[Infrt] add result check for some infrt op. (#41167)

paddle/infrt/api/infrt_api.cc

@@ -238,8 +238,8 @@ int InfRtPredictor::Init(const InfRtConfig& config) {
   std::vector<::infrt::Place> valid_places = {{::infrt::TargetType::CPU,
                                                ::infrt::PrecisionType::FLOAT32,
                                                ::infrt::LayoutType::NCHW}};
-  phi_pass_manager.addPass(::infrt::createPhiOpCvtPass(valid_places));
-  phi_pass_manager.addPass(::infrt::createInfrtOpFusePass());
+  phi_pass_manager.addPass(CreatePhiOpCvtPass(valid_places));
+  phi_pass_manager.addPass(CreateInfrtOpFusePass());
   if (mlir::failed(pm.run(module_op))) {
     std::cout << "\npass failed!\n" << std::endl;
     return 4;

paddle/infrt/dialect/infrt/pass/infrt_op_fuse_pass.cc

@@ -53,7 +53,7 @@ void InfrtOpFusePass::runOnFunction() {
 
 }  // namespace
 
-std::unique_ptr<mlir::Pass> infrt::createInfrtOpFusePass() {
+std::unique_ptr<mlir::Pass> infrt::CreateInfrtOpFusePass() {
   return std::make_unique<InfrtOpFusePass>();
 }
 

paddle/infrt/dialect/infrt/pass/infrt_op_fuse_pass.h

@@ -19,6 +19,6 @@ namespace infrt {
 /*
  * infrtOpFusePass.
  */
-std::unique_ptr<mlir::Pass> createInfrtOpFusePass();
+std::unique_ptr<mlir::Pass> CreateInfrtOpFusePass();
 
 }  // namespace infrt

paddle/infrt/dialect/phi/CMakeLists.txt

@@ -5,10 +5,6 @@ endif()
 add_subdirectory(ir)
 add_subdirectory(pass)
 
-add_executable(phi-ir-exec phi_ir_exec.cc)
-target_link_libraries(phi-ir-exec infrt)
-
-
 add_executable(phi-exec phi_exec.cc)
 target_link_libraries(phi-exec infrt)
 

paddle/infrt/dialect/phi/pass/phi_op_convert_pass.cc

@@ -261,11 +261,11 @@ void PhiOpConvertPass::getDependentDialects(
 
 mlir::PassRegistration<PhiOpConvertPass> phi_op_convert;
 
-std::unique_ptr<mlir::Pass> infrt::createPhiOpCvtPass(
+std::unique_ptr<mlir::Pass> infrt::CreatePhiOpCvtPass(
     std::vector<Place> valid_places) {
   return std::make_unique<PhiOpConvertPass>(valid_places);
 }
 
-std::unique_ptr<mlir::Pass> infrt::createPhiOpCvtPass() {
+std::unique_ptr<mlir::Pass> infrt::CreatePhiOpCvtPass() {
   return std::make_unique<PhiOpConvertPass>();
 }

paddle/infrt/dialect/phi/pass/phi_op_convert_pass.h

@@ -21,8 +21,8 @@ namespace infrt {
  * phiOpCvtPass.
  * Convert the general operators from pd Dialect to phi dialect.
  */
-std::unique_ptr<mlir::Pass> createPhiOpCvtPass(std::vector<Place> valid_places);
+std::unique_ptr<mlir::Pass> CreatePhiOpCvtPass(std::vector<Place> valid_places);
 
-std::unique_ptr<mlir::Pass> createPhiOpCvtPass();
+std::unique_ptr<mlir::Pass> CreatePhiOpCvtPass();
 
 }  // namespace infrt

paddle/infrt/dialect/phi/phi_ir_exec.cc

-// Copyright (c) 2021 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 <llvm/Support/CommandLine.h>
-#include <mlir/Pass/PassManager.h>
-#include <iostream>
-#include <string>
-#include "paddle/infrt/common/global.h"
-#include "paddle/infrt/dialect/infrt/pass/infrt_op_fuse_pass.h"
-#include "paddle/infrt/dialect/mlir_loader.h"
-#include "paddle/infrt/dialect/phi/pass/phi_op_convert_pass.h"
-
-int main(int argc, char** argv) {
-  static llvm::cl::opt<std::string> input_file(
-      llvm::cl::Positional,
-      llvm::cl::desc("Specify input filename"),
-      llvm::cl::init("-"));
-
-  llvm::cl::ParseCommandLineOptions(argc, argv);
-
-  mlir::MLIRContext* context = infrt::Global::getMLIRContext();
-  auto module = infrt::dialect::LoadMlirFile(input_file.c_str(), context);
-  context->loadAllAvailableDialects();
-  module->dump();
-  mlir::PassManager pm(context);
-
-  mlir::OpPassManager& phi_pass_manager = pm.nest<mlir::FuncOp>();
-  std::vector<infrt::Place> valid_places = {{infrt::TargetType::CPU,
-                                             infrt::PrecisionType::FLOAT32,
-                                             infrt::LayoutType::NCHW}};
-  phi_pass_manager.addPass(infrt::createPhiOpCvtPass(valid_places));
-  phi_pass_manager.addPass(infrt::createInfrtOpFusePass());
-  if (mlir::failed(pm.run(*module))) {
-    std::cout << "\npass failed!\n" << std::endl;
-    return 4;
-  }
-  module->dump();
-  return 0;
-}

paddle/infrt/host_context/mlir_exec.cc

@@ -98,8 +98,8 @@ int main(int argc, char** argv) {
   std::vector<infrt::Place> valid_places = {{infrt::TargetType::CPU,
                                              infrt::PrecisionType::FLOAT32,
                                              infrt::LayoutType::NCHW}};
-  phi_pass_manager.addPass(infrt::createPhiOpCvtPass(valid_places));
-  phi_pass_manager.addPass(infrt::createInfrtOpFusePass());
+  phi_pass_manager.addPass(infrt::CreatePhiOpCvtPass(valid_places));
+  phi_pass_manager.addPass(infrt::CreateInfrtOpFusePass());
 #endif
 
   if (mlir::failed(pm.run(*module))) {

paddle/infrt/tests/dialect/phi/kernels/resnet50_ops.mlir

+// RUN: infrtexec -i %s | FileCheck %s
+module  {
+  func @main() {
+    %ctx = "phi_dt.create_context.cpu" (): () -> !phi.context<CPU>
+    %0 = "phi_dt.create_inited_dense_tensor.cpu.f32" (%ctx) {value = 2.0 : f32, layout=#infrt.layout<NCHW>, lod=[1:i64], dims=[1, 3, 6, 6]}: (!phi.context<CPU>) -> (!infrt.dense_tensor<CPU, FP32, NCHW>)
+    %1 = "phi_dt.create_inited_dense_tensor.cpu.f32" (%ctx) {value = 2.0 : f32, layout=#infrt.layout<NCHW>, lod=[1:i64], dims=[1, 3, 3, 3]}: (!phi.context<CPU>) -> (!infrt.dense_tensor<CPU, FP32, NCHW>)
+    
+    %2 = "pd.conv2d"(%0, %1) {data_format = "NCHW", dilations = [1 : i32, 1 : i32], groups = 1 : si32, padding_algorithm = "EXPLICIT", paddings = [3 : i32, 3 : i32], strides = [2 : i32, 2 : i32]} : (!infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>) -> !infrt.dense_tensor<CPU, FP32, NCHW>
+    // CHECK: dense_tensor: shape=shape[1, 1, 5, 5], value=[0,0,0,0,0,0,48,72,72,24,0,72,108,108,36,0,72,108,108,36,0,24,36,36,12]
+    phi_dt.print_tensor (%2 : !infrt.dense_tensor<CPU, FP32, NCHW>)
+    
+    %3 = "pd.relu"(%2) : (!infrt.dense_tensor<CPU, FP32, NCHW>) -> !infrt.dense_tensor<CPU, FP32, NCHW>
+    // dense_tensor: shape=shape[1, 1, 5, 5], value=[0,0,0,0,0,0,48,72,72,24,0,72,108,108,36,0,72,108,108,36,0,24,36,36,12]
+    phi_dt.print_tensor (%3 : !infrt.dense_tensor<CPU, FP32, NCHW>)
+
+    %4 = "pd.pool2d"(%2) {adaptive = false, ceil_mode = false, data_format = "NCHW", exclusive = true, global_pooling = false, ksize = [2 : i32, 2 : i32], padding_algorithm = "EXPLICIT", paddings = [1 : i32, 1 : i32], pooling_type = "avg", strides = [2 : i32, 2 : i32]} : (!infrt.dense_tensor<CPU, FP32, NCHW>) -> !infrt.dense_tensor<CPU, FP32, NCHW>
+    // CHECK: dense_tensor: shape=shape[1, 1, 3, 3], value=[0,0,0,0,75,60,0,60,48]
+    phi_dt.print_tensor (%4 : !infrt.dense_tensor<CPU, FP32, NCHW>)
+
+    %5 = "pd.flatten_contiguous_range"(%4) {start_axis = 1 : si32, stop_axis = 3 : si32} : (!infrt.dense_tensor<CPU, FP32, NCHW>) -> !infrt.dense_tensor<CPU, FP32, NCHW>
+    // CHECK: dense_tensor: shape=shape[1, 9], value=[0,0,0,0,75,60,0,60,48]
+    phi_dt.print_tensor (%5 : !infrt.dense_tensor<CPU, FP32, NCHW>)
+    
+    %6 = "pd.elementwise_add"(%5, %5) {axis = 1 : si32} : (!infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>) -> !infrt.dense_tensor<CPU, FP32, NCHW> 
+    // CHECK: dense_tensor: shape=shape[1, 9], value=[0,0,0,0,150,120,0,120,96]
+    phi_dt.print_tensor (%6 : !infrt.dense_tensor<CPU, FP32, NCHW>)
+    
+    %7 = "phi_dt.create_inited_dense_tensor.cpu.f32" (%ctx) {value = 4.0 : f32, layout=#infrt.layout<NCHW>, lod=[1:i64], dims=[9, 3]}: (!phi.context<CPU>) -> (!infrt.dense_tensor<CPU, FP32, NCHW>)
+    %8 = "pd.matmul_v2"(%5, %7) {trans_x = false, trans_y = false} : (!infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>) -> !infrt.dense_tensor<CPU, FP32, NCHW>
+    // CHECK: dense_tensor: shape=shape[1, 3], value=[972,972,972]
+    phi_dt.print_tensor (%8 : !infrt.dense_tensor<CPU, FP32, NCHW>)
+
+    %scale = "phi_dt.create_inited_dense_tensor.cpu.f32" (%ctx) {value=1.0:f32, layout=#infrt.layout<NCHW>, lod=[1], dims=[3]}: (!phi.context<CPU>) -> (!infrt.dense_tensor<CPU, FP32, NCHW>)
+    %bias = "phi_dt.create_inited_dense_tensor.cpu.f32" (%ctx) {value=1.8:f32, layout=#infrt.layout<NCHW>, lod=[1], dims=[3]}: (!phi.context<CPU>) -> (!infrt.dense_tensor<CPU, FP32, NCHW>)
+    %mean = "phi_dt.create_inited_dense_tensor.cpu.f32" (%ctx) {value=2.0:f32, layout=#infrt.layout<NCHW>, lod=[1], dims=[3]}: (!phi.context<CPU>) -> (!infrt.dense_tensor<CPU, FP32, NCHW>)
+    %var = "phi_dt.create_inited_dense_tensor.cpu.f32" (%ctx) {value=0.0:f32, layout=#infrt.layout<NCHW>, lod=[1], dims=[3]}: (!phi.context<CPU>) -> (!infrt.dense_tensor<CPU, FP32, NCHW>)
+    %Y, %MeanOut, %VarianceOut = "pd.batch_norm"(%1, %scale, %bias, %mean, %var) {data_layout = "NCHW", epsilon = 0.01 : f32, momentum = 0.5 : f32} : (!infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>) -> (!infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>)
+    // CHECK: dense_tensor: shape=shape[1, 3, 3, 3], value=[1.8,1.8,1.8,1.8,1.8,1.8,1.8,1.8,1.8,1.8,1.8,1.8,1.8,1.8,1.8,1.8,1.8,1.8,1.8,1.8,1.8,1.8,1.8,1.8,1.8,1.8,1.8]
+    phi_dt.print_tensor (%Y : !infrt.dense_tensor<CPU, FP32, NCHW>)
+  
+    infrt.return
+  }
+}

paddle/infrt/tests/models/test_abs.cc

@@ -86,8 +86,8 @@ TEST(ABS_MODEL, convert_and_execute) {
   std::vector<infrt::Place> valid_places = {{infrt::TargetType::CPU,
                                              infrt::PrecisionType::FLOAT32,
                                              infrt::LayoutType::NCHW}};
-  phi_pass_manager.addPass(infrt::createPhiOpCvtPass(valid_places));
-  phi_pass_manager.addPass(infrt::createInfrtOpFusePass());
+  phi_pass_manager.addPass(infrt::CreatePhiOpCvtPass(valid_places));
+  phi_pass_manager.addPass(infrt::CreateInfrtOpFusePass());
 
   if (mlir::failed(pm.run(module_))) {
     std::cout << "\npass failed!\n" << std::endl;