#include "src/cuda/mask_conv/opr_impl.h"
#include "./mask_conv.cuh"
#include "src/cuda/utils.h"
namespace megdnn {
namespace cuda {
MaskConvForwardImpl::MaskConvForwardImpl(Handle* handle) : MaskConvForward(handle) {
m_conv_opr =
static_cast<HandleImpl*>(handle)->create_operator<ConvolutionForward>();
}
void MaskConvForwardImpl::exec(
_megdnn_tensor_in src, _megdnn_tensor_in filter, _megdnn_tensor_in mask,
_megdnn_tensor_out dst, _megdnn_workspace workspace) {
megdnn_assert(
dst.layout.dtype.enumv() == DTypeTrait<dtype::Float32>::enumv,
"Mask conv only support Float32 dtype.");
m_conv_opr->exec(src, filter, dst, nullptr, workspace);
auto stream = cuda_stream(handle());
#define cb(DType) \
if (mask.layout.dtype == DType()) { \
using ctype = typename DTypeTrait<DType>::ctype; \
mask_conv::set_zero_by_mask_proxy<ctype>( \
dst.ptr<float>(), mask.ptr<ctype>(), dst.layout[0], dst.layout[1], \
dst.layout[2], dst.layout[3], stream); \
return; \
}
MEGDNN_FOREACH_COMPUTING_DTYPE_INT(cb)
#undef cb
megdnn_assert_internal(0);
}
void MaskPropagateImpl::exec(
_megdnn_tensor_in src, _megdnn_tensor_out dst, _megdnn_workspace) {
auto stream = cuda_stream(handle());
#define cb(DType) \
if (src.layout.dtype == DType()) { \
using ctype = typename DTypeTrait<DType>::ctype; \
mask_conv::mask_propagate_exec_proxy<ctype>( \
src.ptr<ctype>(), dst.ptr<ctype>(), src.layout[0], src.layout[1], \
dst.layout[0], dst.layout[1], param().kernel_h, param().kernel_w, \
param().stride_h, param().stride_w, param().pad_h, param().pad_w, \
param().dilate_h, param().dilate_w, stream); \
return; \
}
MEGDNN_FOREACH_COMPUTING_DTYPE_INT(cb);
#undef cb
megdnn_assert_internal(0);
}
} }