# 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 paddle paddle.enable_static() class TestBuildModuleWithAssertOp(unittest.TestCase): def test_assert_construct(self): main_program = paddle.static.Program() startup_program = paddle.static.Program() with paddle.static.program_guard(main_program, startup_program): x = paddle.static.data(name="x", shape=[2, 8], dtype="float32") condition = paddle.all(x > 0) paddle.static.nn.control_flow.Assert(condition, [x], 20) assert_op = main_program.global_block().ops[-1] self.assertEqual(assert_op.name(), "pd_op.assert") self.assertEqual(len(assert_op.results()), 0) def run_network(self, net_func): with paddle.pir_utils.IrGuard(): main = paddle.static.Program() startup = paddle.static.Program() with paddle.static.program_guard(main, startup): net_func() exe = paddle.static.Executor() exe.run(main) def test_assert_true(self): def net_func(): condition = paddle.tensor.fill_constant( shape=[1], dtype='bool', value=True ) paddle.static.nn.control_flow.Assert(condition, []) self.run_network(net_func) def test_assert_false(self): def net_func(): condition = paddle.tensor.fill_constant( shape=[1], dtype='bool', value=False ) paddle.static.nn.control_flow.Assert(condition) with self.assertRaises(ValueError): self.run_network(net_func) # TODO(MarioLulab): May lead `test_assert_construct` construct empty main_program. Fix it soon. # def test_assert_cond_numel_error(self): # def net_func(): # condition = paddle.tensor.fill_constant( # shape=[1, 2], dtype='bool', value=True # ) # paddle.static.nn.control_flow.Assert(condition, []) # with self.assertRaises(ValueError): # self.run_network(net_func) def test_assert_print_data(self): def net_func(): zero = paddle.tensor.fill_constant( shape=[5], dtype='int64', value=0 ) one = paddle.tensor.fill_constant(shape=[5], dtype='int64', value=1) condition = paddle.less_than(one, zero).all() # False paddle.static.nn.control_flow.Assert( condition, [zero, one], summarize=8 ) with self.assertRaises(ValueError): self.run_network(net_func) def test_assert_summary(self): def net_func(): x = paddle.tensor.fill_constant( shape=[10], dtype='float32', value=2.0 ) condition = paddle.max(x) < 1.0 paddle.static.nn.control_flow.Assert(condition, (x,), 5) with self.assertRaises(ValueError): self.run_network(net_func) def test_assert_summary_greater_than_size(self): def net_func(): x = paddle.tensor.fill_constant( shape=[2, 3], dtype='float32', value=2.0 ) condition = paddle.max(x) < 1.0 paddle.static.nn.control_flow.Assert( condition, [x], 10, name="test" ) with self.assertRaises(ValueError): self.run_network(net_func) if __name__ == "__main__": unittest.main()