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[dnn/conv] added triton-c code for wgrad

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This commit is contained in:
Philippe Tillet
2019-05-11 18:09:23 -04:00
parent fc4daf11dd
commit f6fe9492e4
3 changed files with 299 additions and 173 deletions
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26
examples/cpp/conv.cpp
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@@ -10,13 +10,13 @@ int main() {
// initialize default compute device
auto context = triton::driver::backend::contexts::get_default();
triton::jit jit(context);
triton::dnn::conv::type ty = triton::dnn::conv::BPROP;
triton::dnn::conv::type ty = triton::dnn::conv::WGRAD;
// initialization
int32_t B = 4, NF = 32;
int32_t D = 1, H = 24, W = 240;
int32_t NC = 32, T = 1, R = 3, S = 3;
int32_t pad_d = 0, pad_h = 1, pad_w = 1;
triton::dnn::conv configuration(B, NC, H, W, R, S, NF, 1, 1, pad_h, pad_w, ty);
triton::dnn::conv configuration(B, NC, D, H, W, T, R, S, NF, 1, 1, 1, pad_d, pad_h, pad_w, ty);
// convolution configuration
std::vector<float> hc(configuration.c_size());
std::vector<float> rc(configuration.c_size());
@@ -40,8 +40,10 @@ int main() {
stream->synchronize();
// look-up table
std::vector<int> h_delta, h_masks;
configuration.build_deltas(h_delta);
configuration.build_masks(h_masks);
if(ty != triton::dnn::conv::WGRAD){
configuration.build_deltas(h_delta);
configuration.build_masks(h_masks);
}
// benchmark a given convolution kernel
auto benchmark = [&](triton::driver::kernel* kernel,
triton::jit::launch_information info) {
@@ -49,10 +51,12 @@ int main() {
unsigned TN = info.global_range_size[1];
unsigned nthreads = info.num_threads;
std::array<size_t, 3> grid = configuration.get_grid(TM, TN);
triton::driver::buffer* delta = jit.get_buffer("delta");
triton::driver::buffer* masks = jit.get_buffer("masks");
stream->write(delta, false, 0, h_delta.size()*4, h_delta.data());
stream->write(masks, false, 0, h_masks.size()*4, h_masks.data());
if(ty != triton::dnn::conv::WGRAD){
triton::driver::buffer* delta = jit.get_buffer("delta");
triton::driver::buffer* masks = jit.get_buffer("masks");
stream->write(delta, false, 0, h_delta.size()*4, h_delta.data());
stream->write(masks, false, 0, h_masks.size()*4, h_masks.data());
}
stream->synchronize();
configuration.set_arg(kernel, da, db, dc);
stream->enqueue(kernel, grid, {nthreads, 1, 1});
@@ -69,11 +73,11 @@ int main() {
std::cout << "Performance: " << benchmark(kernel, info) << " TFLOPS " << std::endl;
stream->read(dc, true, 0, hc);
configuration.cpu_ref(rc.data(), ha.data(), hb.data());
// std::cout << c[0] << std::endl;
for(size_t i = 0; i < hc.size(); i++)
for(size_t i = 0; i < hc.size(); i++){
if(std::abs(hc[i] - rc[i])/std::max(hc[i], rc[i]) > 1e-4){
std::cout << i << " " << hc[i] << " " << rc[i] << std::endl;
exit(EXIT_FAILURE);
}
}
}
std::cout << "Pass!" << std::endl;
}