# 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. import paddle import paddle.fluid as fluid import paddle.fluid.layers as layers import unittest class TestAssertOp(unittest.TestCase): def run_network(self, net_func): main_program = fluid.Program() startup_program = fluid.Program() with fluid.program_guard(main_program, startup_program): net_func() exe = fluid.Executor() exe.run(main_program) def test_assert_true(self): def net_func(): condition = layers.fill_constant(shape=[1], dtype='bool', value=True) layers.Assert(condition, []) self.run_network(net_func) def test_assert_false(self): def net_func(): condition = layers.fill_constant(shape=[1], dtype='bool', value=False) layers.Assert(condition) with self.assertRaises(ValueError): self.run_network(net_func) def test_assert_cond_numel_error(self): def net_func(): condition = layers.fill_constant(shape=[1, 2], dtype='bool', value=True) layers.Assert(condition, []) with self.assertRaises(ValueError): self.run_network(net_func) def test_assert_print_data(self): def net_func(): zero = layers.fill_constant(shape=[1], dtype='int64', value=0) one = layers.fill_constant(shape=[1], dtype='int64', value=1) condition = layers.less_than(one, zero) # False layers.Assert(condition, [zero, one]) print("test_assert_print_data") with self.assertRaises(ValueError): self.run_network(net_func) def test_assert_summary(self): def net_func(): x = layers.fill_constant(shape=[10], dtype='float32', value=2.0) condition = layers.reduce_max(x) < 1.0 layers.Assert(condition, (x, ), 5) print("test_assert_summary") with self.assertRaises(ValueError): self.run_network(net_func) def test_assert_summary_greater_than_size(self): def net_func(): x = layers.fill_constant(shape=[2, 3], dtype='float32', value=2.0) condition = layers.reduce_max(x) < 1.0 layers.Assert(condition, [x], 10, name="test") print("test_assert_summary_greater_than_size") with self.assertRaises(ValueError): self.run_network(net_func) if __name__ == '__main__': paddle.enable_static() unittest.main()