#include "dropout_layer.h"
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#include "utils.h"
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#include <stdlib.h>
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#include <stdio.h>
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dropout_layer *make_dropout_layer(int batch, int inputs, float probability)
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{
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fprintf(stderr, "Dropout Layer: %d inputs, %f probability\n", inputs, probability);
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dropout_layer *layer = calloc(1, sizeof(dropout_layer));
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layer->probability = probability;
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layer->inputs = inputs;
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layer->batch = batch;
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layer->output = calloc(inputs*batch, sizeof(float));
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layer->rand = calloc(inputs*batch, sizeof(float));
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layer->scale = 1./(1.-probability);
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#ifdef GPU
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layer->output_cl = cl_make_array(layer->output, inputs*batch);
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layer->rand_cl = cl_make_array(layer->rand, inputs*batch);
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#endif
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return layer;
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}
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void forward_dropout_layer(dropout_layer layer, float *input)
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{
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int i;
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for(i = 0; i < layer.batch * layer.inputs; ++i){
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float r = rand_uniform();
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layer.rand[i] = r;
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if(r < layer.probability) layer.output[i] = 0;
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else layer.output[i] = input[i]*layer.scale;
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}
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}
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void backward_dropout_layer(dropout_layer layer, float *delta)
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{
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int i;
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if(!delta) return;
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for(i = 0; i < layer.batch * layer.inputs; ++i){
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float r = layer.rand[i];
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if(r < layer.probability) delta[i] = 0;
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else delta[i] *= layer.scale;
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}
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}
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#ifdef GPU
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cl_kernel get_dropout_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/dropout_layer.cl", "yoloswag420blazeit360noscope", 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 forward_dropout_layer_gpu(dropout_layer layer, cl_mem input)
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{
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int j;
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int size = layer.inputs*layer.batch;
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for(j = 0; j < size; ++j) layer.rand[j] = rand_uniform();
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cl_write_array(layer.rand_cl, layer.rand, layer.inputs*layer.batch);
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cl_kernel kernel = get_dropout_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(input), (void*) &input);
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cl.error = clSetKernelArg(kernel, i++, sizeof(layer.rand_cl), (void*) &layer.rand_cl);
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cl.error = clSetKernelArg(kernel, i++, sizeof(layer.probability), (void*) &layer.probability);
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cl.error = clSetKernelArg(kernel, i++, sizeof(layer.scale), (void*) &layer.scale);
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cl.error = clSetKernelArg(kernel, i++, sizeof(layer.output_cl), (void*) &layer.output_cl);
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check_error(cl);
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const size_t global_size[] = {size};
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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 backward_dropout_layer_gpu(dropout_layer layer, cl_mem delta)
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{
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int size = layer.inputs*layer.batch;
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cl_kernel kernel = get_dropout_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(delta), (void*) &delta);
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cl.error = clSetKernelArg(kernel, i++, sizeof(layer.rand_cl), (void*) &layer.rand_cl);
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cl.error = clSetKernelArg(kernel, i++, sizeof(layer.probability), (void*) &layer.probability);
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cl.error = clSetKernelArg(kernel, i++, sizeof(layer.scale), (void*) &layer.scale);
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cl.error = clSetKernelArg(kernel, i++, sizeof(delta), (void*) &delta);
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check_error(cl);
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const size_t global_size[] = {size};
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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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#endif
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