From e841d95c33d085d7ac931049657aea7891349fb0 Mon Sep 17 00:00:00 2001
From: Hashim Sharif <hsharif3@miranda.cs.illinois.edu>
Date: Tue, 30 Mar 2021 18:14:33 -0500
Subject: [PATCH] Removing some dead code from tensorUtils.h
---
.../tensor_runtime/include/tensorUtils.h | 183 +-----------------
1 file changed, 5 insertions(+), 178 deletions(-)
diff --git a/hpvm/projects/hpvm-tensor-rt/tensor_runtime/include/tensorUtils.h b/hpvm/projects/hpvm-tensor-rt/tensor_runtime/include/tensorUtils.h
index dd7942e288..d4961d19b9 100644
--- a/hpvm/projects/hpvm-tensor-rt/tensor_runtime/include/tensorUtils.h
+++ b/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+");
--
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