Removing some dead code from tensorUtils.h

hpvm/projects/hpvm-tensor-rt/tensor_runtime/include/tensorUtils.h

@@ -148,7 +148,7 @@ 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++) {
+  for (unsigned int i = 0; i < tensor->dims.num_dims; i++) {
     printf("dim[%d] = %lu \n", i, tensor->dims.dim_sizes[i]);
   }
 }
@@ -188,79 +188,8 @@ 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) {
 
-  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,
@@ -368,27 +297,6 @@ uint32_t *readLabels3(const char *labels_file, int num_labels) {
   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) {
 
@@ -412,88 +320,6 @@ uint32_t *readLabelsBatch3(const char *labels_file, int start, int end) {
 }
 
 
-/*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) {
 
@@ -509,7 +335,7 @@ float computeAccuracy3(uint32_t *labels, void *result_ptr) {
   for (unsigned int i = 0; i < batch_dim; i++) {
 
     int chosen = 0;
-    for (int id = 1; id < num_classes; ++id) {
+    for (unsigned int id = 1; id < num_classes; ++id) {
       if (data[i * num_classes + chosen] < data[i * num_classes + id])
         chosen = id;
     }
@@ -557,10 +383,10 @@ float computeTop5Accuracy(uint8_t *labels, int num_labels, void *result_ptr,
 
   printf("batch_dim = %lu, channels = %lu \n", batch_dim, channels);
 
-  for (int i = 0; i < num_labels; i++) {
+  for (unsigned int i = 0; i < num_labels; i++) {
 
     std::vector<ClassProb> elem_probs;
-    for (int id = 0; id < num_classes; ++id) {
+    for (unsigned int id = 0; id < num_classes; ++id) {
       ClassProb cProb;
       cProb.prob = data[i * channels + id];
       cProb.index = id;
@@ -643,6 +469,7 @@ void dumpPSNRStd(float psnr_std) {
   fclose(fp);
 }
 
+
 void dumpExecutionAccuracies() {
 
   FILE *fp = fopen("run_accuracies.txt", "w+");