From 8ac11bec97d52f1a23f4eedacd6537978e08a791 Mon Sep 17 00:00:00 2001
From: Hashim Sharif <hsharif3@tyler.cs.illinois.edu>
Date: Mon, 24 Feb 2020 22:34:00 -0600
Subject: [PATCH] Adding utils support for dumping class confidences and
predicted labels
---
.../dnn_sources/include/utils.h | 84 ++++++++++++++++++-
.../src/promise/alexnet_promise.cc | 42 ++++++++--
2 files changed, 116 insertions(+), 10 deletions(-)
diff --git a/llvm/projects/hpvm-tensor-rt/dnn_sources/include/utils.h b/llvm/projects/hpvm-tensor-rt/dnn_sources/include/utils.h
index a627f83e6b..9068445670 100644
--- a/llvm/projects/hpvm-tensor-rt/dnn_sources/include/utils.h
+++ b/llvm/projects/hpvm-tensor-rt/dnn_sources/include/utils.h
@@ -17,6 +17,7 @@ std::vector<float> run_accuracies;
void printTensorInfo(void* tensor_ptr){
+
struct Tensor* tensor = (struct Tensor*) tensor_ptr;
if(tensor->gpu_data != NULL){
@@ -76,13 +77,21 @@ void fillWithOnesAndTwos(void* tensor_ptr){
// initialization is specific to the floating point type
if(tensor->data_type == CUDNN_DATA_FLOAT){
float* data_arr = (float*) tensor->host_data;
- for(unsigned int i = 0; i < tensor->num_elems/2; i++){
+
+ for(unsigned int i = 0; i < tensor->num_elems; i++){
+ if (i % 2 == 0)
+ data_arr[i] = 1.0;
+ else
+ data_arr[i] = 2.0;
+ }
+
+ /*for(unsigned int i = 0; i < tensor->num_elems/2; i++){
data_arr[i] = 1.0;
}
for(unsigned int i = tensor->num_elems/2; i < tensor->num_elems; i++){
data_arr[i] = 2.0;
- }
+ }*/
}
}
@@ -852,4 +861,75 @@ void dumpOutput(void* output_ptr, const char* file_name){
+
+
+void copyClassConfsAndLabels(void* result_ptr,
+ float* classConfs,
+ int* predictedLabels,
+ int start, int end){
+
+
+ struct Tensor* result = (struct Tensor*) result_ptr;
+
+ size_t num_classes = result->dims.dim_sizes[1];
+ float* data = (float*) result->host_data;
+
+
+ int it_count = end - start;
+ for(int i = 0; i < it_count; i++){
+
+ int chosen = 0;
+ for (int id = 1; id < num_classes; ++id){
+ if (data[i * num_classes + chosen] < data[i * num_classes + id]) chosen = id;
+ }
+
+ predictedLabels[start + i] = chosen;
+ classConfs[start + i] = data[i * num_classes + chosen];
+ }
+
+
+}
+
+
+void dumpClassConfsAndLabels(float* classConfs,
+ int* predictedLabels,
+ uint32_t* goldLabels,
+ int test_input_size){
+
+ FILE* labels_fp = fopen("predicted_confs_labels.txt", "w+");
+
+ for (int i = 0; i < test_input_size; i++){
+
+ int label = predictedLabels[i];
+ int gold_label = (int) goldLabels[i];
+ printf ("gold_label = %u \n", goldLabels[i]);
+ float conf = classConfs[i];
+
+ std::ostringstream ss;
+ ss << std::fixed << conf;
+ std::string print_str = ss.str();
+ fwrite(print_str.c_str(), 1, print_str.length(), labels_fp);
+ fwrite(" ", 1, 1, labels_fp);
+
+
+ std::ostringstream label_ss;
+ label_ss << label;
+ std::string label_str = label_ss.str();
+ fwrite(label_str.c_str(), 1, label_str.length(), labels_fp);
+ fwrite(" ", 1, 1, labels_fp);
+
+
+ std::ostringstream gold_ss;
+ gold_ss << gold_label;
+ std::string gold_str = gold_ss.str();
+ fwrite(gold_str.c_str(), 1, gold_str.length(), labels_fp);
+ fwrite("\n", 1, 1, labels_fp);
+
+
+ }
+
+ fclose(labels_fp);
+}
+
+
#endif
diff --git a/llvm/projects/hpvm-tensor-rt/dnn_sources/src/promise/alexnet_promise.cc b/llvm/projects/hpvm-tensor-rt/dnn_sources/src/promise/alexnet_promise.cc
index 2529e8eabf..a40add25e1 100644
--- a/llvm/projects/hpvm-tensor-rt/dnn_sources/src/promise/alexnet_promise.cc
+++ b/llvm/projects/hpvm-tensor-rt/dnn_sources/src/promise/alexnet_promise.cc
@@ -41,10 +41,18 @@ int main(int argc, char* argv[]){
offset = atoi(argv[5]);
}
+ bool shouldDumpClassConf = false;
+ float* classConfs;
+ int* predictedLabels;
+ if(argc > 6){
+ shouldDumpClassConf = true;
+ classConfs = (float*) malloc(sizeof(float) * test_input_size);
+ predictedLabels = (int*) malloc(sizeof(int) * test_input_size);
+ }
+
llvm_hpvm_initTensorRt(0);
-
int missed = 0;
for (int i = 0 ; i < total_runs; i++){
@@ -58,11 +66,13 @@ int main(int argc, char* argv[]){
int batch_count = test_input_size / batch_size;
float final_accuracy = 0.0;
+ std::string dir_prefix = std::string("../model_params/alexnet_cifar10_test/");
+ std::string input_path = dir_prefix + std::string("input.bin");
+ std::string labels_path = dir_prefix + std::string("labels.bin");
+ std::string labels32_path = dir_prefix + std::string("labels32.bin");
+
for(int i = 0; i < batch_count; i++){
- std::string dir_prefix = std::string("../model_params/alexnet_cifar10_test/");
- std::string input_path = dir_prefix + std::string("input.bin");
- std::string labels_path = dir_prefix + std::string("labels.bin");
std::string conv2d_1_w_path = dir_prefix + std::string("conv2d_1_w.bin");
void* conv2d_1_w = readTrainedWeights(conv2d_1_w_path.c_str(), 0,64,3,11,11);
std::string conv2d_1_b_path = dir_prefix + std::string("conv2d_1_b.bin");
@@ -107,21 +117,37 @@ int main(int argc, char* argv[]){
float accuracy = computeAccuracy2(labels, batch_size, var_6);
final_accuracy += accuracy;
- freeBatchMemory();
-
+
+ if(shouldDumpClassConf){
+ int relative_start = start - offset;
+ int relative_end = end - offset;
+ copyClassConfsAndLabels(var_6, classConfs, predictedLabels, relative_start, relative_end);
+ }
+
+
+ freeBatchMemory();
}
final_accuracy = final_accuracy / batch_count;
dumpFinalAccuracy(final_accuracy);
-
if (final_accuracy < bench_acc)
missed += 1;
+
+
+ if(shouldDumpClassConf){
+ int labels_start = offset;
+ int labels_end = offset + test_input_size;
+ uint32_t* goldLabels = readLabelsBatch3(labels32_path.c_str(), labels_start, labels_end);
+ dumpClassConfsAndLabels(classConfs, predictedLabels, goldLabels, test_input_size);
+ }
+
}
+ dumpExecutionAccuracies();
- dumpExecutionAccuracies();
+
llvm_hpvm_cleanupTensorRt();
return 0;
--
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