# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. # # 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. from __future__ import print_function import unittest import numpy as np from op_test import OpTest, randomize_probability import paddle.fluid as fluid import paddle.fluid.layers as layers class TestLoadOp(unittest.TestCase): """ Test load operator. """ def setUp(self): self.ones = np.ones((4, 4)).astype('float32') main_prog = fluid.Program() start_prog = fluid.Program() with fluid.program_guard(main_prog, start_prog): input = fluid.data('input', shape=[-1, 4], dtype='float32') output = layers.fc( input, 4, param_attr=fluid.ParamAttr( name='w', initializer=fluid.initializer.NumpyArrayInitializer( self.ones))) exe = fluid.Executor(fluid.CPUPlace()) exe.run(start_prog) fluid.io.save_persistables( exe, dirname="/tmp/model", main_program=main_prog) def test_load(self): main_prog = fluid.Program() start_prog = fluid.Program() with fluid.program_guard(main_prog, start_prog): var = layers.create_tensor(dtype='float32') layers.load(var, file_path='/tmp/model/w') exe = fluid.Executor(fluid.CPUPlace()) exe.run(start_prog) ret = exe.run(main_prog, fetch_list=[var.name]) self.assertTrue(np.array_equal(self.ones, ret[0])) if __name__ == "__main__": unittest.main()