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alexmr09
2024-07-23 13:00:49 +03:00
parent 9e044fd7fc
commit 745cc4ed6d
28 changed files with 33632 additions and 106 deletions
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inference_codes/common/dws_conv.h
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#ifndef DWS_CONV_H
#define DWS_CONV_H
void pw_conv(int in_dim[3], int fil_dim[4], int out_dim[3], int inp[in_dim[0]][in_dim[1]][in_dim[2]],
const int fil[fil_dim[0]][fil_dim[3]], const int bias[],
int out[out_dim[0]][out_dim[1]][out_dim[2]], int strides, int pad[],
const int bias_shift_mode, const int quantized_multiplier, const int out_shift_rl){
int i, j, k, m, res, str1, str2, quant_prod;
for (i = 0; i < out_dim[2]; i++) { // output depth
str1 = -pad[0] - strides;
for (j = 0; j < out_dim[0]; j++) { // output height
str1 += strides;
str2 = -pad[2] - strides;
for (k = 0; k < out_dim[1]; k++) { // output width
res = bias[i];
str2 += strides;
if (str1 < in_dim[0] && str1 >= 0 && str2 >= 0 && str2 < in_dim[1]) {
for (m = 0; m < fil_dim[3]; m++) { // filters depth
res += inp[str1][str2][m] * fil[i][m];
}
}
quant_prod = quantized_multiplier * res + (1 << (out_shift_rl -1));
quant_prod = quant_prod >> (out_shift_rl);
if(quant_prod < 0) quant_prod = 0;
if(quant_prod > 255) quant_prod = 255;
out[j][k][i] = quant_prod;
}
}
}
}
void dw_conv(int in_dim[3], int depthwise_fil_dim[4], int out_dim[3], int inp[in_dim[0]][in_dim[1]][in_dim[2]],
const int depthwise_fil[depthwise_fil_dim[0]][depthwise_fil_dim[1]][depthwise_fil_dim[2]][1], const int bias[],
int out[out_dim[0]][out_dim[1]][out_dim[2]], int strides, int pad[],
const int bias_shift_mode, const int depthwise_multiplier, const int depthwise_out_shift_rl){
int i, j, k, n, p, res, k1, k2, str1, str2, quant_prod;
// Depthwise convolution
for (i = 0; i < out_dim[2]; i++) { // output depth
str1 = -pad[0] - strides;
for (j = 0; j < out_dim[0]; j++) { // output height
str1 += strides;
str2 = -pad[2] - strides;
for (k = 0; k < out_dim[1]; k++) { // output width
res = bias[i];
str2 += strides;
for (p = 0; p < depthwise_fil_dim[1]; p++){ // depthwise filter height
for (n = 0; n < depthwise_fil_dim[2]; n++) { // depthwise filter width
k1 = str1 + p;
k2 = str2 + n;
if (k1 < in_dim[0] && k1 >= 0 && k2 >= 0 && k2 < in_dim[1]) {
res += inp[k1][k2][i] * depthwise_fil[i][p][n][0];
}
}
}
quant_prod = depthwise_multiplier * res + (1 << (depthwise_out_shift_rl -1));
quant_prod = quant_prod >> (depthwise_out_shift_rl);
if(quant_prod < 0) quant_prod = 0;
if(quant_prod > 255) quant_prod = 255;
out[j][k][i] = quant_prod;
}
}
}
}
#endif /* DWS_CONV_H */
inference_codes/common/dws_conv_opt.h
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#ifndef DWS_CONV_OPT_H
#define DWS_CONV_OPT_H
void pw_conv_8bits(int in_dim[3], int fil_dim[4], int out_dim[3], int inp[in_dim[0]][in_dim[1]][in_dim[2]],
const int fil[fil_dim[0]][fil_dim[3] << 2], const int bias[fil_dim[0]],
int out[out_dim[0]][out_dim[1]][out_dim[2]], int strides, int pad[], const int bias_shift_mode[],
const int quantized_multiplier, const int out_shift_rl){
int i, j, k, m, res, str1, str2, bias_val, w, in_cnn;
for (i = 0; i < out_dim[2]; i++) { // output depth
str1 = -pad[0] - strides;
for (j = 0; j < out_dim[0]; j++) { // output height
str1 += 1;
str2 = -pad[2] - strides;
for (k = 0; k < out_dim[1]; k++) { // output width
bias_val = bias[i];
str2 += 1;
asm volatile("neur_init %0, %1, %2\n":"=r"(res):"r"(bias_val),"r"(bias_shift_mode[i]):);
for (m = 0; m < fil_dim[3]; m++) { // filters depth
in_cnn = inp[str1][str2][m];
w = fil[i][4*m];
asm volatile("nn_mac_8b %0, %1,%2\n":"=r"(res):"r"(w),"r"(in_cnn):);
w = fil[i][4*m+1];
asm volatile("nn_mac_8b %0, %1,%2\n":"=r"(res):"r"(w),"r"(in_cnn):);
w = fil[i][4*m+2];
asm volatile("nn_mac_8b %0, %1,%2\n":"=r"(res):"r"(w),"r"(in_cnn):);
w = fil[i][4*m+3];
asm volatile("nn_mac_8b %0, %1,%2\n":"=r"(res):"r"(w),"r"(in_cnn):);
}
asm volatile("neur_res %0, %1, %2\n":"=r"(res):"r"(quantized_multiplier),"r"(out_shift_rl):);
out[j][k][i] = res;
}
}
}
}
void pw_conv_4bits(int in_dim[3], int fil_dim[4], int out_dim[3], int inp[in_dim[0]][in_dim[1]][in_dim[2]],
const int fil[fil_dim[0]][fil_dim[3] << 1], const int bias[fil_dim[0]],
int out[out_dim[0]][out_dim[1]][out_dim[2]], int strides, int pad[], const int bias_shift_mode[],
const int quantized_multiplier, const int out_shift_rl){
int i, j, k, m, res, str1, str2, bias_val, w, in_cnn;
for (i = 0; i < out_dim[2]; i++) { // output depth
str1 = -pad[0] - strides;
for (j = 0; j < out_dim[0]; j++) { // output height
str1 += 1;
str2 = -pad[2] - strides;
for (k = 0; k < out_dim[1]; k++) { // output width
bias_val = bias[i];
str2 += 1;
asm volatile("neur_init %0, %1, %2\n":"=r"(res):"r"(bias_val),"r"(bias_shift_mode[i]):);
for (m = 0; m < fil_dim[3]; m++) { // filters depth
in_cnn = inp[str1][str2][m];
w = fil[i][2*m];
asm volatile("nn_mac_4b %0, %1,%2\n":"=r"(res):"r"(w),"r"(in_cnn):);
w = fil[i][2*m+1];
asm volatile("nn_mac_4b %0, %1,%2\n":"=r"(res):"r"(w),"r"(in_cnn):);
}
asm volatile("neur_res %0, %1, %2\n":"=r"(res):"r"(quantized_multiplier),"r"(out_shift_rl):);
out[j][k][i] = res;
}
}
}
}
void pw_conv_2bits(int in_dim[3], int fil_dim[4], int out_dim[3], int inp[in_dim[0]][in_dim[1]][in_dim[2]],
const int fil[fil_dim[0]][fil_dim[3]], const int bias[fil_dim[0]],
int out[out_dim[0]][out_dim[1]][out_dim[2]], int strides, int pad[], const int bias_shift_mode[],
const int quantized_multiplier, const int out_shift_rl){
int i, j, k, m, res, str1, str2, bias_val, w, in_cnn;
for (i = 0; i < out_dim[2]; i++) { // output depth
str1 = -pad[0] - strides;
for (j = 0; j < out_dim[0]; j++) { // output height
str1 += 1;
str2 = -pad[2] - strides;
for (k = 0; k < out_dim[1]; k++) { // output width
bias_val = bias[i];
str2 += 1;
asm volatile("neur_init %0, %1, %2\n":"=r"(res):"r"(bias_val),"r"(bias_shift_mode[i]):);
for (m = 0; m < fil_dim[3]; m++) { // filters depth
in_cnn = inp[str1][str2][m];
w = fil[i][m];
asm volatile("nn_mac_2b %0, %1,%2\n":"=r"(res):"r"(w),"r"(in_cnn):);
}
asm volatile("neur_res %0, %1, %2\n":"=r"(res):"r"(quantized_multiplier),"r"(out_shift_rl):);
out[j][k][i] = res;
}
}
}
}
void dw_conv_opt(int in_dim[3], int depthwise_fil_dim[4], int out_dim[3],
int inp[in_dim[0]][in_dim[1]][in_dim[2]], const int depthwise_fil[depthwise_fil_dim[0]][depthwise_fil_dim[1]][depthwise_fil_dim[2]],
const int bias[depthwise_fil_dim[0]], int out[out_dim[0]][out_dim[1]][out_dim[2]],
int strides, int pad[], const int bias_shift_mode[], const int quantized_multiplier, const int out_shift_rl){
int i, j, k, n, p, res, k1, k2, str1, str2, bias_val, in_cnn, w;
// Depthwise convolution
for (i = 0; i < out_dim[2]; i++){ // output depth
str1 = -pad[0] - strides;
for (j = 0; j < out_dim[0]; j++) { // output height
str1 += strides;
str2 = -pad[2] - strides;
for (k = 0; k < out_dim[1]; k++) { // output width
bias_val = bias[i];
str2 += strides;
asm volatile("neur_init %0, %1, %2\n":"=r"(res):"r"(bias_val),"r"(bias_shift_mode[i]):);
for (p = 0; p < depthwise_fil_dim[1]; p++) { // depthwise filter height
for (n = 0; n < depthwise_fil_dim[2]; n++) { // depthwise filter width
k1 = str1 + p;
k2 = str2 + n;
if (k1 < in_dim[0] && k1 >= 0 && k2 >= 0 && k2 < in_dim[1]) {
in_cnn = inp[k1][k2][i];
w = depthwise_fil[i][p][n];
asm volatile("nn_mac_8b %0, %1,%2\n":"=r"(res):"r"(w),"r"(in_cnn):);
}
}
}
asm volatile("neur_res %0, %1, %2\n":"=r"(res):"r"(quantized_multiplier),"r"(out_shift_rl):);
out[j][k][i] = res;
}
}
}
}
void dw_conv_opt_1ch(int in_dim[3], int depthwise_fil_dim[4], int out_dim[3],
int inp[in_dim[0]][in_dim[1]][in_dim[2]], const int depthwise_fil[depthwise_fil_dim[0]][depthwise_fil_dim[1]][depthwise_fil_dim[2]],
const int bias[depthwise_fil_dim[0]], int out[out_dim[0]][out_dim[1]][out_dim[2]],
int strides, int pad[], const int bias_shift_mode[], const int quantized_multiplier, const int out_shift_rl){
int j, k, n, p, res, k1, k2, str1, str2, bias_val, in_cnn, w;
// Depthwise convolution
str1 = -pad[0] - strides;
for (j = 0; j < out_dim[0]; j++) { // output height
str1 += strides;
str2 = -pad[2] - strides;
for (k = 0; k < out_dim[1]; k++) { // output width
bias_val = bias[0];
str2 += strides;
asm volatile("neur_init %0, %1, %2\n":"=r"(res):"r"(bias_val),"r"(bias_shift_mode[0]):);
for (p = 0; p < depthwise_fil_dim[1]; p++) { // depthwise filter height
for (n = 0; n < depthwise_fil_dim[2]; n++) { // depthwise filter width
k1 = str1 + p;
k2 = str2 + n;
if (k1 < in_dim[0] && k1 >= 0 && k2 >= 0 && k2 < in_dim[1]) {
in_cnn = inp[k1][k2][0];
w = depthwise_fil[0][p][n];
asm volatile("nn_mac_8b %0, %1,%2\n":"=r"(res):"r"(w),"r"(in_cnn):);
}
}
}
asm volatile("neur_res %0, %1, %2\n":"=r"(res):"r"(quantized_multiplier),"r"(out_shift_rl):);
out[j][k][0] = res;
}
}
}
#endif /* DWS_CONV_OPT_H */