Better imagenet distributed training

Joseph Redmon

2014-12-11 79fffcce3ce495bd415dc1284224c915d7194d4c

 src/network_gpu.c

@@ -87,7 +87,7 @@
        }
        if(net.types[i] == CONVOLUTIONAL){
            convolutional_layer layer = *(convolutional_layer *)net.layers[i];
            backward_convolutional_layer_gpu(layer, prev_delta);
            backward_convolutional_layer_gpu(layer, prev_input, prev_delta);
        }
        else if(net.types[i] == COST){
            cost_layer layer = *(cost_layer *)net.layers[i];
@@ -182,22 +182,10 @@
        cl_write_array(*net.input_cl, x, x_size);
        cl_write_array(*net.truth_cl, y, y_size);
    }
    //printf("trans %f\n", sec(clock()-time));
    //time = clock();

    forward_network_gpu(net, *net.input_cl, *net.truth_cl, 1);

    //printf("forw %f\n", sec(clock()-time));
    //time = clock();
    backward_network_gpu(net, *net.input_cl);
    //printf("back %f\n", sec(clock()-time));
    //time = clock();

    update_network_gpu(net);
    float error = get_network_cost(net);

    //printf("updt %f\n", sec(clock()-time));
    //time = clock();
    return error;
}

@@ -302,11 +290,29 @@
float network_accuracy_gpu(network net, data d)
{
    matrix guess = network_predict_data_gpu(net, d);
    float acc = matrix_accuracy(d.y, guess);
    float acc = matrix_topk_accuracy(d.y, guess,1);
    free_matrix(guess);
    return acc;
}

float *network_accuracies_gpu(network net, data d)
{
    static float acc[2];
    matrix guess = network_predict_data_gpu(net, d);
    acc[0] = matrix_topk_accuracy(d.y, guess,1);
    acc[1] = matrix_topk_accuracy(d.y, guess,5);
    free_matrix(guess);
    return acc;
}


#else
void forward_network_gpu(network net, cl_mem input, cl_mem truth, int train){}
void backward_network_gpu(network net, cl_mem input){}
void update_network_gpu(network net){}
float train_network_sgd_gpu(network net, data d, int n){return 0;}
float train_network_data_gpu(network net, data d, int n){return 0;}
float *network_predict_gpu(network net, float *input){return 0;}
float network_accuracy_gpu(network net, data d){return 0;}

#endif