From 644bf40430c4f168181afd29857e8c25f77a552a Mon Sep 17 00:00:00 2001
From: Yifan Zhao <yifanz16@illinois.edu>
Date: Tue, 2 Feb 2021 03:03:36 -0600
Subject: [PATCH] Fixed some warning in compilation
---
.../dnn_sources/include/utils.h | 68 ++++++-------------
.../tensor_runtime/src/global_data.cc | 2 +-
.../tensor_runtime/src/hpvm-rt-controller.cpp | 7 +-
.../tensor_runtime/src/tensor_cpu_runtime.cc | 10 ---
4 files changed, 25 insertions(+), 62 deletions(-)
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 178454153b..43d4975749 100644
--- a/hpvm/projects/hpvm-tensor-rt/dnn_sources/include/utils.h
+++ b/hpvm/projects/hpvm-tensor-rt/dnn_sources/include/utils.h
@@ -46,10 +46,6 @@ void dumpWeightsToFile(const char *file_name, void *weights_ptr) {
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);
}
@@ -204,12 +200,12 @@ void compareValues(void *tensor_ptr, float *data, size_t num_elems) {
void *readInputTensor(const char *file_name, int data_type, int dim1_size,
int dim2_size, int dim3_size, int dim4_size) {
- int type_size = 4; // NOTE: Assuming floating point tensors
- int num_elems = dim1_size * dim2_size * dim3_size * dim4_size;
- int size_in_bytes = type_size * dim1_size * dim2_size * dim3_size * dim4_size;
+ size_t type_size = 4; // NOTE: Assuming floating point tensors
+ size_t num_elems = dim1_size * dim2_size * dim3_size * dim4_size;
+ size_t size_in_bytes = type_size * num_elems;
uint8_t *file_data = (uint8_t *)malloc(sizeof(char) * num_elems);
float *tensor_data = (float *)malloc(sizeof(float) * num_elems);
- int file_header_size = 16;
+ size_t file_header_size = 16;
FILE *file = fopen(file_name, "rb");
if (file == NULL) {
@@ -218,8 +214,7 @@ void *readInputTensor(const char *file_name, int data_type, int dim1_size,
}
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);
-
+ fread(file_data, 1, sizeof(uint8_t) * num_elems, file);
fclose(file);
for (size_t i = 0; i < num_elems; ++i) {
@@ -256,11 +251,7 @@ struct Tensor *readTrainedWeightsCPU(const char *file_name, int data_type,
}
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);
-
+ fread(tensor_data, 1, size_in_bytes, file);
fclose(file);
struct Tensor *weights = (struct Tensor *)create4DTensor(
@@ -294,11 +285,7 @@ struct Tensor *readTrainedWeights(const char *file_name, int data_type,
}
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);
-
+ fread(tensor_data, 1, size_in_bytes, file);
fclose(file);
struct Tensor *weights = (struct Tensor *)create4DTensor(
@@ -332,8 +319,7 @@ struct Tensor *readInputBatch(const char *file_name, int data_type,
}
fseek(file, file_header_size, SEEK_SET); // Skipping the file header
- size_t bytes_read = fread(tensor_data, 1, size_in_bytes, file);
-
+ fread(tensor_data, 1, size_in_bytes, file);
fclose(file);
struct Tensor *weights = (struct Tensor *)create4DTensor(
@@ -367,8 +353,7 @@ void *copyInputBatch(const char *file_name, int start, int end,
}
fseek(file, file_header_size, SEEK_SET); // Skipping the file header
- size_t bytes_read = fread(tensor_data, 1, size_in_bytes, file);
-
+ fread(tensor_data, 1, size_in_bytes, file);
fclose(file);
initTensorData(inputTensor, tensor_data, size_in_bytes);
@@ -392,9 +377,7 @@ uint8_t *readLabels(const char *labels_file, int num_labels) {
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);
-
+ fread(labels, 1, sizeof(uint8_t) * num_labels, file);
fclose(file);
return labels;
@@ -408,9 +391,7 @@ uint32_t *readLabels3(const char *labels_file, int num_labels) {
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);
-
+ fread(labels, 1, sizeof(uint32_t) * num_labels, file);
fclose(file);
return labels;
@@ -429,9 +410,7 @@ uint8_t *readLabelsBatch(const char *labels_file, int start, int end) {
}
fseek(file, file_header_size, SEEK_SET); // Skipping the file header
-
- size_t bytes_read = fread(labels, 1, sizeof(uint8_t) * num_labels, file);
-
+ fread(labels, 1, sizeof(uint8_t) * num_labels, file);
fclose(file);
// printf("--labels bytes_read = %lu \n", bytes_read);
@@ -451,9 +430,7 @@ uint32_t *readLabelsBatch3(const char *labels_file, int start, int end) {
}
fseek(file, file_header_size, SEEK_SET); // Skipping the file header
-
- size_t bytes_read = fread(labels, 1, sizeof(uint32_t) * num_labels, file);
-
+ fread(labels, 1, sizeof(uint32_t) * num_labels, file);
fclose(file);
return labels;
@@ -470,7 +447,7 @@ void computeAccuracy(const char *labels_file, int num_labels,
float *data = (float *)result->host_data;
int num_errors = 0;
- for (int i = 0; i < batch_dim; i++) {
+ for (size_t 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])
@@ -513,7 +490,7 @@ float computeAccuracy2(uint8_t *labels, int batch_size, void *result_ptr,
for (unsigned int i = 0; i < batch_dim; i++) {
int chosen = 0;
- for (int id = 1; id < num_classes; ++id) {
+ for (size_t id = 1; id < num_classes; ++id) {
if (data[i * num_classes + chosen] < data[i * num_classes + id])
chosen = id;
}
@@ -551,10 +528,10 @@ float computeAccuracy3(uint32_t *labels, void *result_ptr) {
printf("batch_dim = %lu, num_classes = %lu \n", batch_dim, num_classes);
- for (int i = 0; i < batch_dim; i++) {
+ for (size_t i = 0; i < batch_dim; i++) {
- int chosen = 0;
- for (int id = 1; id < num_classes; ++id) {
+ 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;
}
@@ -605,15 +582,14 @@ float computeTop5Accuracy(uint8_t *labels, int num_labels, void *result_ptr,
for (int i = 0; i < num_labels; i++) {
std::vector<ClassProb> elem_probs;
- for (int id = 0; id < num_classes; ++id) {
+ for (size_t 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);
+ 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++) {
@@ -692,7 +668,7 @@ void dumpExecutionAccuracies() {
FILE *fp = fopen("run_accuracies.txt", "w+");
if (fp != NULL) {
- for (int i = 0; i < run_accuracies.size(); i++) {
+ for (size_t i = 0; i < run_accuracies.size(); i++) {
float accuracy = run_accuracies[i];
std::ostringstream ss;
ss << std::fixed << accuracy;
@@ -822,7 +798,7 @@ void copyClassConfsAndLabels(void *result_ptr, float *classConfs,
for (int i = 0; i < it_count; i++) {
int chosen = 0;
- for (int id = 1; id < num_classes; ++id) {
+ for (size_t id = 1; id < num_classes; ++id) {
if (data[i * num_classes + chosen] < data[i * num_classes + id])
chosen = id;
}
diff --git a/hpvm/projects/hpvm-tensor-rt/tensor_runtime/src/global_data.cc b/hpvm/projects/hpvm-tensor-rt/tensor_runtime/src/global_data.cc
index b812a51d7e..aeb12e9f6e 100644
--- a/hpvm/projects/hpvm-tensor-rt/tensor_runtime/src/global_data.cc
+++ b/hpvm/projects/hpvm-tensor-rt/tensor_runtime/src/global_data.cc
@@ -47,4 +47,4 @@ std::string profile_data = "";
PerfParamSet *perfParamSet;
SampParamSet *sampParamSet;
-unsigned int currentTensorID = -1;
+unsigned int currentTensorID = ~0U;
diff --git a/hpvm/projects/hpvm-tensor-rt/tensor_runtime/src/hpvm-rt-controller.cpp b/hpvm/projects/hpvm-tensor-rt/tensor_runtime/src/hpvm-rt-controller.cpp
index c7237c0076..66e8e3d1ba 100644
--- a/hpvm/projects/hpvm-tensor-rt/tensor_runtime/src/hpvm-rt-controller.cpp
+++ b/hpvm/projects/hpvm-tensor-rt/tensor_runtime/src/hpvm-rt-controller.cpp
@@ -417,12 +417,12 @@ double RuntimeController::getCurrentConfigurationAccuracyLoss() {
NodeConfiguration *RuntimeController::getNodeConfiguration(const char *data) {
// if visc.node.id Not specified for this HPVM Node
- if (currentTensorID == -1) {
+ if (currentTensorID == ~0U) {
std::string s(data);
// All nodes are expected to have a configuration
return (*Configurations)[configurationIdx]->setup.at(s);
} else {
- DEBUG("-- currentTensorID = \%u \n", currentTensorID);
+ DEBUG("-- currentTensorID = %u \n", currentTensorID);
return (*Configurations)[configurationIdx]->idConfigMap.at(currentTensorID);
}
}
@@ -664,7 +664,6 @@ void RuntimeController::readConfigurationFile(const char *str) {
abort();
}
- bool readingConfiguration = false;
bool readingFirstLine = false;
// Read baseline_time from first line of configuration file
@@ -697,13 +696,11 @@ void RuntimeController::readConfigurationFile(const char *str) {
if (tokens[0] == "+++++") { // Found new configuration start token
// Mark the start of a new configuration
- readingConfiguration = true;
readingFirstLine = true;
continue;
}
if (tokens[0] == "-----") { // Found configuration end token
- readingConfiguration = false;
// Mark the end of current configuration
continue;
}
diff --git a/hpvm/projects/hpvm-tensor-rt/tensor_runtime/src/tensor_cpu_runtime.cc b/hpvm/projects/hpvm-tensor-rt/tensor_runtime/src/tensor_cpu_runtime.cc
index 7a1acd2ba0..939f6e0619 100644
--- a/hpvm/projects/hpvm-tensor-rt/tensor_runtime/src/tensor_cpu_runtime.cc
+++ b/hpvm/projects/hpvm-tensor-rt/tensor_runtime/src/tensor_cpu_runtime.cc
@@ -371,7 +371,6 @@ void *tensorIrregularFilterSamplingConvolutionCPU(
float *reduced_kernels = (float *)malloc(reduced_filer_size);
float fac = (((float)skip_every) / ((float)skip_every - 1));
- int reduced_filter_dim = reduced_num_filter_elem / channels;
// Create Reduced filter
omp_set_num_threads(4);
@@ -750,7 +749,6 @@ void *tensorConvApproxCPU(void *input_ptr, void *filter_ptr, int vertical_pad,
}
if (skip_every > 1) {
printf("INPUT FILTERING\n");
- Tensor *input = (Tensor *)input_ptr;
Tensor *filter = (Tensor *)filter_ptr;
const int kernel_height = filter->dims.dim_sizes[2];
@@ -1026,7 +1024,6 @@ void *tensorGemmCPU(void *lhs_ptr, void *rhs_ptr) {
int m = lhs->dims.dim_sizes[0];
int n = rhs->dims.dim_sizes[rhs->dims.num_dims - 1]; // output neurons
- int rhs_k = rhs->dims.dim_sizes[rhs->dims.num_dims - 2];
Tensor *output = (Tensor *)create4DTensorCPU(0, 0, m, n, 1, 1);
@@ -1098,17 +1095,10 @@ void *tensorBatchNormCPU(void *input_ptr, void *gamma_ptr, void *beta_ptr,
Tensor *input = (Tensor *)input_ptr;
Tensor *gamma = (Tensor *)gamma_ptr;
Tensor *beta = (Tensor *)beta_ptr;
- Tensor *mean = (Tensor *)mean_ptr;
- Tensor *variance = (Tensor *)variance_ptr;
float *__restrict__ host_image = (float *)input->host_data;
float *__restrict__ host_beta = (float *)beta->host_data;
float *__restrict__ host_gamma = (float *)gamma->host_data;
- float *__restrict__ host_mean = (float *)mean->host_data;
- float *__restrict__ host_variance = (float *)variance->host_data;
-
- float alpha_val = 1.0f, beta_val = 0.0f;
- size_t num_elems = input->num_elems;
int batch_size = input->dims.dim_sizes[0];
int channels = input->dims.dim_sizes[1];
--
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