diff --git a/hpvm/projects/hpvm-tensor-rt/dnn_sources/include/utils.h b/hpvm/projects/hpvm-tensor-rt/dnn_sources/include/utils.h
index 7bcfda70080688387e9bb74e8d25a1174a3e7337..e3e6a864fa5128ed21ca6a1a161b3593f7bc9948 100644
--- a/hpvm/projects/hpvm-tensor-rt/dnn_sources/include/utils.h
+++ b/hpvm/projects/hpvm-tensor-rt/dnn_sources/include/utils.h
@@ -16,11 +16,10 @@
#include <string.h>
std::vector<float> run_accuracies;
-std::string model_params_path = "../../../build/model_params/";
+std::string model_params_path = "../../test/dnn_benchmarks/model_params/";
// FIXIT: Move this to debug.h and include in all files
void dumpWeightsToFile(const char *file_name, void *weights_ptr) {
-
struct Tensor *weights = (Tensor *)weights_ptr;
// Move data back to host
hpvm_request_tensor(weights, 0);
diff --git a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp16/alexnet2_cifar10_half.cc b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp16/alexnet2_cifar10_half.cc
index 8133e86ef9735932607b5548cec5910a907f7b3c..7fa76350b5ec8f95f0a27da2436b7cccbe3c21f3 100644
--- a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp16/alexnet2_cifar10_half.cc
+++ b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp16/alexnet2_cifar10_half.cc
@@ -10,10 +10,9 @@ void testCifarNet() {
std::string dir_prefix =
model_params_path + std::string("/alexnet2_cifar10/");
- 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");
-
+ std::string input_path = dir_prefix + std::string("test_input.bin");
+ std::string labels_path = dir_prefix + std::string("test_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, 32, 3, 3, 3);
@@ -119,9 +118,9 @@ void testCifarNet() {
void *gemm1biasout = tensorHalfAdd(gemm1out, dense_1_b);
void *result = tensorSoftmax(gemm1biasout);
- uint8_t *labels = readLabelsBatch(labels_path.c_str(), start, end);
+ uint32_t *labels = readLabelsBatch3(labels_path.c_str(), start, end);
- float accuracy = computeAccuracy2(labels, batch_size, result);
+ float accuracy = computeAccuracy3(labels, result);
final_accuracy += accuracy;
freeBatchMemory();
diff --git a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp16/alexnet_cifar10_half.cc b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp16/alexnet_cifar10_half.cc
index 020ad6d578bea8acae8cce5373bdf37ec7df1fd9..7d493b8720ab701f87fdd53b315da7eafecf6637 100644
--- a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp16/alexnet_cifar10_half.cc
+++ b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp16/alexnet_cifar10_half.cc
@@ -9,9 +9,8 @@ int main() {
std::string dir_prefix = model_params_path + std::string("/alexnet_cifar10/");
- 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");
+ std::string input_path = dir_prefix + std::string("test_input.bin");
+ std::string labels_path = dir_prefix + std::string("test_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);
@@ -86,9 +85,9 @@ int main() {
void *var_23 = tensorHalfAdd(var_22, dense_1_b);
void *var_24 = tensorSoftmax(var_23);
- uint8_t *labels = readLabelsBatch(labels_path.c_str(), start, end);
+ uint32_t *labels = readLabelsBatch3(labels_path.c_str(), start, end);
- float accuracy = computeAccuracy2(labels, batch_size, var_24);
+ float accuracy = computeAccuracy3(labels, var_24);
final_accuracy += accuracy;
freeBatchMemory();
diff --git a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/alexnet2_cifar10.cc b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/alexnet2_cifar10.cc
index 7e2c4be6335e3de82b0719923554e17b74732b93..287943c0bf2417beccaebbee4f6f5cddfc667549 100644
--- a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/alexnet2_cifar10.cc
+++ b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/alexnet2_cifar10.cc
@@ -8,11 +8,9 @@ void testCifarNet() {
printf("********* Alexnet2 CIFAR-10 DNN ********** \n");
- std::string dir_prefix =
- model_params_path + std::string("/alexnet2_cifar10/");
- 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");
+ std::string dir_prefix = model_params_path + std::string("/alexnet2_cifar10/");
+ std::string input_path = dir_prefix + std::string("test_input.bin");
+ std::string labels_path = dir_prefix + std::string("test_labels.bin");
std::string conv2d_1_w_path = dir_prefix + std::string("conv2d_1_w.bin");
void *conv2d_1_w =
@@ -62,8 +60,8 @@ void testCifarNet() {
startMemTracking();
- int test_input_size = 2000;
- int batch_size = 2000;
+ int test_input_size = 5000;
+ int batch_size = 1000;
int batch_count = test_input_size / batch_size;
float final_accuracy = 0.0;
@@ -119,9 +117,9 @@ void testCifarNet() {
void *gemm1biasout = tensorAdd(gemm1out, dense_1_b);
void *result = tensorSoftmax(gemm1biasout);
- uint8_t *labels = readLabelsBatch(labels_path.c_str(), start, end);
+ uint32_t *labels = readLabelsBatch3(labels_path.c_str(), start, end);
- float accuracy = computeAccuracy2(labels, batch_size, result);
+ float accuracy = computeAccuracy3(labels, result);
final_accuracy += accuracy;
freeBatchMemory();
diff --git a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/alexnet_cifar10.cc b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/alexnet_cifar10.cc
index 1cee9b4fa5dd96bf74c4662d0d8edef34f8f2282..3dfef856c6eeeb93458ee93f7bf4a8c4feb852ac 100644
--- a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/alexnet_cifar10.cc
+++ b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/alexnet_cifar10.cc
@@ -9,9 +9,9 @@ int main() {
std::string dir_prefix = model_params_path + std::string("/alexnet_cifar10/");
- 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");
+ std::string input_path = dir_prefix + std::string("test_input.bin");
+ //std::string labels_path = dir_prefix + std::string("labels.bin");
+ std::string labels32_path = dir_prefix + std::string("test_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);
@@ -86,9 +86,9 @@ int main() {
void *var_23 = tensorAdd(var_22, dense_1_b);
void *var_24 = tensorSoftmax(var_23);
- uint8_t *labels = readLabelsBatch(labels_path.c_str(), start, end);
+ uint32_t *labels = readLabelsBatch3(labels32_path.c_str(), start, end);
- float accuracy = computeAccuracy2(labels, batch_size, var_24);
+ float accuracy = computeAccuracy3(labels, var_24);
final_accuracy += accuracy;
freeBatchMemory();