// 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. #include #include "glog/logging.h" #include "paddle/fluid/ir/dialect/pd_dialect.h" #include "paddle/fluid/ir/dialect/pd_type.h" #include "paddle/fluid/ir/dialect/utils.h" #include "paddle/fluid/ir/interface/op_yaml_info.h" #include "paddle/ir/core/builtin_dialect.h" #include "paddle/ir/core/builtin_op.h" #include "paddle/ir/core/builtin_type.h" #include "paddle/ir/core/dialect.h" #include "paddle/ir/core/ir_context.h" #include "paddle/ir/core/op_base.h" #include "paddle/ir/core/operation.h" #include "paddle/ir/pass/pass.h" #include "paddle/ir/pass/pass_manager.h" #include "paddle/phi/kernels/elementwise_add_kernel.h" #ifndef _WIN32 class TestAnalysis1 {}; class TestAnalysis2 {}; IR_DECLARE_EXPLICIT_TYPE_ID(TestAnalysis1) IR_DEFINE_EXPLICIT_TYPE_ID(TestAnalysis1) IR_DECLARE_EXPLICIT_TYPE_ID(TestAnalysis2) IR_DEFINE_EXPLICIT_TYPE_ID(TestAnalysis2) TEST(pass_manager, PreservedAnalyses) { ir::detail::PreservedAnalyses pa; CHECK_EQ(pa.IsNone(), true); CHECK_EQ(pa.IsPreserved(), false); pa.Preserve(); CHECK_EQ(pa.IsPreserved(), true); pa.Unpreserve(); CHECK_EQ(pa.IsPreserved(), false); CHECK_EQ(pa.IsPreserved(), false); pa.Preserve(); CHECK_EQ(pa.IsPreserved(), true); CHECK_EQ(pa.IsPreserved(), true); CHECK_EQ(pa.IsAll(), false); pa.PreserveAll(); CHECK_EQ(pa.IsAll(), true); CHECK_EQ(pa.IsNone(), false); } #endif class AddOp : public ir::Op { public: using Op::Op; static const char *name() { return "test.add"; } static constexpr const char **attributes_name = nullptr; static constexpr uint32_t attributes_num = 0; void Verify(); static void Build(ir::Builder &builder, // NOLINT ir::OperationArgument &argument, // NOLINT ir::OpResult l_operand, ir::OpResult r_operand, ir::Type sum_type); }; void AddOp::Verify() { if (num_operands() != 2) { throw("The size of inputs must be equal to 2."); } if (num_results() != 1) { throw("The size of outputs must be equal to 1."); } } void AddOp::Build(ir::Builder &, ir::OperationArgument &argument, ir::OpResult l_operand, ir::OpResult r_operand, ir::Type sum_type) { argument.AddOperand(l_operand); argument.AddOperand(r_operand); argument.AddOutput(sum_type); } IR_DECLARE_EXPLICIT_TYPE_ID(AddOp) IR_DEFINE_EXPLICIT_TYPE_ID(AddOp) struct CountOpAnalysis { explicit CountOpAnalysis(ir::Operation *container_op) { IR_ENFORCE(container_op->num_regions() > 0, true); LOG(INFO) << "In CountOpAnalysis, op is " << container_op->name() << "\n"; for (size_t i = 0; i < container_op->num_regions(); ++i) { auto ®ion = container_op->region(i); for (auto it = region.begin(); it != region.end(); ++it) { auto *block = *it; for (auto it = block->begin(); it != block->end(); ++it) { ++count; } } } LOG(INFO) << "-- count is " << count << "\n"; } int count = 0; }; IR_DECLARE_EXPLICIT_TYPE_ID(CountOpAnalysis) IR_DEFINE_EXPLICIT_TYPE_ID(CountOpAnalysis) class TestPass : public ir::Pass { public: TestPass() : ir::Pass("TestPass", 1) {} void Run(ir::Operation *op) override { auto count_op_analysis = analysis_manager().GetAnalysis(); pass_state().preserved_analyses.Preserve(); CHECK_EQ(pass_state().preserved_analyses.IsPreserved(), true); CHECK_EQ(count_op_analysis.count, 4); auto module_op = op->dyn_cast(); CHECK_EQ(module_op.operation(), op); CHECK_EQ(module_op.name(), module_op->name()); LOG(INFO) << "In " << pass_info().name << ": " << module_op->name() << std::endl; pass_state().preserved_analyses.Unpreserve(); CHECK_EQ(pass_state().preserved_analyses.IsPreserved(), false); } bool CanApplyOn(ir::Operation *op) const override { return op->name() == "builtin.module" && op->num_regions() > 0; } }; TEST(pass_manager, PassManager) { // // TODO(liuyuanle): remove test code other than pass manager // // (1) Init environment. ir::IrContext *ctx = ir::IrContext::Instance(); ir::Dialect *builtin_dialect = ctx->GetOrRegisterDialect(); builtin_dialect->RegisterOp(); ir::Dialect *paddle_dialect = ctx->GetOrRegisterDialect(); // (2) Create an empty program object ir::Program program(ctx); // (3) Create a float32 DenseTensor Parameter and save into Program ir::Type fp32_dtype = ir::Float32Type::get(ctx); phi::DDim dims = {2, 2}; phi::DataLayout data_layout = phi::DataLayout::NCHW; phi::LoD lod = {{0, 1, 2}}; size_t offset = 0; ir::Type dense_tensor_dtype = paddle::dialect::DenseTensorType::get( ctx, fp32_dtype, dims, data_layout, lod, offset); std::vector data_a = {1, 2, 3, 4}; std::unique_ptr parameter_a = std::make_unique(reinterpret_cast(data_a.data()), 4 * sizeof(float), dense_tensor_dtype); program.SetParameter("a", std::move(parameter_a)); EXPECT_EQ(program.parameters_num() == 1, true); std::vector data_b = {5, 6, 7, 8}; std::unique_ptr parameter_b = std::make_unique(reinterpret_cast(data_b.data()), 4 * sizeof(float), dense_tensor_dtype); program.SetParameter("b", std::move(parameter_b)); EXPECT_EQ(program.parameters_num() == 2, true); // (4) Def a = GetParameterOp("a"), and create DenseTensor for a. ir::Builder builder(ctx, program.block()); auto op1 = builder.Build("a", dense_tensor_dtype); EXPECT_EQ(&program, op1->GetParentProgram()); EXPECT_EQ(op1->result(0).type().dialect().id(), paddle_dialect->id()); using Interface = paddle::dialect::ParameterConvertInterface; Interface *a_interface = op1->result(0).type().dialect().GetRegisteredInterface(); std::shared_ptr a_var = a_interface->ParameterToVariable(program.GetParameter("a")); const phi::DenseTensor &a_tensor = a_var->Get(); EXPECT_EQ(a_tensor.numel(), 4); EXPECT_EQ(a_tensor.dims(), dims); EXPECT_EQ(a_tensor.dtype(), paddle::dialect::TransToPhiDataType(fp32_dtype)); EXPECT_EQ(a_tensor.layout(), data_layout); EXPECT_EQ(a_tensor.lod(), lod); EXPECT_EQ(a_tensor.offset(), offset); for (int64_t i = 0; i < a_tensor.numel(); i++) { EXPECT_EQ(*(a_tensor.data() + i), data_a[i]); } // (5) Def b = GetParameterOp("b"), and create DenseTensor for b. auto op2 = builder.Build("b", dense_tensor_dtype); EXPECT_EQ(op2->result(0).type().dialect().id(), paddle_dialect->id()); Interface *b_interface = op2->result(0).type().dialect().GetRegisteredInterface(); std::shared_ptr b_var = b_interface->ParameterToVariable(program.GetParameter("b")); const phi::DenseTensor &b_tensor = b_var->Get(); EXPECT_EQ(b_tensor.numel(), 4); EXPECT_EQ(b_tensor.dims(), dims); EXPECT_EQ(b_tensor.dtype(), paddle::dialect::TransToPhiDataType(fp32_dtype)); EXPECT_EQ(b_tensor.layout(), data_layout); EXPECT_EQ(b_tensor.lod(), lod); EXPECT_EQ(b_tensor.offset(), offset); for (int64_t i = 0; i < b_tensor.numel(); i++) { EXPECT_EQ(*(b_tensor.data() + i), data_b[i]); } // (6) Def c = AddOp(a, b), execute this op. auto op3 = builder.Build(op1->result(0), op2->result(0), dense_tensor_dtype); phi::CPUContext *dev_ctx = static_cast( paddle::platform::DeviceContextPool::Instance().Get( paddle::platform::CPUPlace())); phi::DenseTensor c_tensor = phi::Add(*dev_ctx, a_tensor, b_tensor); std::shared_ptr variable_c = std::make_shared(); auto *dst_tensor = variable_c->GetMutable(); *dst_tensor = c_tensor; EXPECT_EQ(dst_tensor->numel(), b_tensor.numel()); EXPECT_EQ(dst_tensor->dims(), b_tensor.dims()); EXPECT_EQ(dst_tensor->dtype(), b_tensor.dtype()); EXPECT_EQ(dst_tensor->layout(), b_tensor.layout()); EXPECT_EQ(dst_tensor->lod(), b_tensor.lod()); EXPECT_EQ(dst_tensor->offset(), b_tensor.offset()); for (int64_t i = 0; i < dst_tensor->numel(); i++) { EXPECT_EQ(*(dst_tensor->data() + i), data_a[i] + data_b[i]); } // (7) Def SetParameterOp(c, "c") auto op4 = builder.Build(op3->result(0), "c"); EXPECT_EQ(op4->operand(0).source().type().dialect().id(), paddle_dialect->id()); Interface *c_interface = op4->operand(0).type().dialect().GetRegisteredInterface(); // ir::Parameter *parameter_c = // c_interface->VariableToParameter(variable_c.get()); std::unique_ptr parameter_c = c_interface->VariableToParameter(variable_c.get()); EXPECT_EQ(parameter_c->type(), dense_tensor_dtype); for (int64_t i = 0; i < dst_tensor->numel(); i++) { EXPECT_EQ(*(dst_tensor->data() + i), *(static_cast(parameter_c->data()) + i)); } program.SetParameter("c", std::move(parameter_c)); // (8) Traverse Program EXPECT_EQ(program.block()->size() == 4, true); EXPECT_EQ(program.parameters_num() == 3, true); // // TODO(liuyuanle): remove the code above. // // (9) Test pass manager for program. ir::PassManager pm(ctx); pm.AddPass(std::make_unique()); pm.EnableIRPrinting(std::make_unique( [](ir::Pass *pass, ir::Operation *op) { return pass->name() == "TestPass"; }, [](ir::Pass *pass, ir::Operation *op) { return pass->name() == "TestPass"; }, true, true)); pm.EnablePassTiming(true); CHECK_EQ(pm.Run(&program), true); }