| | |
| | | GPU=1 |
| | | DEBUG=0 |
| | | ARCH= -arch=sm_50 |
| | | ARCH= -arch=sm_52 |
| | | |
| | | VPATH=./src/ |
| | | EXEC=darknet |
| | |
| | | #include "blas.h" |
| | | #include "assert.h" |
| | | #include <stdlib.h> |
| | | #include <time.h> |
| | | |
| | | |
| | | void check_error(cudaError_t status) |
| | |
| | | static int init = 0; |
| | | if(!init){ |
| | | curandCreateGenerator(&gen, CURAND_RNG_PSEUDO_DEFAULT); |
| | | curandSetPseudoRandomGeneratorSeed(gen, 0ULL); |
| | | curandSetPseudoRandomGeneratorSeed(gen, time(0)); |
| | | init = 1; |
| | | } |
| | | curandGenerateUniform(gen, x_gpu, n); |
| | |
| | | if(weightfile){ |
| | | load_weights_upto(&net, weightfile, max); |
| | | } |
| | | //net.seen = 0; |
| | | save_weights(net, outfile); |
| | | } |
| | | |
| | |
| | | if (!state.train) return; |
| | | int size = layer.inputs*layer.batch; |
| | | cuda_random(layer.rand_gpu, size); |
| | | /* |
| | | int i; |
| | | for(i = 0; i < size; ++i){ |
| | | layer.rand[i] = rand_uniform(); |
| | | } |
| | | cuda_push_array(layer.rand_gpu, layer.rand, size); |
| | | */ |
| | | |
| | | yoloswag420blazeit360noscope<<<cuda_gridsize(size), BLOCK>>>(state.input, size, layer.rand_gpu, layer.probability, layer.scale); |
| | | check_error(cudaPeekAtLastError()); |