# 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 from paddle import ir paddle.enable_static() def get_ir_program(): x = paddle.randn([4, 4]) main_program, start_program = ( paddle.static.Program(), paddle.static.Program(), ) with paddle.static.program_guard(main_program, start_program): x_s = paddle.static.data('x', [4, 4], x.dtype) x_s.stop_gradient = False y_s = paddle.matmul(x_s, x_s) y_s = paddle.add(x_s, y_s) y_s = paddle.tanh(y_s) newir_program = ir.translate_to_new_ir(main_program.desc) return newir_program class TestBuildOp(unittest.TestCase): def test_build_mean_op(self): newir_program = get_ir_program() tanh_out = newir_program.block().ops[-1].result(0) paddle.framework.set_flags({"FLAGS_enable_new_ir_api": True}) with paddle.ir.core.program_guard(newir_program): out = paddle.mean(tanh_out) self.assertEqual(out.get_defining_op().name(), "pd.mean") self.assertEqual( out.get_defining_op() .operands()[0] .source() .get_defining_op() .name(), "pd.tanh", ) paddle.framework.set_flags({"FLAGS_enable_new_ir_api": False}) class TestBuildOp2(unittest.TestCase): def test_build_add_n_op(self): newir_program = get_ir_program() tanh_out = newir_program.block().ops[-1].result(0) paddle.framework.set_flags({"FLAGS_enable_new_ir_api": True}) with paddle.ir.core.program_guard(newir_program): out1 = paddle.mean(tanh_out) out2 = paddle.mean(tanh_out) out = paddle.add_n([out1, out2]) self.assertEqual(out.get_defining_op().name(), "pd.add_n") self.assertEqual( out.get_defining_op() .operands()[0] .source() .get_defining_op() .name(), "builtin.combine", ) paddle.framework.set_flags({"FLAGS_enable_new_ir_api": False}) class TestBuildOp3(unittest.TestCase): def test_insertion_point(self): newir_program = get_ir_program() paddle.framework.set_flags({"FLAGS_enable_new_ir_api": True}) add_op = newir_program.block().ops[-2] tanh_op = newir_program.block().ops[-1] add_out = add_op.result(0) tanh_operand = tanh_op.operands()[0] with paddle.ir.core.program_guard(newir_program): ir.set_insertion_point(tanh_op) full_out = paddle.tensor.fill_constant( shape=[4, 4], dtype="float", value=2 ) divide_out = paddle.divide(full_out, full_out) sum_out = paddle.sum(divide_out) out = paddle.mean(sum_out) tanh_operand.set_source(out) print(newir_program) self.assertEqual( tanh_operand.source().get_defining_op().name(), "pd.mean" ) paddle.framework.set_flags({"FLAGS_enable_new_ir_api": False}) class TestBuildOp4(unittest.TestCase): def test_build_concat_op(self): newir_program = get_ir_program() tanh_out = newir_program.block().ops[-1].result(0) paddle.framework.set_flags({"FLAGS_enable_new_ir_api": True}) with paddle.ir.core.program_guard(newir_program): out = paddle.concat([tanh_out, tanh_out], 0) self.assertEqual(out.get_defining_op().name(), "pd.concat") self.assertEqual( out.get_defining_op() .operands()[0] .source() .get_defining_op() .name(), "builtin.combine", ) paddle.framework.set_flags({"FLAGS_enable_new_ir_api": False}) if __name__ == "__main__": unittest.main()