main_prog)
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def test_load_xpu(self):
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main_prog = fluid.Program()
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start_prog = fluid.Program()
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with fluid.program_guard(main_prog, start_prog):
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var = layers.create_tensor(dtype='float32')
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layers.load(var, file_path='./model/w')
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exe = fluid.Executor(fluid.XPUPlace(0))
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exe.run(start_prog)
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ret = exe.run(main_prog, fetch_list=[var.name])
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self.assertTrue(np.array_equal(self.ones, ret[0]))
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if __name__ == "__main__":
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unittest.main()
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