| #include <torch/torch.h> |
| #include <vector> |
|
|
| std::vector<float*> dynamicconv_cpu_forward( |
| float* input, |
| float* filters, |
| int padding_l); |
|
|
| std::vector<float*> dynamicconv_cpu_backward( |
| float* gradOutput, |
| int padding_l, |
| float* input, |
| float* filters); |
|
|
| std::vector<float*> dynamicconv_forward( |
| float* input, |
| float* filters, |
| int padding_l) { |
|
|
| return dynamicconv_cpu_forward(input, filters, padding_l); |
| } |
|
|
| std::vector<float*> dynamicconv_backward( |
| float* gradOutput, |
| int padding_l, |
| float* input, |
| float* filters) { |
|
|
| return dynamicconv_cpu_backward(gradOutput, padding_l, input, filters); |
| } |
|
|
| PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) { |
| m.def("forward", &dynamicconv_forward, "dynamicconv forward (CPU)"); |
| m.def("backward", &dynamicconv_backward, "dynamicconv backward (CPU)"); |
| } |
|
|
