#include "cost_layer.h"
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#include "utils.h"
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#include "mini_blas.h"
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#include <math.h>
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#include <string.h>
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#include <stdlib.h>
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#include <stdio.h>
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COST_TYPE get_cost_type(char *s)
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{
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if (strcmp(s, "sse")==0) return SSE;
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if (strcmp(s, "detection")==0) return DETECTION;
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fprintf(stderr, "Couldn't find activation function %s, going with SSE\n", s);
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return SSE;
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}
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char *get_cost_string(COST_TYPE a)
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{
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switch(a){
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case SSE:
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return "sse";
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case DETECTION:
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return "detection";
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}
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return "sse";
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}
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cost_layer *make_cost_layer(int batch, int inputs, COST_TYPE type)
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{
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fprintf(stderr, "Cost Layer: %d inputs\n", inputs);
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cost_layer *layer = calloc(1, sizeof(cost_layer));
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layer->batch = batch;
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layer->inputs = inputs;
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layer->type = type;
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layer->delta = calloc(inputs*batch, sizeof(float));
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layer->output = calloc(1, sizeof(float));
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#ifdef GPU
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layer->delta_cl = cl_make_array(layer->delta, inputs*batch);
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#endif
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return layer;
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}
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void forward_cost_layer(cost_layer layer, float *input, float *truth)
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{
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if (!truth) return;
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copy_cpu(layer.batch*layer.inputs, truth, 1, layer.delta, 1);
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axpy_cpu(layer.batch*layer.inputs, -1, input, 1, layer.delta, 1);
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if(layer.type == DETECTION){
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int i;
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for(i = 0; i < layer.batch*layer.inputs; ++i){
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if((i%5) && !truth[(i/5)*5]) layer.delta[i] = 0;
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}
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}
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*(layer.output) = dot_cpu(layer.batch*layer.inputs, layer.delta, 1, layer.delta, 1);
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//printf("cost: %f\n", *layer.output);
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}
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void backward_cost_layer(const cost_layer layer, float *input, float *delta)
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{
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copy_cpu(layer.batch*layer.inputs, layer.delta, 1, delta, 1);
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}
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#ifdef GPU
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cl_kernel get_mask_kernel()
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{
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static int init = 0;
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static cl_kernel kernel;
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if(!init){
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kernel = get_kernel("src/axpy.cl", "mask", 0);
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init = 1;
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}
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return kernel;
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}
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void mask_ongpu(int n, cl_mem x, cl_mem mask, int mod)
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{
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cl_kernel kernel = get_mask_kernel();
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cl_command_queue queue = cl.queue;
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cl_uint i = 0;
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cl.error = clSetKernelArg(kernel, i++, sizeof(n), (void*) &n);
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cl.error = clSetKernelArg(kernel, i++, sizeof(x), (void*) &x);
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cl.error = clSetKernelArg(kernel, i++, sizeof(mask), (void*) &mask);
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cl.error = clSetKernelArg(kernel, i++, sizeof(mod), (void*) &mod);
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check_error(cl);
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const size_t global_size[] = {n};
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cl.error = clEnqueueNDRangeKernel(queue, kernel, 1, 0, global_size, 0, 0, 0, 0);
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check_error(cl);
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}
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void forward_cost_layer_gpu(cost_layer layer, cl_mem input, cl_mem truth)
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{
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if (!truth) return;
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copy_ongpu(layer.batch*layer.inputs, truth, 1, layer.delta_cl, 1);
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axpy_ongpu(layer.batch*layer.inputs, -1, input, 1, layer.delta_cl, 1);
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if(layer.type==DETECTION){
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mask_ongpu(layer.inputs*layer.batch, layer.delta_cl, truth, 5);
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}
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cl_read_array(layer.delta_cl, layer.delta, layer.batch*layer.inputs);
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*(layer.output) = dot_cpu(layer.batch*layer.inputs, layer.delta, 1, layer.delta, 1);
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//printf("cost: %f\n", *layer.output);
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}
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void backward_cost_layer_gpu(const cost_layer layer, cl_mem input, cl_mem delta)
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{
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copy_ongpu(layer.batch*layer.inputs, layer.delta_cl, 1, delta, 1);
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}
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#endif
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