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[dnn]: Now implementing all existing DNN routines using common base template and auto-tuner

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This commit is contained in:
Philippe Tillet
2019-07-09 17:30:58 -07:00
parent 88675fa01a
commit b7986baffa
19 changed files with 388 additions and 375 deletions
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33
examples/cpp/conv.cpp
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@@ -10,7 +10,6 @@
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::FPROP;
// initialization
int32_t B = 16, NF = 128;
@@ -19,8 +18,12 @@ int main() {
int32_t pad_d = 0, pad_h = 0, pad_w = 0;
int32_t stride_d = 1, stride_h = 1, stride_w = 1;
int32_t upsample_d = 1, upsample_h = 1, upsample_w = 1;
triton::dnn::conv configuration(128, 256, 1, 14, 14, 1, 5, 5, 512, 1, 1, 1, 0, 0, 0, 1, 1, 1, "fp32", "fp32", triton::dnn::conv::FPROP, 0);
// triton::dnn::conv configuration(B, NC, D, H, W, T, R, S, NF, stride_d, stride_h, stride_w, pad_d, pad_h, pad_w, upsample_d, upsample_h, upsample_w, ty);
// triton::dnn::conv configuration(128, 256, 1, 14, 14, 1, 5, 5, 512, 1, 1, 1, 0, 0, 0, 1, 1, 1, "fp32", "fp32", triton::dnn::conv::FPROP, 0);
triton::dnn::conv configuration(B, NC, D, H, W, T, R, S, NF,
stride_d, stride_h, stride_w,
pad_d, pad_h, pad_w,
upsample_d, upsample_h, upsample_w,
"fp32", "fp32", ty, 0);
// convolution configuration
std::vector<float> hc(configuration.c_size());
std::vector<float> rc(configuration.c_size());
@@ -42,29 +45,7 @@ int main() {
stream->write(db, true, 0, hb);
stream->write(dc, true, 0, hc);
stream->synchronize();
// benchmark a given convolution kernel
auto benchmark = [&](triton::driver::kernel* kernel,
triton::jit::launch_information info) {
configuration.init(stream, (triton::driver::cu_module*)kernel->module());
unsigned TM = info.global_range_size[0];
unsigned TN = info.global_range_size[1];
unsigned nthreads = info.num_threads;
unsigned GZ = jit.get_int("GZ");
configuration.enqueue(stream, kernel, da, db, dc, nullptr, TM, TN, GZ, nthreads);
stream->synchronize();
double ts = triton::tools::bench([&](){ configuration.enqueue(stream, kernel, da, db, dc, nullptr, TM, TN, GZ, nthreads); },
[&](){ stream->synchronize(); }, nullptr);
return configuration.get_nflops() / ts * 1e-3;
};
std::ostringstream oss;
configuration.src(oss);
std::string src = oss.str();
triton::jit::tune_res_t best = jit.autotune("conv", src.c_str(), benchmark);
jit.add_module("conv", src.c_str(), best.params);
// jit.add_module("conv", src.c_str(), configuration.default_params());
triton::driver::kernel* kernel = jit.get_function("conv");
triton::jit::launch_information info = jit.get_launch_info("conv");
std::cout << "Performance: " << benchmark(kernel, info) << " TFLOPS " << std::endl;
configuration.enqueue(stream, {da, db, dc, nullptr});
stream->read(dc, true, 0, hc);
configuration.cpu_ref(rc.data(), ha.data(), hb.data());
for(size_t i = 0; i < hc.size(); i++){