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Add bias to make_dense_linearized

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augustin64 2023-02-28 11:47:57 +01:00
parent c1b4f55929
commit 4b87b19188
4 changed files with 22 additions and 22 deletions
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2
src/cnn/cnn.c
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@ -110,7 +110,7 @@ void forward_propagation(Network* network) {
if (k_i->linearisation == 0) { // Vecteur -> Vecteur
make_dense(k_i->nn, input[0][0], output[0][0], input_width, output_width);
} else { // Matrice -> Vecteur
make_dense_linearised(k_i->nn, input, output[0][0], input_depth, input_width, output_width);
make_dense_linearized(k_i->nn, input, output[0][0], input_depth, input_width, output_width);
}
copy_input_to_input_z(output, output_a, 1, 1, output_width);
choose_apply_function_vector(activation, output, output_width);

2
src/cnn/include/make.h
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@ -43,6 +43,6 @@ extern "C"
/*
* Effectue une full connection qui passe d'une matrice à un vecteur
*/
void make_dense_linearised(Kernel_nn* kernel, float*** input, float* output, int depth_input, int dim_input, int size_output);
void make_dense_linearized(Kernel_nn* kernel, float*** input, float* output, int depth_input, int dim_input, int size_output);
#endif

20
src/cnn/make.c
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@ -229,17 +229,17 @@ void make_dense(Kernel_nn* kernel, float* input, float* output, int size_input,
/*
* Dense linearised
* Dense linearized
*/
#ifdef __CUDACC__
__global__ void make_dense_linearised_kernel(float** weights, float*** input, float* output, int depth_input, int dim_input, int size_output) {
__global__ void make_dense_linearized_kernel(float** weights, float* bias, float*** input, float* output, int depth_input, int dim_input, int size_output) {
// Équivalents respectifs de i, j et k dans la boucle effectuée par le cpu
int idx = threadIdx.x + blockDim.x*blockIdx.x; // < size_output
if (idx >= size_output) {
return;
}
float f = 0;
float f = bias[idx];
for (int i=0; i < depth_input; i++) {
for (int j=0; j < dim_input; j++) {
@ -251,24 +251,24 @@ __global__ void make_dense_linearised_kernel(float** weights, float*** input, fl
output[idx] = f;
}
void make_dense_linearised_device(Kernel_nn* kernel, float*** input, float* output, int depth_input, int dim_input, int size_output) {
void make_dense_linearized_device(Kernel_nn* kernel, float*** input, float* output, int depth_input, int dim_input, int size_output) {
// Make computation
dim3 gridSize(i_div_up(size_output, BLOCKSIZE_x*BLOCKSIZE_y), 1, 1);
dim3 blockSize(BLOCKSIZE_x*BLOCKSIZE_y, 1, BLOCKSIZE_z);
make_dense_linearised_kernel<<<gridSize, blockSize>>>(kernel->weights, input, output, depth_input, dim_input, size_output);
make_dense_linearized_kernel<<<gridSize, blockSize>>>(kernel->weights, kernel->bias, input, output, depth_input, dim_input, size_output);
gpuErrchk( cudaPeekAtLastError() );
gpuErrchk( cudaDeviceSynchronize() );
}
#endif
void make_dense_linearised_cpu(Kernel_nn* kernel, float*** input, float* output, int depth_input, int dim_input, int size_output) {
void make_dense_linearized_cpu(Kernel_nn* kernel, float*** input, float* output, int depth_input, int dim_input, int size_output) {
// input[depth_input][dim_input][dim_input]
// output[size_output]
float f;
for (int l=0; l < size_output; l++) {
f = 0;
f = kernel->bias[l];
for (int i=0; i < depth_input; i++) {
for (int j=0; j < dim_input; j++) {
for (int k=0; k < dim_input; k++) {
@ -283,10 +283,10 @@ void make_dense_linearised_cpu(Kernel_nn* kernel, float*** input, float* output,
#ifdef __CUDACC__
extern "C"
#endif
void make_dense_linearised(Kernel_nn* kernel, float*** input, float* output, int depth_input, int dim_input, int size_output) {
void make_dense_linearized(Kernel_nn* kernel, float*** input, float* output, int depth_input, int dim_input, int size_output) {
#ifndef __CUDACC__
make_dense_linearised_cpu(kernel, input, output, depth_input, dim_input, size_output);
make_dense_linearized_cpu(kernel, input, output, depth_input, dim_input, size_output);
#else
make_dense_linearised_device(kernel, input, output, depth_input, dim_input, size_output);
make_dense_linearized_device(kernel, input, output, depth_input, dim_input, size_output);
#endif
}

20
src/cnn/make.cu
View File

@ -229,17 +229,17 @@ void make_dense(Kernel_nn* kernel, float* input, float* output, int size_input,
/*
* Dense linearised
* Dense linearized
*/
#ifdef __CUDACC__
__global__ void make_dense_linearised_kernel(float** weights, float*** input, float* output, int depth_input, int dim_input, int size_output) {
__global__ void make_dense_linearized_kernel(float** weights, float* bias, float*** input, float* output, int depth_input, int dim_input, int size_output) {
// Équivalents respectifs de i, j et k dans la boucle effectuée par le cpu
int idx = threadIdx.x + blockDim.x*blockIdx.x; // < size_output
if (idx >= size_output) {
return;
}
float f = 0;
float f = bias[idx];
for (int i=0; i < depth_input; i++) {
for (int j=0; j < dim_input; j++) {
@ -251,24 +251,24 @@ __global__ void make_dense_linearised_kernel(float** weights, float*** input, fl
output[idx] = f;
}
void make_dense_linearised_device(Kernel_nn* kernel, float*** input, float* output, int depth_input, int dim_input, int size_output) {
void make_dense_linearized_device(Kernel_nn* kernel, float*** input, float* output, int depth_input, int dim_input, int size_output) {
// Make computation
dim3 gridSize(i_div_up(size_output, BLOCKSIZE_x*BLOCKSIZE_y), 1, 1);
dim3 blockSize(BLOCKSIZE_x*BLOCKSIZE_y, 1, BLOCKSIZE_z);
make_dense_linearised_kernel<<<gridSize, blockSize>>>(kernel->weights, input, output, depth_input, dim_input, size_output);
make_dense_linearized_kernel<<<gridSize, blockSize>>>(kernel->weights, kernel->bias, input, output, depth_input, dim_input, size_output);
gpuErrchk( cudaPeekAtLastError() );
gpuErrchk( cudaDeviceSynchronize() );
}
#endif
void make_dense_linearised_cpu(Kernel_nn* kernel, float*** input, float* output, int depth_input, int dim_input, int size_output) {
void make_dense_linearized_cpu(Kernel_nn* kernel, float*** input, float* output, int depth_input, int dim_input, int size_output) {
// input[depth_input][dim_input][dim_input]
// output[size_output]
float f;
for (int l=0; l < size_output; l++) {
f = 0;
f = kernel->bias[l];
for (int i=0; i < depth_input; i++) {
for (int j=0; j < dim_input; j++) {
for (int k=0; k < dim_input; k++) {
@ -283,10 +283,10 @@ void make_dense_linearised_cpu(Kernel_nn* kernel, float*** input, float* output,
#ifdef __CUDACC__
extern "C"
#endif
void make_dense_linearised(Kernel_nn* kernel, float*** input, float* output, int depth_input, int dim_input, int size_output) {
void make_dense_linearized(Kernel_nn* kernel, float*** input, float* output, int depth_input, int dim_input, int size_output) {
#ifndef __CUDACC__
make_dense_linearised_cpu(kernel, input, output, depth_input, dim_input, size_output);
make_dense_linearized_cpu(kernel, input, output, depth_input, dim_input, size_output);
#else
make_dense_linearised_device(kernel, input, output, depth_input, dim_input, size_output);
make_dense_linearized_device(kernel, input, output, depth_input, dim_input, size_output);
#endif
}