up new v4

Scheaven

2021-06-03 168af40fe9a3cc81c6ee16b3e81f154780c36bdb

 lib/detecter_tools/darknet/activation_layer.c

@@ -1,63 +1,63 @@
#include "activation_layer.h"

#include "utils.h"

#include "dark_cuda.h"

#include "blas.h"

#include "gemm.h"



#include <math.h>

#include <stdio.h>

#include <stdlib.h>

#include <string.h>



layer make_activation_layer(int batch, int inputs, ACTIVATION activation)

{

    layer l = { (LAYER_TYPE)0 };

    l.type = ACTIVE;



    l.inputs = inputs;

    l.outputs = inputs;

    l.batch=batch;



    l.output = (float*)xcalloc(batch * inputs, sizeof(float));

    l.delta = (float*)xcalloc(batch * inputs, sizeof(float));



    l.forward = forward_activation_layer;

    l.backward = backward_activation_layer;

#ifdef GPU

    l.forward_gpu = forward_activation_layer_gpu;

    l.backward_gpu = backward_activation_layer_gpu;



    l.output_gpu = cuda_make_array(l.output, inputs*batch);

    l.delta_gpu = cuda_make_array(l.delta, inputs*batch);

#endif

    l.activation = activation;

    fprintf(stderr, "Activation Layer: %d inputs\n", inputs);

    return l;

}



void forward_activation_layer(layer l, network_state state)

{

    copy_cpu(l.outputs*l.batch, state.input, 1, l.output, 1);

    activate_array(l.output, l.outputs*l.batch, l.activation);

}



void backward_activation_layer(layer l, network_state state)

{

    gradient_array(l.output, l.outputs*l.batch, l.activation, l.delta);

    copy_cpu(l.outputs*l.batch, l.delta, 1, state.delta, 1);

}



#ifdef GPU



void forward_activation_layer_gpu(layer l, network_state state)

{

    copy_ongpu(l.outputs*l.batch, state.input, 1, l.output_gpu, 1);

    activate_array_ongpu(l.output_gpu, l.outputs*l.batch, l.activation);

}



void backward_activation_layer_gpu(layer l, network_state state)

{

    gradient_array_ongpu(l.output_gpu, l.outputs*l.batch, l.activation, l.delta_gpu);

    copy_ongpu(l.outputs*l.batch, l.delta_gpu, 1, state.delta, 1);

}

#endif

#include "activation_layer.h"
#include "utils.h"
#include "dark_cuda.h"
#include "blas.h"
#include "gemm.h"

#include <math.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>

layer make_activation_layer(int batch, int inputs, ACTIVATION activation)
{
    layer l = { (LAYER_TYPE)0 };
    l.type = ACTIVE;

    l.inputs = inputs;
    l.outputs = inputs;
    l.batch=batch;

    l.output = (float*)xcalloc(batch * inputs, sizeof(float));
    l.delta = (float*)xcalloc(batch * inputs, sizeof(float));

    l.forward = forward_activation_layer;
    l.backward = backward_activation_layer;
#ifdef GPU
    l.forward_gpu = forward_activation_layer_gpu;
    l.backward_gpu = backward_activation_layer_gpu;

    l.output_gpu = cuda_make_array(l.output, inputs*batch);
    l.delta_gpu = cuda_make_array(l.delta, inputs*batch);
#endif
    l.activation = activation;
    fprintf(stderr, "Activation Layer: %d inputs\n", inputs);
    return l;
}

void forward_activation_layer(layer l, network_state state)
{
    copy_cpu(l.outputs*l.batch, state.input, 1, l.output, 1);
    activate_array(l.output, l.outputs*l.batch, l.activation);
}

void backward_activation_layer(layer l, network_state state)
{
    gradient_array(l.output, l.outputs*l.batch, l.activation, l.delta);
    copy_cpu(l.outputs*l.batch, l.delta, 1, state.delta, 1);
}

#ifdef GPU

void forward_activation_layer_gpu(layer l, network_state state)
{
    copy_ongpu(l.outputs*l.batch, state.input, 1, l.output_gpu, 1);
    activate_array_ongpu(l.output_gpu, l.outputs*l.batch, l.activation);
}

void backward_activation_layer_gpu(layer l, network_state state)
{
    gradient_array_ongpu(l.output_gpu, l.outputs*l.batch, l.activation, l.delta_gpu);
    copy_ongpu(l.outputs*l.batch, l.delta_gpu, 1, state.delta, 1);
}
#endif