Merge pull request #12 from AnushreeBannadabhavi/fix-build-errors

Fix build errors

llvm_passes/CustomTensorOperatorInstSelector.cpp

@@ -69,24 +69,6 @@ class CustomTensorOperatorInstSelector : public HardwareFIInstSelector {
         // Operator number to do FI
         int FIOperatorCount;
 
-        Operator(std::string name, std::string count) {
-
-            OperatorName = name;
-            FIOperatorCount = atoll(count.c_str());
-            OperatorCount = 0;
-            OperatorNumber = getOperatorNumber(name);
-
-            if (OperatorNumber == -1) {
-                std::cout<<"Operator name "<< OperatorName.c_str() <<
-                    "not found.\n";
-                std::cout<<"Please use the following operator name(s): \
-                conv, relu, maxpool, matmul, add, avgpool, all, and softmax.";
-                assert(false && "Invalid input operator name");
-            }
-
-            assert(FIOperatorCount >= 0 && "Invalid input FI operator number");
-        }
-
         // Get unique Id corresponding to the ONNX operator.
         static int64_t getOperatorNumber(std::string name) {
 
@@ -96,8 +78,10 @@ class CustomTensorOperatorInstSelector : public HardwareFIInstSelector {
 
             strcpy(opname, name.c_str());
 
+            std::cout<<"OperatorName: "<<opname<<"\n";
+
             // ONNX assigns unique IDs to each tensor operator.
-            std::map<char*, int64_t> ONNXOperatorId = {
+            std::map<std::string, int64_t> ONNXOperatorId = {
                 {"conv", 1986948931},
                 {"relu", 1970038098},
                 {"maxpool", 30521821366870349},
@@ -113,6 +97,24 @@ class CustomTensorOperatorInstSelector : public HardwareFIInstSelector {
             return ONNXOperatorId[opname];
         }
 
+        Operator(std::string name, std::string count) {
+
+            OperatorName = name;
+            FIOperatorCount = atoll(count.c_str());
+            OperatorCount = 0;
+            OperatorNumber = getOperatorNumber(name);
+
+            if (OperatorNumber == -1) {
+                std::cout<<"Operator name "<< OperatorName.c_str() <<
+                    " not found.\n";
+                std::cout<<"Please use the following operator name(s):\
+                conv, relu, maxpool, matmul, add, avgpool, all, and softmax.";
+                assert(false && "Invalid input operator name");
+            }
+
+            assert(FIOperatorCount >= 0 && "Invalid input FI operator number");
+        }
+
         bool doFaultInjection(){
 
             OperatorCount++;
@@ -262,7 +264,7 @@ class CustomTensorOperatorInstSelector : public HardwareFIInstSelector {
     virtual void getCompileTimeInfo(std::map<std::string, std::string> &info) {
         info["failure_class"] = "HardwareFault";
         info["failure_mode"] = "CustomTensorOperator";
-        info["targets"] = "<instructions in main_graph() function and within 
+        info["targets"] = "<instructions in main_graph() function and within \
             the specified tensor operator>";
         info["injector"] = "<fi_type>";
     }

llvm_passes/core/Controller.cpp

@@ -204,7 +204,7 @@ void Controller::processRegSelArgs() {
 void Controller::processCmdArgs() {
   // clear the log file
   std::error_code err;
-  raw_fd_ostream logFile(llfilogfile.c_str(), err, sys::fs::F_Append);
+  raw_fd_ostream logFile(llfilogfile.c_str(), err, sys::fs::OF_Append);
   if (!err) {
     logFile << "\n\nStart of a pass\n";
   } else {

llvm_passes/core/FIRegSelector.cpp

@@ -16,7 +16,7 @@ void FIRegSelector::getFIInstRegMap(
     const std::set< Instruction* > *instset, 
     std::map<Instruction*, std::list< int >* > *instregmap) {
   std::error_code err;
-  raw_fd_ostream logFile(llfilogfile.c_str(), err, sys::fs::F_Append);
+  raw_fd_ostream logFile(llfilogfile.c_str(), err, sys::fs::OF_Append);
 
   for (std::set<Instruction*>::const_iterator inst_it = instset->begin();
        inst_it != instset->end(); ++inst_it) {

llvm_passes/core/ProfilingPass.cpp

@@ -45,7 +45,7 @@ bool ProfilingPass::runOnModule(Module &M) {
   ctrl->getFIInstRegsMap(&fi_inst_regs_map);
   //BEHROOZ:
   std::error_code err;
-  raw_fd_ostream logFile(llfilogfile.c_str(), err, sys::fs::F_Append);
+  raw_fd_ostream logFile(llfilogfile.c_str(), err, sys::fs::OF_Append);
 
   for (std::map<Instruction*, std::list< int >* >::const_iterator 
        inst_reg_it = fi_inst_regs_map->begin(); 

sample_programs/memcpy1/input.yaml

@@ -5,12 +5,14 @@ kernelOption:
 
 compileOption:
     instSelMethod:
-      - customInstselector:
-          include:
-            - InappropriateClose(API)
+      - insttype:
+          include: 
+            - all
+          exclude:
+            - ret
 
-    regSelMethod: customregselector
-    customRegSelector: Automatic
+    regSelMethod: regloc
+    regloc: dstreg
 
 runOption:
     - run:

sample_programs/mnist/compile.sh

@@ -3,7 +3,7 @@ python3 $1.py
 
 printf "\n[Compile Script]: Convert TF model to LLVM IR\n"
 python3 -m tf2onnx.convert --saved-model $1.tf --output model.onnx
-python3 ../../tools/ExtendONNXModel.py model.onnx extendedmodel.onnx > expected_op_seq.txt
+python3 ../../tools/ExtendONNXModel.py --model_path ./model.onnx  --output_model_path ./extendedmodel.onnx > expected_op_seq.txt
 onnx-mlir --EmitLLVMIR extendedmodel.onnx --instrument-onnx-ops="ALL" --InstrumentBeforeOp --InstrumentAfterOp
 mlir-translate -mlir-to-llvmir extendedmodel.onnx.mlir > model.mlir.ll
 
@@ -12,4 +12,3 @@ clang -S -emit-llvm image.c -I$ONNX_MLIR_SRC/include -o main.ll
 llvm-link -o model.ll -S main.ll model.mlir.ll
 
 printf "\n[Compile Script]: Compilation complete\n"
-

sample_programs/mnist/image.c

@@ -13,11 +13,14 @@
 #include <string.h>
 #include <assert.h>
 #include <stdlib.h>
+#include <sys/time.h>
 
 #define STB_IMAGE_IMPLEMENTATION
 #include "stb_image.h"
 
 #define RANK 2
+#define NUM_OUTPUT_CLASSES 10 // For MNIST, there are 10 possible digits.
+
 
 OMTensorList *run_main_graph(OMTensorList *);
 void export_layer_output_to_json(OMTensorList *, char*, char*);
@@ -42,24 +45,34 @@ int main(int argc, char *argv[]) {
     OMTensor *x1 = omTensorCreate(rgb_image, in_shape, RANK, ONNX_TYPE_FLOAT);
     OMTensor *img_list[1] = {x1};
     OMTensorList *input = omTensorListCreate(img_list, 1);
+
+    struct timeval start, end;
+    gettimeofday(&start, NULL);
 
     // Call the compiled onnx model function.
     OMTensorList *outputList = run_main_graph(input);
 
+    gettimeofday(&end, NULL);
+
+    double time_taken = end.tv_sec + end.tv_usec / 1e6 -
+                        start.tv_sec - start.tv_usec / 1e6; // in seconds
+
+
+    printf("Time taken to execute the model: %f\n", time_taken);
+
     // Export layer outputs to a JSON file
     export_layer_output_to_json(outputList, savefilename, output_seq);
 
-    // Get the last omt as output.
+    // Get the first omt as output.
     OMTensor *output = omTensorListGetOmtByIndex(outputList, omTensorListGetSize(outputList) - 1);
     float *outputPtr = (float *)omTensorGetDataPtr(output);
 
-    // Print out elements of the last tensor
-    int64_t *shape = omTensorGetShape(output);
-    int64_t numElements = (int64_t) (omTensorGetNumElems(output) / shape[0]);
     printf("Final prediction for %s is: ", filename);
 
-    for (int i = 0; i < numElements; i++)
+    // Print its content, should be in softmax form
+    for (int i = 0; i < NUM_OUTPUT_CLASSES; i++)
         printf("%f ", outputPtr[i]);
+    printf("\n");
 
     stbi_image_free(rgb_image);
 

sample_programs/mnist/input.yaml

@@ -4,8 +4,8 @@ compileOption:
           include:
             - CustomTensorOperator
           options:
-            - -layerNo=1;1
-            - -layerName=conv;relu
+            - -layerNo=0;0;0;0;0;0;0
+            - -layerName=conv;relu;matmul;maxpool;add;avgpool;softmax
 
     regSelMethod: regloc
     regloc: dstreg
@@ -23,8 +23,8 @@ compileOption:
 
 runOption:
     - run:
-        numOfRuns: 50
+        numOfRuns: 1000
         fi_type: bitflip
         window_len_multiple_startindex: 1
         window_len_multiple_endindex: 500
-        fi_max_multiple: 9
+        fi_max_multiple: 2