From f76a605db8903b1a9b687a06ee11aeb076b48d91 Mon Sep 17 00:00:00 2001
From: Hashim Sharif <hsharif3@miranda.cs.illinois.edu>
Date: Tue, 30 Mar 2021 17:26:58 -0500
Subject: [PATCH] Updating tensorRT sources to use 'tensorUtils.h'
---
.../dnn_sources/include/utils.h | 363 ---------
.../src/fp16/alexnet2_cifar10_half.cc | 5 +-
.../src/fp16/alexnet_cifar10_half.cc | 5 +-
.../dnn_sources/src/fp16/lenet_mnist_half.cc | 3 +-
.../dnn_sources/src/fp16/mobilenet_half.cc | 5 +-
.../src/fp16/resnet18_cifar10_half.cc | 5 +-
.../src/fp16/vgg16_cifar100_half.cc | 5 +-
.../src/fp16/vgg16_cifar10_half.cc | 5 +-
.../dnn_sources/src/fp32/alexnet2_cifar10.cc | 5 +-
.../dnn_sources/src/fp32/alexnet_cifar10.cc | 5 +-
.../dnn_sources/src/fp32/alexnet_imagenet.cc | 3 +-
.../dnn_sources/src/fp32/lenet_mnist.cc | 3 +-
.../dnn_sources/src/fp32/mobilenet.cc | 4 +-
.../dnn_sources/src/fp32/resnet18_cifar10.cc | 5 +-
.../dnn_sources/src/fp32/resnet50_imagenet.cc | 5 +-
.../dnn_sources/src/fp32/vgg16_cifar10.cc | 4 +-
.../dnn_sources/src/fp32/vgg16_cifar100.cc | 5 +-
.../dnn_sources/src/fp32/vgg16_imagenet.cc | 3 +-
.../tensor_runtime/include/tensorUtils.h | 768 ++++++++++++++++++
19 files changed, 813 insertions(+), 393 deletions(-)
delete mode 100644 hpvm/projects/hpvm-tensor-rt/dnn_sources/include/utils.h
create mode 100644 hpvm/projects/hpvm-tensor-rt/tensor_runtime/include/tensorUtils.h
diff --git a/hpvm/projects/hpvm-tensor-rt/dnn_sources/include/utils.h b/hpvm/projects/hpvm-tensor-rt/dnn_sources/include/utils.h
deleted file mode 100644
index 61fd362afc..0000000000
--- a/hpvm/projects/hpvm-tensor-rt/dnn_sources/include/utils.h
+++ /dev/null
@@ -1,363 +0,0 @@
-
-// Header guards
-#ifndef UTILS_HEADER
-#define UTILS_HEADER
-
-#include <stdio.h>
-#include <stdlib.h>
-#include <unistd.h>
-#include <fcntl.h>
-#include <sstream>
-#include <vector>
-#include <bits/stdc++.h>
-#include <tensor_runtime.h>
-#include <tensor.h>
-#include <cmath>
-#include <string.h>
-
-std::vector<float> run_accuracies;
-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);
-
- FILE *fp = fopen(file_name, "wb");
- if (fp == NULL) {
- printf("File %s could not be created. Check if directory exists \n",
- file_name);
- abort();
- }
-
- fclose(fp);
-}
-
-void fillTensorWithOnes(void *tensor_ptr) {
-
- struct Tensor *tensor = (struct Tensor *)tensor_ptr;
-
- hpvm_request_tensor(tensor, 0);
-
- // 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; i++) {
- data_arr[i] = 1.0;
- }
- }
-}
-
-void fillWithOnesAndTwos(void *tensor_ptr) {
-
- struct Tensor *tensor = (struct Tensor *)tensor_ptr;
-
- hpvm_request_tensor(tensor, 0);
-
- // 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; 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;
- }*/
- }
-}
-
-void fillTensorWithVal(void *tensor_ptr, float target_value) {
-
- struct Tensor *tensor = (struct Tensor *)tensor_ptr;
-
- hpvm_request_tensor(tensor, 0);
-
- // 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; i++) {
- data_arr[i] = target_value;
- }
- }
-}
-
-void fillTensorWithNegOnes(void *tensor_ptr) {
-
- struct Tensor *tensor = (struct Tensor *)tensor_ptr;
-
- hpvm_request_tensor(tensor, 0);
-
- // 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; i++) {
- data_arr[i] = -1.0;
- }
- }
-}
-
-void printTensorValues(void *tensor_ptr) {
-
- struct Tensor *tensor = (struct Tensor *)tensor_ptr;
-
- hpvm_request_tensor(tensor, 0);
-
- // printing is specific to the floating point type
- if (tensor->data_type != CUDNN_DATA_FLOAT) {
- // printf("\n WARNING: The tensor is non-float type tensor \n\n");
- }
-
- float *data_arr = (float *)tensor->host_data;
-
- for (unsigned int i = 0; i < tensor->num_elems; i++) {
- printf("%f,", data_arr[i]);
- }
-
- printf("\n");
-}
-
-void printTensorDims(void *tensor_ptr) {
-
- struct Tensor *tensor = (struct Tensor *)tensor_ptr;
-
- printf("Num_elems = %lu \n", tensor->num_elems);
- for (int i = 0; i < tensor->dims.num_dims; i++) {
- printf("dim[%d] = %lu \n", i, tensor->dims.dim_sizes[i]);
- }
-}
-
-struct Tensor *readTrainedWeights(const char *file_name, int data_type,
- long int dim1_size, long int dim2_size,
- long int dim3_size, long int dim4_size) {
-
- // FIXIT: Don't assume floating point types
- int type_size = 4; // NOTE: Assuming floating point tensors
- long int num_elems = dim1_size * dim2_size * dim3_size * dim4_size;
- long int size_in_bytes =
- type_size * dim1_size * dim2_size * dim3_size * dim4_size;
- float *tensor_data = (float *)malloc(sizeof(float) * num_elems);
- // printf("size_in_bytes = %lu \n", size_in_bytes);
-
- int file_header_size = 0;
-
- FILE *file = fopen(file_name, "rb");
- if (file == NULL) {
- printf("Data file %s is not found. Aborting... \n", file_name);
- abort();
- }
-
- fseek(file, file_header_size, SEEK_CUR); // Skipping the file header
- fread(tensor_data, 1, size_in_bytes, file);
- fclose(file);
-
- struct Tensor *weights = (struct Tensor *)create4DTensor(
- data_type, nchw, dim1_size, dim2_size, dim3_size, dim4_size);
-
- initTensorData(weights, tensor_data, size_in_bytes);
- // compareValues(weights, tensor_data, num_elems);
- free(tensor_data);
-
- return weights;
-}
-
-struct Tensor *readInputBatch(const char *file_name, int data_type,
- long int start, long int end, long int dim2_size,
- long int dim3_size, long int dim4_size) {
-
- long int dim1_size = end - start;
- // FIXIT: Don't assume floating point types
- long int type_size = 4; // NOTE: Assuming floating point tensors
- long int num_elems = dim1_size * dim2_size * dim3_size * dim4_size;
- long int size_in_bytes =
- type_size * dim1_size * dim2_size * dim3_size * dim4_size;
- float *tensor_data = (float *)malloc(sizeof(float) * num_elems);
- long int file_header_size =
- type_size * start * dim2_size * dim3_size * dim4_size;
-
- FILE *file = fopen(file_name, "rb");
- if (file == NULL) {
- printf("Data file %s is not found. Aborting... \n", file_name);
- abort();
- }
-
- fseek(file, file_header_size, SEEK_SET); // Skipping the file header
- fread(tensor_data, 1, size_in_bytes, file);
- fclose(file);
-
- struct Tensor *weights = (struct Tensor *)create4DTensor(
- data_type, nchw, dim1_size, dim2_size, dim3_size, dim4_size);
-
- initTensorData(weights, tensor_data, size_in_bytes);
- free(tensor_data);
-
- return weights;
-}
-
-uint8_t *readLabelsBatch(const char *labels_file, int start, int end) {
-
- int num_labels = end - start;
- int file_header_size = sizeof(uint8_t) * start;
-
- uint8_t *labels = (uint8_t *)malloc(sizeof(uint8_t) * num_labels);
- FILE *file = fopen(labels_file, "rb");
- if (file == NULL) {
- printf("Data file %s is not found. Aborting...\n", labels_file);
- abort();
- }
-
- fseek(file, file_header_size, SEEK_SET); // Skipping the file header
- fread(labels, 1, sizeof(uint8_t) * num_labels, file);
- fclose(file);
-
- // printf("--labels bytes_read = %lu \n", bytes_read);
- return labels;
-}
-
-uint32_t *readLabelsBatch3(const char *labels_file, int start, int end) {
-
- int num_labels = end - start;
- int file_header_size = sizeof(uint32_t) * start;
-
- uint32_t *labels = (uint32_t *)malloc(sizeof(uint32_t) * num_labels);
- FILE *file = fopen(labels_file, "rb");
- if (file == NULL) {
- printf("Data file %s is not found. Aborting...\n", labels_file);
- abort();
- }
-
- fseek(file, file_header_size, SEEK_SET); // Skipping the file header
- fread(labels, 1, sizeof(uint32_t) * num_labels, file);
- fclose(file);
-
- return labels;
-}
-
-// NOTE: batch_size and num_classes are Unused arguments
-float computeAccuracy2(uint8_t *labels, int batch_size, void *result_ptr,
- size_t num_classes = 10) {
-
- struct Tensor *result = (struct Tensor *)result_ptr;
-
- size_t batch_dim = result->dims.dim_sizes[0];
- num_classes = result->dims.dim_sizes[1];
- float *data = (float *)result->host_data;
- int num_errors = 0;
-
- printf("batch_dim = %lu, channels = %lu \n", batch_dim, num_classes);
-
- for (unsigned int i = 0; i < batch_dim; i++) {
-
- int chosen = 0;
- for (size_t id = 1; id < num_classes; ++id) {
- if (data[i * num_classes + chosen] < data[i * num_classes + id])
- chosen = id;
- }
-
- if (chosen != labels[i])
- num_errors++;
- }
-
- float accuracy = ((batch_dim - num_errors) * 1.0 / batch_dim * 1.0) * 100.0;
- printf("****** Accuracy = %f \n\n", accuracy);
-
- FILE *fp = fopen("final_accuracy", "w+");
- if (fp != NULL) {
-
- std::ostringstream ss;
- ss << std::fixed << accuracy;
- std::string print_str = ss.str();
-
- fwrite(print_str.c_str(), 1, print_str.length(), fp);
- }
-
- fclose(fp);
-
- return accuracy;
-}
-
-float computeAccuracy3(uint32_t *labels, void *result_ptr) {
-
- struct Tensor *result = (struct Tensor *)result_ptr;
-
- size_t batch_dim = result->dims.dim_sizes[0];
- size_t num_classes = result->dims.dim_sizes[1];
- float *data = (float *)result->host_data;
- int num_errors = 0;
-
- printf("batch_dim = %lu, num_classes = %lu \n", batch_dim, num_classes);
-
- for (size_t i = 0; i < batch_dim; i++) {
-
- uint32_t chosen = 0;
- for (size_t id = 1; id < num_classes; ++id) {
- if (data[i * num_classes + chosen] < data[i * num_classes + id])
- chosen = id;
- }
-
- if (chosen != labels[i])
- num_errors++;
- }
-
- float accuracy = ((batch_dim - num_errors) * 1.0 / batch_dim * 1.0) * 100.0;
- printf("****** Accuracy = %f \n\n", accuracy);
-
- FILE *fp = fopen("final_accuracy", "w+");
- if (fp != NULL) {
-
- std::ostringstream ss;
- ss << std::fixed << accuracy;
- std::string print_str = ss.str();
-
- fwrite(print_str.c_str(), 1, print_str.length(), fp);
- }
-
- fclose(fp);
-
- return accuracy;
-}
-
-void dumpFinalAccuracy(float accuracy) {
-
- printf("\n\n **** Final Accuracy = %f \n", accuracy);
-
- FILE *fp = fopen("final_accuracy", "w+");
- if (fp != NULL) {
- std::ostringstream ss;
- ss << std::fixed << accuracy;
- std::string print_str = ss.str();
-
- fwrite(print_str.c_str(), 1, print_str.length(), fp);
- }
-
- fclose(fp);
-
- run_accuracies.push_back(accuracy);
-}
-
-void dumpExecutionAccuracies() {
-
- FILE *fp = fopen("run_accuracies.txt", "w+");
- if (fp != NULL) {
- for (size_t i = 0; i < run_accuracies.size(); i++) {
- float accuracy = run_accuracies[i];
- std::ostringstream ss;
- ss << std::fixed << accuracy;
- std::string print_str = ss.str();
- fwrite(print_str.c_str(), 1, print_str.length(), fp);
- fwrite("\n", 1, 1, fp);
- }
- }
-
- fclose(fp);
-}
-#endif
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 0b34403529..206b4beed7 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
@@ -1,7 +1,8 @@
-#include "../../../tensor_runtime/include/tensor_runtime.h"
-#include "../../include/utils.h"
+#include "tensor_runtime.h"
+#include "tensorUtils.h"
+
/* NOTE: Reference Architecture to use for profiling */
void testCifarNet() {
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 7d493b8720..eaf666b374 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
@@ -1,7 +1,8 @@
-#include "../../../tensor_runtime/include/tensor_runtime.h"
-#include "../../include/utils.h"
+#include "tensor_runtime.h"
+#include "tensorUtils.h"
+
int main() {
diff --git a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp16/lenet_mnist_half.cc b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp16/lenet_mnist_half.cc
index 03dc905bbf..9fcc382aed 100644
--- a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp16/lenet_mnist_half.cc
+++ b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp16/lenet_mnist_half.cc
@@ -1,7 +1,8 @@
#include "tensor_runtime.h"
-#include "utils.h"
+#include "tensorUtils.h"
+
/* NOTE: Reference Architecture to use for profiling */
void testLenetTanh() {
diff --git a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp16/mobilenet_half.cc b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp16/mobilenet_half.cc
index d6eaef7557..7857f210f9 100644
--- a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp16/mobilenet_half.cc
+++ b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp16/mobilenet_half.cc
@@ -1,7 +1,8 @@
-#include "../../../tensor_runtime/include/tensor_runtime.h"
-#include "../../include/utils.h"
+#include "tensor_runtime.h"
+#include "tensorUtils.h"
+
int main() {
diff --git a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp16/resnet18_cifar10_half.cc b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp16/resnet18_cifar10_half.cc
index 40e128eb8a..40745c9986 100644
--- a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp16/resnet18_cifar10_half.cc
+++ b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp16/resnet18_cifar10_half.cc
@@ -1,7 +1,8 @@
-#include "../../../tensor_runtime/include/tensor_runtime.h"
-#include "../../include/utils.h"
+#include "tensor_runtime.h"
+#include "tensorUtils.h"
+
int main() {
diff --git a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp16/vgg16_cifar100_half.cc b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp16/vgg16_cifar100_half.cc
index eb3275b830..de5657f63d 100644
--- a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp16/vgg16_cifar100_half.cc
+++ b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp16/vgg16_cifar100_half.cc
@@ -1,7 +1,8 @@
-#include "../../../tensor_runtime/include/tensor_runtime.h"
-#include "../../include/utils.h"
+#include "tensor_runtime.h"
+#include "tensorUtils.h"
+
int main() {
diff --git a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp16/vgg16_cifar10_half.cc b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp16/vgg16_cifar10_half.cc
index 2a4b5a6a91..7b4318c895 100644
--- a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp16/vgg16_cifar10_half.cc
+++ b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp16/vgg16_cifar10_half.cc
@@ -1,7 +1,8 @@
-#include "../../../tensor_runtime/include/tensor_runtime.h"
-#include "../../include/utils.h"
+#include "tensor_runtime.h"
+#include "tensorUtils.h"
+
int main() {
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 396e9f11ca..b69596f8f5 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
@@ -1,7 +1,8 @@
+#include "tensor_runtime.h"
+#include "tensorUtils.h"
+
-#include "../../tensor_runtime/include/tensor_runtime.h"
-#include "../include/utils.h"
/* NOTE: Reference Architecture to use for profiling */
void testCifarNet() {
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 6005120785..2283448bc3 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
@@ -1,7 +1,8 @@
-#include "../../tensor_runtime/include/tensor_runtime.h"
-#include "../include/utils.h"
+#include "tensor_runtime.h"
+#include "tensorUtils.h"
+
int main() {
diff --git a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/alexnet_imagenet.cc b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/alexnet_imagenet.cc
index 29909e5938..cb01f8ba3d 100644
--- a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/alexnet_imagenet.cc
+++ b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/alexnet_imagenet.cc
@@ -1,7 +1,8 @@
#include "tensor_runtime.h"
-#include "utils.h"
+#include "tensorUtils.h"
+
int main() {
diff --git a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/lenet_mnist.cc b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/lenet_mnist.cc
index 61a0eeb441..2294c34df1 100644
--- a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/lenet_mnist.cc
+++ b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/lenet_mnist.cc
@@ -1,7 +1,8 @@
#include "tensor_runtime.h"
-#include "../include/utils.h"
+#include "tensorUtils.h"
+
int total_runs = 1;
diff --git a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/mobilenet.cc b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/mobilenet.cc
index 85849126cf..23a738ef13 100644
--- a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/mobilenet.cc
+++ b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/mobilenet.cc
@@ -1,7 +1,7 @@
-#include "../../tensor_runtime/include/tensor_runtime.h"
-#include "../include/utils.h"
+#include "tensor_runtime.h"
+#include "tensorUtils.h"
int main() {
diff --git a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/resnet18_cifar10.cc b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/resnet18_cifar10.cc
index bd3dd7dc1e..fffb02c605 100644
--- a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/resnet18_cifar10.cc
+++ b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/resnet18_cifar10.cc
@@ -1,7 +1,8 @@
-#include "../../../tensor_runtime/include/tensor_runtime.h"
-#include "../../include/utils.h"
+#include "tensor_runtime.h"
+#include "tensorUtils.h"
+
int main() {
diff --git a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/resnet50_imagenet.cc b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/resnet50_imagenet.cc
index 0cccb124b0..110acf5c89 100644
--- a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/resnet50_imagenet.cc
+++ b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/resnet50_imagenet.cc
@@ -1,7 +1,8 @@
-#include "../../tensor_runtime/include/tensor_runtime.h"
-#include "../include/utils.h"
+#include "tensor_runtime.h"
+#include "tensorUtils.h"
+
int main() {
diff --git a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/vgg16_cifar10.cc b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/vgg16_cifar10.cc
index 813874f0ed..1d2602ab28 100644
--- a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/vgg16_cifar10.cc
+++ b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/vgg16_cifar10.cc
@@ -1,7 +1,7 @@
-#include "../../tensor_runtime/include/tensor_runtime.h"
-#include "../include/utils.h"
+#include "tensor_runtime.h"
+#include "tensorUtils.h"
int main() {
diff --git a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/vgg16_cifar100.cc b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/vgg16_cifar100.cc
index 84164bf24b..85fe400f7e 100644
--- a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/vgg16_cifar100.cc
+++ b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/vgg16_cifar100.cc
@@ -1,7 +1,8 @@
-#include "../../tensor_runtime/include/tensor_runtime.h"
-#include "../include/utils.h"
+#include "tensor_runtime.h"
+#include "tensorUtils.h"
+
int main() {
diff --git a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/vgg16_imagenet.cc b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/vgg16_imagenet.cc
index eca833b08f..4ab8707a0d 100644
--- a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/vgg16_imagenet.cc
+++ b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/vgg16_imagenet.cc
@@ -1,7 +1,8 @@
#include "tensor_runtime.h"
-#include "utils.h"
+#include "tensorUtils.h"
+
int main() {
diff --git a/hpvm/projects/hpvm-tensor-rt/tensor_runtime/include/tensorUtils.h b/hpvm/projects/hpvm-tensor-rt/tensor_runtime/include/tensorUtils.h
new file mode 100644
index 0000000000..dd7942e288
--- /dev/null
+++ b/hpvm/projects/hpvm-tensor-rt/tensor_runtime/include/tensorUtils.h
@@ -0,0 +1,768 @@
+
+// Header guards
+#ifndef UTILS_HEADER
+#define UTILS_HEADER
+
+#include <sstream>
+#include <vector>
+#include <bits/stdc++.h>
+#include <tensor_runtime.h>
+#include <tensor.h>
+#include <cmath>
+
+
+std::vector<float> run_accuracies;
+std::string model_params_path = "../../test/dnn_benchmarks/model_params/";
+
+
+void printTensorInfo(void *tensor_ptr) {
+
+ struct Tensor *tensor = (struct Tensor *)tensor_ptr;
+
+ if (tensor->gpu_data != NULL) {
+ printf("Successful cudaMalloc \n");
+ }
+
+ printf("tensor dims = %d \n", tensor->dims.num_dims);
+ printf("dim1_size = %lu \n", tensor->dims.dim_sizes[0]);
+ printf("dim2_size = %lu \n", tensor->dims.dim_sizes[1]);
+ printf("num_elems = %lu \n", tensor->num_elems);
+}
+
+// FIXIT: Move this to debug.h and include in all files
+void dumpWeightsToFile(char *file_name, void *weights_ptr) {
+
+ struct Tensor *weights = (Tensor *)weights_ptr;
+ // Move data back to host
+ hpvm_request_tensor(weights, 0);
+
+ FILE *fp = fopen(file_name, "wb");
+ if (fp == NULL) {
+ printf("File %s could not be created. Check if directory exists \n",
+ file_name);
+ abort();
+ }
+
+ // printf("size_in_bytes = %lu \n", weights->size_in_bytes);
+ size_t bytes_written =
+ fwrite(weights->host_data, 1, weights->size_in_bytes, fp);
+ // printf("bytes_written = %lu \n", bytes_written);
+ fclose(fp);
+}
+
+void fillTensorWithOnes(void *tensor_ptr) {
+
+ struct Tensor *tensor = (struct Tensor *)tensor_ptr;
+
+ hpvm_request_tensor(tensor, 0);
+
+ // 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; i++) {
+ data_arr[i] = 1.0;
+ }
+ }
+}
+
+void fillWithOnesAndTwos(void *tensor_ptr) {
+
+ struct Tensor *tensor = (struct Tensor *)tensor_ptr;
+
+ hpvm_request_tensor(tensor, 0);
+
+ // 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++) {
+ data_arr[i] = 1.0;
+ }
+
+ for (unsigned int i = tensor->num_elems / 2; i < tensor->num_elems; i++) {
+ data_arr[i] = 2.0;
+ }
+ }
+}
+
+void fillTensorWithVal(void *tensor_ptr, float target_value) {
+
+ struct Tensor *tensor = (struct Tensor *)tensor_ptr;
+
+ hpvm_request_tensor(tensor, 0);
+
+ // 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; i++) {
+ data_arr[i] = target_value;
+ }
+ }
+}
+
+void fillTensorWithNegOnes(void *tensor_ptr) {
+
+ struct Tensor *tensor = (struct Tensor *)tensor_ptr;
+
+ hpvm_request_tensor(tensor, 0);
+
+ // 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; i++) {
+ data_arr[i] = -1.0;
+ }
+ }
+}
+
+void fillTensorVals(void *tensor_ptr) {
+
+ struct Tensor *tensor = (struct Tensor *)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; i++) {
+ data_arr[i] = i + 1;
+ }
+ }
+}
+
+void printTensorValues(void *tensor_ptr) {
+
+ struct Tensor *tensor = (struct Tensor *)tensor_ptr;
+
+ hpvm_request_tensor(tensor, 0);
+
+ // printing 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; i++) {
+ printf("%f,", data_arr[i]);
+ }
+ }
+
+ printf("\n");
+}
+
+void printTensorDims(void *tensor_ptr) {
+
+ struct Tensor *tensor = (struct Tensor *)tensor_ptr;
+
+ printf("Num_elems = %lu \n", tensor->num_elems);
+ for (int i = 0; i < tensor->dims.num_dims; i++) {
+ printf("dim[%d] = %lu \n", i, tensor->dims.dim_sizes[i]);
+ }
+}
+
+void compareTensors(void *tensor1_ptr, void *tensor2_ptr) {
+
+ struct Tensor *tensor1 = (struct Tensor *)tensor1_ptr;
+ struct Tensor *tensor2 = (struct Tensor *)tensor2_ptr;
+
+ hpvm_request_tensor(tensor1, 0);
+ hpvm_request_tensor(tensor2, 0);
+
+ float *tensor_data1 = (float *)tensor1->host_data;
+ float *tensor_data2 = (float *)tensor2->host_data;
+
+ for (unsigned int i = 0; i < tensor1->num_elems; i++) {
+ if (tensor_data1[i] != tensor_data2[i]) {
+ printf("Tensor data mismatch at index %d \n", i);
+ abort();
+ }
+ }
+}
+
+void compareValues(void *tensor_ptr, float *data, size_t num_elems) {
+
+ struct Tensor *tensor = (struct Tensor *)tensor_ptr;
+
+ hpvm_request_tensor(tensor, 0);
+
+ float *tensor_data = (float *)tensor->host_data;
+ for (unsigned int i = 0; i < num_elems; i++) {
+ if (tensor_data[i] != data[i]) {
+ printf("Tensor data mismatch");
+ abort();
+ }
+ }
+}
+
+
+/*
+void *readInputTensor(const char *file_name, int data_type,
+ int dim1_size, int dim2_size, int dim3_size, int dim4_size) {
+
+ long int type_size = 4; // NOTE: Assuming floating point tensors
+ long int num_elems = dim1_size * dim2_size * dim3_size * dim4_size;
+ long int size_in_bytes = type_size * dim1_size * dim2_size * dim3_size * dim4_size;
+ uint8_t *file_data = (uint8_t *)malloc(sizeof(char) * num_elems);
+ float *tensor_data = (float *)malloc(sizeof(float) * num_elems);
+ long int file_header_size = 16;
+
+ FILE *file = fopen(file_name, "rb");
+ if (file == NULL) {
+ printf("Data file %s is not found. Aborting... \n", file_name);
+ abort();
+ }
+
+ fseek(file, file_header_size, SEEK_CUR); // Skipping the file header
+ size_t bytes_read = fread(file_data, 1, sizeof(uint8_t) * num_elems, file);
+
+ fclose(file);
+
+ for (size_t i = 0; i < num_elems; ++i) {
+ tensor_data[i] = (float)file_data[i] / 255.0f;
+ }
+
+ // NOTE: Using NCHW format
+ struct Tensor *input = (struct Tensor *)create4DTensor(
+ data_type, nchw, dim1_size, dim2_size, dim3_size, dim4_size);
+
+ initTensorData(input, tensor_data, size_in_bytes);
+ // compareValues(input, tensor_data, num_elems);
+
+ return input;
+}
+*/
+
+
+//*** FIXIT: Move this to CPU-only
+struct Tensor *readTrainedWeightsCPU(const char *file_name, int data_type,
+ int dim1_size, int dim2_size,
+ int dim3_size, int dim4_size) {
+
+ // FIXIT: Don't assume floating point types
+ int type_size = 4; // NOTE: Assuming floating point tensors
+ long int num_elems = dim1_size * dim2_size * dim3_size * dim4_size;
+ long int size_in_bytes =
+ type_size * dim1_size * dim2_size * dim3_size * dim4_size;
+ float *tensor_data = (float *)malloc(sizeof(float) * num_elems);
+ int file_header_size = 0;
+
+ FILE *file = fopen(file_name, "rb");
+ if (file == NULL) {
+ printf("Data file %s is not found. Aborting... \n", file_name);
+ abort();
+ }
+
+ fseek(file, file_header_size, SEEK_CUR); // Skipping the file header
+ size_t bytes_read = fread(tensor_data, 1, size_in_bytes, file);
+
+ printf("size in bytes = %lu, bytes read = %lu \n", size_in_bytes, bytes_read);
+
+ fclose(file);
+
+ struct Tensor *weights = (struct Tensor *)create4DTensor(
+ data_type, nchw, dim1_size, dim2_size, dim3_size, dim4_size);
+
+ initTensorData(weights, tensor_data, size_in_bytes);
+ // compareValues(weights, tensor_data, num_elems);
+ free(tensor_data);
+
+ return weights;
+}
+
+struct Tensor *readTrainedWeights(const char *file_name, int data_type,
+ long int dim1_size, long int dim2_size,
+ long int dim3_size, long int dim4_size) {
+
+ // FIXIT: Don't assume floating point types
+ int type_size = 4; // NOTE: Assuming floating point tensors
+ long int num_elems = dim1_size * dim2_size * dim3_size * dim4_size;
+ long int size_in_bytes =
+ type_size * dim1_size * dim2_size * dim3_size * dim4_size;
+ float *tensor_data = (float *)malloc(sizeof(float) * num_elems);
+ printf("size_in_bytes = %lu \n", size_in_bytes);
+
+ int file_header_size = 0;
+
+ FILE *file = fopen(file_name, "rb");
+ if (file == NULL) {
+ printf("Data file %s is not found. Aborting... \n", file_name);
+ abort();
+ }
+
+ fseek(file, file_header_size, SEEK_CUR); // Skipping the file header
+ size_t bytes_read = fread(tensor_data, 1, size_in_bytes, file);
+
+ // printf("size in bytes = %lu, bytes read = %lu \n", size_in_bytes,
+ // bytes_read);
+
+ fclose(file);
+
+ struct Tensor *weights = (struct Tensor *)create4DTensor(
+ data_type, nchw, dim1_size, dim2_size, dim3_size, dim4_size);
+
+ initTensorData(weights, tensor_data, size_in_bytes);
+ // compareValues(weights, tensor_data, num_elems);
+ free(tensor_data);
+
+ return weights;
+}
+
+struct Tensor *readInputBatch(const char *file_name, long data_type,
+ long start, long end,
+ long dim2_size, long dim3_size, long dim4_size) {
+
+ long int dim1_size = end - start;
+ // FIXIT: Don't assume floating point types
+ long int type_size = 4; // NOTE: Assuming floating point tensors
+ long int num_elems = dim1_size * dim2_size * dim3_size * dim4_size;
+ long int size_in_bytes =
+ type_size * dim1_size * dim2_size * dim3_size * dim4_size;
+ float *tensor_data = (float *)malloc(sizeof(float) * num_elems);
+ long int file_header_size =
+ type_size * start * dim2_size * dim3_size * dim4_size;
+
+ FILE *file = fopen(file_name, "rb");
+ if (file == NULL) {
+ printf("Data file %s is not found. Aborting... \n", file_name);
+ abort();
+ }
+
+ fseek(file, file_header_size, SEEK_SET); // Skipping the file header
+ size_t bytes_read = fread(tensor_data, 1, size_in_bytes, file);
+
+ fclose(file);
+
+ // printf ("FIXED input BATCH read \n");
+
+ struct Tensor *weights = (struct Tensor *)create4DTensor(
+ data_type, nchw, dim1_size, dim2_size, dim3_size, dim4_size);
+
+ initTensorData(weights, tensor_data, size_in_bytes);
+ free(tensor_data);
+
+ return weights;
+}
+
+uint8_t *readLabels(const char *labels_file, int num_labels) {
+
+ uint8_t *labels = (uint8_t *)malloc(sizeof(uint8_t) * num_labels);
+ FILE *file = fopen(labels_file, "rb");
+ if (file == NULL) {
+ printf("Data file %s is not found. Aborting...\n", labels_file);
+ abort();
+ }
+
+ size_t bytes_read = fread(labels, 1, sizeof(uint8_t) * num_labels, file);
+
+ fclose(file);
+
+ return labels;
+}
+
+uint32_t *readLabels3(const char *labels_file, int num_labels) {
+
+ uint32_t *labels = (uint32_t *)malloc(sizeof(uint32_t) * num_labels);
+ FILE *file = fopen(labels_file, "rb");
+ if (file == NULL) {
+ printf("Data file %s is not found. Aborting...\n", labels_file);
+ abort();
+ }
+
+ size_t bytes_read = fread(labels, 1, sizeof(uint32_t) * num_labels, file);
+
+ fclose(file);
+
+ return labels;
+}
+
+uint8_t *readLabelsBatch(const char *labels_file, int start, int end) {
+
+ int num_labels = end - start;
+ int file_header_size = sizeof(uint8_t) * start;
+
+ uint8_t *labels = (uint8_t *)malloc(sizeof(uint8_t) * num_labels);
+ FILE *file = fopen(labels_file, "rb");
+ if (file == NULL) {
+ printf("Data file %s is not found. Aborting...\n", labels_file);
+ abort();
+ }
+
+ fseek(file, file_header_size, SEEK_SET); // Skipping the file header
+
+ size_t bytes_read = fread(labels, 1, sizeof(uint8_t) * num_labels, file);
+
+ fclose(file);
+
+ // printf("--labels bytes_read = %lu \n", bytes_read);
+ return labels;
+}
+
+uint32_t *readLabelsBatch3(const char *labels_file, int start, int end) {
+
+ int num_labels = end - start;
+ int file_header_size = sizeof(uint32_t) * start;
+
+ uint32_t *labels = (uint32_t *)malloc(sizeof(uint32_t) * num_labels);
+ FILE *file = fopen(labels_file, "rb");
+ if (file == NULL) {
+ printf("Data file %s is not found. Aborting...\n", labels_file);
+ abort();
+ }
+
+ fseek(file, file_header_size, SEEK_SET); // Skipping the file header
+
+ size_t bytes_read = fread(labels, 1, sizeof(uint32_t) * num_labels, file);
+
+ fclose(file);
+
+ return labels;
+}
+
+
+/*void computeAccuracy(const char *labels_file, int num_labels,
+ void *result_ptr) {
+
+ struct Tensor *result = (struct Tensor *)result_ptr;
+
+ uint8_t *labels = readLabels(labels_file, num_labels);
+ size_t batch_dim = result->dims.dim_sizes[0];
+ size_t channels = result->dims.dim_sizes[1];
+ float *data = (float *)result->host_data;
+ int num_errors = 0;
+
+ for (int i = 0; i < batch_dim; i++) {
+ int chosen = 0;
+ for (int id = 1; id < 10; ++id) {
+ if (data[i * channels + chosen] < data[i * channels + id])
+ chosen = id;
+ }
+
+ // printf("chosen = %d, label = %d \n", chosen, labels[i]);
+ if (chosen != labels[i])
+ num_errors++;
+ }
+
+ float accuracy = ((batch_dim - num_errors) * 1.0 / batch_dim * 1.0) * 100.0;
+ printf("****** Accuracy = %f \n\n", accuracy);
+
+ FILE *fp = fopen("final_accuracy", "w+");
+ if (fp != NULL) {
+
+ std::ostringstream ss;
+ ss << std::fixed << accuracy;
+ std::string print_str = ss.str();
+
+ fwrite(print_str.c_str(), 1, print_str.length(), fp);
+ fclose(fp);
+ }
+}
+*/
+
+
+// NOTE: batch_size and num_classes are Unused arguments
+float computeAccuracy2(uint8_t *labels, int batch_size, void *result_ptr,
+ size_t num_classes = 10) {
+
+ struct Tensor *result = (struct Tensor *)result_ptr;
+
+ size_t batch_dim = result->dims.dim_sizes[0];
+ num_classes = result->dims.dim_sizes[1];
+ float *data = (float *)result->host_data;
+ int num_errors = 0;
+
+ printf("batch_dim = %lu, channels = %lu \n", batch_dim, num_classes);
+
+ for (unsigned int i = 0; i < batch_dim; i++) {
+
+ int chosen = 0;
+ for (unsigned int id = 1; id < num_classes; ++id) {
+ if (data[i * num_classes + chosen] < data[i * num_classes + id])
+ chosen = id;
+ }
+
+ if (chosen != labels[i])
+ num_errors++;
+ }
+
+ float accuracy = ((batch_dim - num_errors) * 1.0 / batch_dim * 1.0) * 100.0;
+ printf("****** Accuracy = %f \n\n", accuracy);
+
+ FILE *fp = fopen("final_accuracy", "w+");
+ if (fp != NULL) {
+
+ std::ostringstream ss;
+ ss << std::fixed << accuracy;
+ std::string print_str = ss.str();
+
+ fwrite(print_str.c_str(), 1, print_str.length(), fp);
+ }
+
+ fclose(fp);
+
+ return accuracy;
+}
+
+float computeAccuracy3(uint32_t *labels, void *result_ptr) {
+
+ struct Tensor *result = (struct Tensor *)result_ptr;
+
+ size_t batch_dim = result->dims.dim_sizes[0];
+ size_t num_classes = result->dims.dim_sizes[1];
+ float *data = (float *)result->host_data;
+ int num_errors = 0;
+
+ printf("batch_dim = %lu, num_classes = %lu \n", batch_dim, num_classes);
+
+ for (unsigned int i = 0; i < batch_dim; 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;
+ }
+
+ if (chosen != labels[i])
+ num_errors++;
+ }
+
+ float accuracy = ((batch_dim - num_errors) * 1.0 / batch_dim * 1.0) * 100.0;
+ printf("****** Accuracy = %f \n\n", accuracy);
+
+ FILE *fp = fopen("final_accuracy", "w+");
+ if (fp != NULL) {
+
+ std::ostringstream ss;
+ ss << std::fixed << accuracy;
+ std::string print_str = ss.str();
+
+ fwrite(print_str.c_str(), 1, print_str.length(), fp);
+ }
+
+ fclose(fp);
+
+ return accuracy;
+}
+
+struct ClassProb {
+ float prob;
+ int index;
+};
+
+bool descendFloatComp(ClassProb obj1, ClassProb obj2) {
+ return obj1.prob > obj2.prob;
+}
+
+float computeTop5Accuracy(uint8_t *labels, int num_labels, void *result_ptr,
+ unsigned num_classes = 10) {
+
+ struct Tensor *result = (struct Tensor *)result_ptr;
+
+ size_t batch_dim = result->dims.dim_sizes[0];
+ size_t channels = result->dims.dim_sizes[1];
+ float *data = (float *)result->host_data;
+ int num_errors = 0;
+
+ printf("batch_dim = %lu, channels = %lu \n", batch_dim, channels);
+
+ for (int i = 0; i < num_labels; i++) {
+
+ std::vector<ClassProb> elem_probs;
+ for (int id = 0; id < num_classes; ++id) {
+ ClassProb cProb;
+ cProb.prob = data[i * channels + id];
+ cProb.index = id;
+ elem_probs.push_back(cProb);
+ }
+
+ std:
+ sort(elem_probs.begin(), elem_probs.end(), descendFloatComp);
+ // Check if any of top-5 predictions matches
+ bool matched = false;
+ for (int j = 0; j < 5; j++) {
+ ClassProb cProb = elem_probs[j];
+ if (cProb.index == labels[i])
+ matched = true;
+ }
+
+ if (!matched)
+ num_errors += 1;
+ }
+
+ float accuracy = ((batch_dim - num_errors) * 1.0 / batch_dim * 1.0) * 100.0;
+ printf("****** Accuracy = %f \n\n", accuracy);
+
+ FILE *fp = fopen("final_accuracy", "w+");
+ if (fp != NULL) {
+
+ std::ostringstream ss;
+ ss << std::fixed << accuracy;
+ std::string print_str = ss.str();
+
+ fwrite(print_str.c_str(), 1, print_str.length(), fp);
+ }
+
+ fclose(fp);
+
+ return accuracy;
+}
+
+void dumpFinalAccuracy(float accuracy) {
+
+ printf("\n\n **** Final Accuracy = %f \n", accuracy);
+
+ FILE *fp = fopen("final_accuracy", "w+");
+ if (fp != NULL) {
+ std::ostringstream ss;
+ ss << std::fixed << accuracy;
+ std::string print_str = ss.str();
+
+ fwrite(print_str.c_str(), 1, print_str.length(), fp);
+ }
+
+ fclose(fp);
+
+ run_accuracies.push_back(accuracy);
+}
+
+void dumpAvgPSNR(float avg_psnr) {
+
+ FILE *fp = fopen("avg_psnr", "w+");
+ if (fp != NULL) {
+ std::ostringstream ss;
+ ss << std::fixed << avg_psnr;
+ std::string print_str = ss.str();
+ fwrite(print_str.c_str(), 1, print_str.length(), fp);
+ }
+
+ fclose(fp);
+}
+
+void dumpPSNRStd(float psnr_std) {
+
+ FILE *fp = fopen("psnr_std.txt", "w+");
+ if (fp != NULL) {
+ std::ostringstream ss;
+ ss << std::fixed << psnr_std;
+ std::string print_str = ss.str();
+ fwrite(print_str.c_str(), 1, print_str.length(), fp);
+ }
+
+ fclose(fp);
+}
+
+void dumpExecutionAccuracies() {
+
+ FILE *fp = fopen("run_accuracies.txt", "w+");
+ if (fp != NULL) {
+ for (unsigned int i = 0; i < run_accuracies.size(); i++) {
+ float accuracy = run_accuracies[i];
+ std::ostringstream ss;
+ ss << std::fixed << accuracy;
+ std::string print_str = ss.str();
+ fwrite(print_str.c_str(), 1, print_str.length(), fp);
+ fwrite("\n", 1, 1, fp);
+ }
+ }
+
+ fclose(fp);
+}
+
+float readPSNRFromFile(const char *file_name) {
+
+ float psnr;
+ FILE *pFile = fopen(file_name, "r");
+ if (pFile == NULL) {
+ printf("ERROR: psnr.txt not found! \n");
+ abort();
+ }
+
+ fscanf(pFile, "%f", &psnr);
+ printf("**** PSNR read = %f \n\n", psnr);
+ return psnr;
+}
+
+float computePSNRViolation(void *gold_ptr, void *approx_ptr,
+ float PSNR_threshold) {
+
+ PSNR_threshold = readPSNRFromFile("psnr.txt");
+ std::vector<float> psnr_list;
+
+ struct Tensor *gold_tensor = (struct Tensor *)gold_ptr;
+ struct Tensor *approx_tensor = (struct Tensor *)approx_ptr;
+
+ size_t *dim_sizes = gold_tensor->dims.dim_sizes;
+ size_t batch_dim = dim_sizes[0];
+ size_t image_size = dim_sizes[1] * dim_sizes[2] * dim_sizes[3];
+
+ printf("batch_dim = %lu, image_size = %lu \n", batch_dim, image_size);
+
+ float *gold_data = (float *)gold_tensor->host_data;
+ float *approx_data = (float *)approx_tensor->host_data;
+
+ FILE *fp = fopen("img_psnr.txt", "w+");
+
+ float sum_psnr = 0.0;
+ int num_errors = 0;
+ for (size_t i = 0; i < batch_dim; i++) {
+ float mse_sum = 0.0;
+ float max_val = -999999;
+ size_t offset = i * image_size;
+
+ for (size_t j = 0; j < image_size; j++) {
+ float diff = gold_data[offset + j] - approx_data[offset + j];
+ float diff_square = diff * diff;
+ mse_sum += diff_square;
+
+ if (max_val < gold_data[offset + j]) {
+ max_val = gold_data[offset + j];
+ }
+ }
+
+ mse_sum = mse_sum / image_size;
+ float psnr = 20 * log10(255 / sqrt(mse_sum));
+
+ sum_psnr += psnr;
+ if (psnr < PSNR_threshold)
+ num_errors += 1;
+
+ printf("PSNR value = %f \n", psnr);
+ psnr_list.push_back(psnr);
+
+ std::ostringstream ss;
+ ss << std::fixed << psnr;
+ std::string print_str = ss.str();
+ fwrite(print_str.c_str(), 1, print_str.length(), fp);
+ fwrite("\n", 1, 1, fp);
+ }
+
+ float violation_rate = (num_errors * 1.0) / batch_dim * 100.0;
+ printf("*** violation_rate= %f \n\n", violation_rate);
+
+ float avg_psnr = sum_psnr / batch_dim;
+ printf("*** avg_psnr = %f \n\n", avg_psnr);
+ dumpAvgPSNR(avg_psnr);
+
+ float success_rate = 100.0 - violation_rate;
+ dumpFinalAccuracy(success_rate);
+
+ fclose(fp);
+
+ float var = 0.0;
+ for (size_t i = 0; i < batch_dim; i++) {
+ var = var + (psnr_list[i] - avg_psnr) * (psnr_list[i] - avg_psnr);
+ }
+
+ var /= batch_dim;
+ float std = sqrt(var);
+
+ dumpPSNRStd(std);
+
+ return violation_rate;
+}
+
+void dumpOutput(void *output_ptr, const char *file_name) {
+
+ struct Tensor *out_tensor = (struct Tensor *)output_ptr;
+ size_t size_in_bytes = out_tensor->size_in_bytes;
+ printf("** Output size = %lu \n", size_in_bytes);
+
+ float *host_data = (float *)out_tensor->host_data;
+ FILE *fd = fopen(file_name, "w+");
+ fwrite(host_data, 1, size_in_bytes, fd);
+ fclose(fd);
+}
+
+#endif
--
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