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Fixed many warnings

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This commit is contained in:
AlexeyAB
2019-03-18 19:25:48 +03:00
parent 6d6202f666
commit b3254ed523
20 changed files with 73 additions and 75 deletions
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25
src/convolutional_layer.c
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@ -679,7 +679,7 @@ void float_to_bit(float *src, unsigned char *dst, size_t size) {
void bit_to_float(unsigned char *src, float *dst, size_t size, size_t filters, float *mean_arr) {
memset(dst, 0, size *sizeof(float));
size_t i, src_i, src_shift;
size_t i;
for (i = 0; i < size; ++i) {
float mean_val = 1;
@ -726,7 +726,7 @@ void binary_align_weights(convolutional_layer *l)
const int items_per_channel = l->size*l->size;
for (i = 0; i < items_per_channel; ++i)
{
uint32_t val = 0;
//uint32_t val = 0;
int c_pack;
for (c_pack = 0; c_pack < 32; ++c_pack) {
float src = l->binary_weights[fil*items_per_filter + (chan + c_pack)*items_per_channel + i];
@ -749,8 +749,8 @@ void binary_align_weights(convolutional_layer *l)
//if (l->n >= 32)
if(gpu_index >= 0)
{
int M = l->n;
int N = l->out_w*l->out_h;
//int M = l->n;
//int N = l->out_w*l->out_h;
//printf("\n M = %d, N = %d, M %% 8 = %d, N %% 8 = %d - weights \n", M, N, M % 8, N % 8);
//printf("\n l.w = %d, l.c = %d, l.n = %d \n", l->w, l->c, l->n);
for (i = 0; i < align_weights_size / 8; ++i) l->align_bit_weights[i] = ~(l->align_bit_weights[i]);
@ -806,7 +806,7 @@ size_t binary_transpose_align_input(int k, int n, float *b, char **t_bit_input,
size_t t_bit_input_size = t_intput_size / 8;// +1;
memset(*t_bit_input, 0, t_bit_input_size * sizeof(char));
int src_size = k * bit_align;
//int src_size = k * bit_align;
// b - [bit_align, k] - [l.bit_align, l.size*l.size*l.c] = src_size
// t_input - [bit_align, k] - [n', k]
@ -862,8 +862,8 @@ void forward_convolutional_layer(convolutional_layer l, network_state state)
int ldb_align = l.lda_align;
size_t new_ldb = k + (ldb_align - k%ldb_align); // (k / 8 + 1) * 8;
size_t t_intput_size = new_ldb * l.bit_align;// n;
size_t t_bit_input_size = t_intput_size / 8;// +1;
//size_t t_intput_size = new_ldb * l.bit_align;// n;
//size_t t_bit_input_size = t_intput_size / 8;// +1;
int re_packed_input_size = l.c * l.w * l.h;
memset(state.workspace, 0, re_packed_input_size * sizeof(float));
@ -928,17 +928,18 @@ void forward_convolutional_layer(convolutional_layer l, network_state state)
//im2col_cpu_custom_align(state.input, l.c, l.h, l.w, l.size, l.stride, l.pad, b, l.bit_align);
im2col_cpu_custom_bin(state.input, l.c, l.h, l.w, l.size, l.stride, l.pad, state.workspace, l.bit_align);
size_t output_size = l.outputs;
//size_t output_size = l.outputs;
//float *count_output = calloc(output_size, sizeof(float));
//size_t bit_output_size = output_size / 8 + 1;
//char *bit_output = calloc(bit_output_size, sizeof(char));
size_t intput_size = n * k; // (out_h*out_w) X (l.size*l.size*l.c) : after im2col()
size_t bit_input_size = intput_size / 8 + 1;
//size_t intput_size = n * k; // (out_h*out_w) X (l.size*l.size*l.c) : after im2col()
//size_t bit_input_size = intput_size / 8 + 1;
//char *bit_input = calloc(bit_input_size, sizeof(char));
size_t weights_size = k * m; //l.size*l.size*l.c*l.n;
size_t bit_weights_size = weights_size / 8 + 1;
//size_t weights_size = k * m; //l.size*l.size*l.c*l.n;
//size_t bit_weights_size = weights_size / 8 + 1;
//char *bit_weights = calloc(bit_weights_size, sizeof(char));
//float *mean_arr = calloc(l.n, sizeof(float));