mirror of https://github.com/pjreddie/darknet.git
64 lines
1.8 KiB
C
64 lines
1.8 KiB
C
#include "l2norm_layer.h"
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#include "activations.h"
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#include "blas.h"
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#include "cuda.h"
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#include <float.h>
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#include <math.h>
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#include <stdlib.h>
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#include <stdio.h>
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#include <assert.h>
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layer make_l2norm_layer(int batch, int inputs)
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{
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fprintf(stderr, "l2norm %4d\n", inputs);
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layer l = {0};
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l.type = L2NORM;
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l.batch = batch;
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l.inputs = inputs;
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l.outputs = inputs;
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l.output = calloc(inputs*batch, sizeof(float));
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l.scales = calloc(inputs*batch, sizeof(float));
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l.delta = calloc(inputs*batch, sizeof(float));
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l.forward = forward_l2norm_layer;
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l.backward = backward_l2norm_layer;
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#ifdef GPU
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l.forward_gpu = forward_l2norm_layer_gpu;
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l.backward_gpu = backward_l2norm_layer_gpu;
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l.output_gpu = cuda_make_array(l.output, inputs*batch);
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l.scales_gpu = cuda_make_array(l.output, inputs*batch);
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l.delta_gpu = cuda_make_array(l.delta, inputs*batch);
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#endif
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return l;
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}
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void forward_l2norm_layer(const layer l, network net)
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{
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copy_cpu(l.outputs*l.batch, net.input, 1, l.output, 1);
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l2normalize_cpu(l.output, l.scales, l.batch, l.out_c, l.out_w*l.out_h);
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}
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void backward_l2norm_layer(const layer l, network net)
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{
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//axpy_cpu(l.inputs*l.batch, 1, l.scales, 1, l.delta, 1);
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axpy_cpu(l.inputs*l.batch, 1, l.delta, 1, net.delta, 1);
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}
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#ifdef GPU
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void forward_l2norm_layer_gpu(const layer l, network net)
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{
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copy_gpu(l.outputs*l.batch, net.input_gpu, 1, l.output_gpu, 1);
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l2normalize_gpu(l.output_gpu, l.scales_gpu, l.batch, l.out_c, l.out_w*l.out_h);
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}
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void backward_l2norm_layer_gpu(const layer l, network net)
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{
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axpy_gpu(l.batch*l.inputs, 1, l.scales_gpu, 1, l.delta_gpu, 1);
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axpy_gpu(l.batch*l.inputs, 1, l.delta_gpu, 1, net.delta_gpu, 1);
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}
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#endif
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