mirror of https://github.com/pjreddie/darknet.git
91 lines
2.9 KiB
C
91 lines
2.9 KiB
C
#include "shortcut_layer.h"
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#include "cuda.h"
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#include "blas.h"
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#include "activations.h"
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#include <stdio.h>
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#include <assert.h>
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layer make_shortcut_layer(int batch, int index, int w, int h, int c, int w2, int h2, int c2)
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{
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fprintf(stderr, "res %3d %4d x%4d x%4d -> %4d x%4d x%4d\n",index, w2,h2,c2, w,h,c);
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layer l = {0};
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l.type = SHORTCUT;
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l.batch = batch;
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l.w = w2;
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l.h = h2;
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l.c = c2;
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l.out_w = w;
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l.out_h = h;
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l.out_c = c;
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l.outputs = w*h*c;
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l.inputs = l.outputs;
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l.index = index;
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l.delta = calloc(l.outputs*batch, sizeof(float));
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l.output = calloc(l.outputs*batch, sizeof(float));;
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l.forward = forward_shortcut_layer;
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l.backward = backward_shortcut_layer;
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#ifdef GPU
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l.forward_gpu = forward_shortcut_layer_gpu;
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l.backward_gpu = backward_shortcut_layer_gpu;
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l.delta_gpu = cuda_make_array(l.delta, l.outputs*batch);
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l.output_gpu = cuda_make_array(l.output, l.outputs*batch);
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#endif
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return l;
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}
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void resize_shortcut_layer(layer *l, int w, int h)
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{
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assert(l->w == l->out_w);
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assert(l->h == l->out_h);
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l->w = l->out_w = w;
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l->h = l->out_h = h;
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l->outputs = w*h*l->out_c;
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l->inputs = l->outputs;
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l->delta = realloc(l->delta, l->outputs*l->batch*sizeof(float));
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l->output = realloc(l->output, l->outputs*l->batch*sizeof(float));
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#ifdef GPU
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cuda_free(l->output_gpu);
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cuda_free(l->delta_gpu);
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l->output_gpu = cuda_make_array(l->output, l->outputs*l->batch);
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l->delta_gpu = cuda_make_array(l->delta, l->outputs*l->batch);
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#endif
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}
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void forward_shortcut_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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shortcut_cpu(l.batch, l.w, l.h, l.c, net.layers[l.index].output, l.out_w, l.out_h, l.out_c, l.alpha, l.beta, l.output);
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activate_array(l.output, l.outputs*l.batch, l.activation);
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}
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void backward_shortcut_layer(const layer l, network net)
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{
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gradient_array(l.output, l.outputs*l.batch, l.activation, l.delta);
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axpy_cpu(l.outputs*l.batch, l.alpha, l.delta, 1, net.delta, 1);
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shortcut_cpu(l.batch, l.out_w, l.out_h, l.out_c, l.delta, l.w, l.h, l.c, 1, l.beta, net.layers[l.index].delta);
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}
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#ifdef GPU
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void forward_shortcut_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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shortcut_gpu(l.batch, l.w, l.h, l.c, net.layers[l.index].output_gpu, l.out_w, l.out_h, l.out_c, l.alpha, l.beta, l.output_gpu);
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activate_array_gpu(l.output_gpu, l.outputs*l.batch, l.activation);
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}
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void backward_shortcut_layer_gpu(const layer l, network net)
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{
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gradient_array_gpu(l.output_gpu, l.outputs*l.batch, l.activation, l.delta_gpu);
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axpy_gpu(l.outputs*l.batch, l.alpha, l.delta_gpu, 1, net.delta_gpu, 1);
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shortcut_gpu(l.batch, l.out_w, l.out_h, l.out_c, l.delta_gpu, l.w, l.h, l.c, 1, l.beta, net.layers[l.index].delta_gpu);
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}
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#endif
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