# Copyright (c) 2023 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. import unittest import numpy as np import paddle class TestStandaloneExecutor(unittest.TestCase): def build_program(self): main_program = paddle.static.Program() startup_program = paddle.static.Program() with paddle.static.program_guard(main_program, startup_program): a = paddle.static.data(name="data", shape=[2, 2], dtype='float32') b = paddle.ones([2, 2]) * 2 t = paddle.static.nn.fc(a, 2) c = t + b return main_program, startup_program, [c] def run_program(self, force_sequential_run=False): seed = 100 paddle.seed(seed) np.random.seed(seed) main, startup, outs = self.build_program() build_strategy = paddle.static.BuildStrategy() build_strategy.force_sequential_run = force_sequential_run compiled_program = paddle.static.CompiledProgram( main, build_strategy=build_strategy ) exe = paddle.static.Executor() scope = paddle.static.Scope() with paddle.static.scope_guard(scope): exe.run(startup) data = np.ones([2, 2], dtype="float32") ret = exe.run( compiled_program, feed={"data": data}, fetch_list=[v.name for v in outs], ) return ret def test_result(self): paddle.enable_static() ret1 = self.run_program(True) ret2 = self.run_program(False) np.testing.assert_array_equal(ret1, ret2) if __name__ == "__main__": unittest.main()