#include "src/cuda/group_local/opr_impl.h"

#include "src/common/utils.h"
#include "src/cuda/local/local.cuh"
#include "src/cuda/utils.h"

namespace megdnn {
namespace cuda {

void GroupLocalBackwardDataImpl::exec(
        _megdnn_tensor_in filter, _megdnn_tensor_in diff, _megdnn_tensor_out grad,
        _megdnn_workspace workspace) {
    check_exec(filter.layout, diff.layout, grad.layout, workspace.size);

    auto G = filter.layout[0];
    auto N = grad.layout.shape[0], IC = grad.layout.shape[1] / G,
         IH = grad.layout.shape[2], IW = grad.layout.shape[3],
         OC = diff.layout.shape[1] / G, OH = diff.layout.shape[2],
         OW = diff.layout.shape[3];
    auto FH = filter.layout.shape[4], FW = filter.layout.shape[5];
    auto PH = param().pad_h, PW = param().pad_w;
    auto SH = param().stride_h, SW = param().stride_w;
    float* sptr = grad.ptr<dt_float32>();
    const float* fptr = filter.ptr<dt_float32>();
    const float* dptr = diff.ptr<dt_float32>();
    float* wptr = workspace.ptr<dt_float32>();
    auto handle = concrete_handle(this->handle());
    auto stream = cuda_stream(this->handle());
    auto cublas = cublas_handle(this->handle());
    auto one = handle->one_device();
    auto zero = handle->zero_device();
    megdnn_assert(
            local::can_backward_data_proxy_convnet(
                    N, IC, IH, IW, OC, OH, OW, FH, FW, G * IC * IH * IW,
                    G * OC * OH * OW, PH, PW, SH, SW),
            "Cannot do Group Local bwd data.");
    for (size_t g = 0; g < G; ++g) {
        local::backward_data_proxy_convnet(
                fptr + g * OH * OW * IC * FH * FW * OC, dptr + g * OC * OH * OW,
                sptr + g * IC * IH * IW, wptr, N, IC, IH, IW, OC, OH, OW, FH, FW,
                G * IC * IH * IW, G * OC * OH * OW, PH, PW, SH, SW, cublas, stream, one,
                zero);
    }
}

GroupLocalBackwardDataImpl::GroupLocalBackwardDataImpl(Handle* handle)
        : GroupLocalBackwardData(handle) {}

size_t GroupLocalBackwardDataImpl::get_workspace_in_bytes(
        const TensorLayout& filter, const TensorLayout& diff,
        const TensorLayout& grad) {
    auto G = filter[0];
    auto N = grad.shape[0], IC = grad.shape[1] / G, IH = grad.shape[2],
         IW = grad.shape[3], OC = diff.shape[1] / G, OH = diff.shape[2],
         OW = diff.shape[3];
    auto FH = filter.shape[4], FW = filter.shape[5];
    auto PH = param().pad_h, PW = param().pad_w;
    auto SH = param().stride_h, SW = param().stride_w;
    auto res = local::get_workspace_in_floats_backward_data_proxy_convnet(
                       N, IC, IH, IW, OC, OH, OW, FH, FW, G * IC * IH * IW,
                       G * OC * OH * OW, PH, PW, SH, SW) *
               sizeof(float);
    return res;
}

}  // namespace cuda
}  // namespace megdnn
// vim: syntax=cpp.doxygen
