| #include <iostream> | |
| #include "ATen/ATen.h" | |
| #include "ATen/Dispatch.h" | |
| using std::cout; | |
| using namespace at; | |
| constexpr auto Float = ScalarType::Float; | |
| template<typename scalar_type> | |
| struct Foo { | |
| static void CPU(const Type & t, Tensor a, Tensor b) { | |
| scalar_type s = 1; | |
| cout << "hello, dispatch: " << t.toString() << s << "\n"; | |
| auto data = (scalar_type*)a.data_ptr(); | |
| (void)data; | |
| } | |
| static void CUDA(const Type & t, Tensor a, Tensor b) { | |
| } | |
| }; | |
| template<> | |
| struct Foo<Half> { | |
| static void CPU(const Type & t, Tensor a, Tensor b) {} | |
| static void CUDA(const Type & t, Tensor a, Tensor b) {} | |
| }; | |
| int main() { | |
| Scalar what = 257; | |
| Scalar bar = 3.0; | |
| Half h = bar.toHalf(); | |
| Scalar h2 = h; | |
| cout << "H2: " << h2.toDouble() << " " << what.toFloat() << " " << bar.toDouble() << " " << what.isIntegral() << "\n"; | |
| Generator & gen = at::globalContext().defaultGenerator(Backend::CPU); | |
| cout << gen.seed() << "\n"; | |
| auto && C = at::globalContext(); | |
| if(at::hasCUDA()) { | |
| auto & CUDAFloat = C.getType(Backend::CPU,ScalarType::Float); | |
| auto t2 = CUDAFloat.zeros({4,4}); | |
| cout << &t2 << "\n"; | |
| cout << "AFTER GET TYPE " << &CUDAFloat << "\n"; | |
| cout << "STORAGE: " << CUDAFloat.storage(4).get() << "\n"; | |
| auto s = CUDAFloat.storage(4); | |
| s->fill(7); | |
| cout << "GET " << s->get(3).toFloat() << "\n"; | |
| } | |
| auto t = CPU(Float).ones({4,4}); | |
| auto wha2 = CPU(Float).zeros({4,4}).add(t).sum(); | |
| cout << wha2.toDouble() << " <-ndim\n"; | |
| cout << t.sizes() << " " << t.strides() << "\n"; | |
| auto output = CPU(Float).ones(3); | |
| at::Abs_updateOutput(t,output); | |
| Type & T = CPU(Float); | |
| Tensor x = T.randn({1,10}); | |
| Tensor prev_h = T.randn({1,20}); | |
| Tensor W_h = T.randn({20,20}); | |
| Tensor W_x = T.randn({20,10}); | |
| Tensor i2h = at::mm(W_x, x.t()); | |
| Tensor h2h = at::mm(W_h, prev_h.t()); | |
| Tensor next_h = i2h.add(h2h); | |
| next_h = next_h.tanh(); | |
| if(at::hasCUDA()) { | |
| auto r = CUDA(Float).copy(next_h); | |
| cout << r << "\n"; | |
| } | |
| cout << T.randn({10,10,2}) << "\n"; | |
| dispatch<Foo>(x.type(),x,prev_h); | |
| return 0; | |
| } |