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Add copy_network_cuda

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augustin64 2022-06-01 17:14:16 +02:00
parent f27d7542f8
commit bea5eafab7
2 changed files with 55 additions and 3 deletions
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3
src/mnist/include/neural_network.h
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@ -27,4 +27,7 @@ void patch_delta(Network* network, Network* delta, uint32_t nb_modifs);
Network* copy_network(Network* network);
float loss_computing(Network* network, int numero_voulu);
#ifdef __CUDACC__
Network* copy_network_cuda(Network* network);
#endif
#endif

51
src/mnist/neural_network.c
View File

@ -16,16 +16,20 @@
//Coefficient leaking ReLU
#define COEFF_LEAKY_RELU 0.2
#define MAX_RESEAU 100000
#define INT_MIN -2147483648
#define PRINT_POIDS false
#define PRINT_BIAIS false
#ifndef __CUDACC__
// The functions and macros below are already defined when using NVCC
#define INT_MIN -2147483648
float max(float a, float b){
return a < b ? b : a;
}
#endif
float sigmoid(float x){
return 1/(1 + exp(-x));
}
@ -390,3 +394,48 @@ float loss_computing(Network* network, int numero_voulu){
return erreur;
}
#ifdef __CUDACC__
Network* copy_network_cuda(Network* network) {
// Renvoie une copie modifiable d'un réseau de neurones
Network* network2 = NULL;
Layer* layer;
Neuron* neuron1;
Neuron* neuron;
cudaMalloc((void**)&network2, sizeof(Network));
network2->nb_layers = network->nb_layers;
cudaMalloc((void***)&network2->layers, sizeof(Layer*)*network->nb_layers);
for (int i=0; i < network2->nb_layers; i++) {
cudaMalloc((void**)&layer, sizeof(Layer));
layer->nb_neurons = network->layers[i]->nb_neurons;
cudaMalloc((void***)&layer->neurons, sizeof(Neuron*)*layer->nb_neurons);
for (int j=0; j < layer->nb_neurons; j++) {
cudaMalloc((void**)neuron, sizeof(Neuron));
neuron1 = network->layers[i]->neurons[j];
neuron->bias = neuron1->bias;
neuron->z = neuron1->z;
neuron->back_bias = neuron1->back_bias;
neuron->last_back_bias = neuron1->last_back_bias;
if (i != network2->nb_layers-1) {
(void)network2->layers[i+1]->nb_neurons;
cudaMalloc((float**)&neuron->weights, sizeof(float)*network->layers[i+1]->nb_neurons);
cudaMalloc((float**)&neuron->back_weights, sizeof(float)*network->layers[i+1]->nb_neurons);
cudaMalloc((float**)&neuron->last_back_weights, sizeof(float)*network->layers[i+1]->nb_neurons);
for (int k=0; k < network->layers[i+1]->nb_neurons; k++) {
neuron->weights[k] = neuron1->weights[k];
neuron->back_weights[k] = neuron1->back_weights[k];
neuron->last_back_weights[k] = neuron1->last_back_weights[k];
}
}
layer->neurons[j] = neuron;
}
network2->layers[i] = layer;
}
return network2;
}
#endif