#include "op_plugin/AclOpsInterface.h"
#include "op_plugin/utils/OpAdapter.h"
namespace acl_op {
using npu_preparation = at_npu::native::OpPreparation;
using npu_utils = at_npu::native::NpuUtils;
namespace {
at::Tensor& glu_npu_out_nocheck(at::Tensor& result, const at::Tensor& self, int64_t dim)
{
at_npu::native::OpCommand cmd;
cmd.Name("GLU")
.Input(self)
.Output(result)
.Attr("dim", dim)
.Run();
return result;
}
}
at::Tensor& glu_out(const at::Tensor& self, int64_t dim, at::Tensor& out)
{
auto output_size = op_infer::glu_npu_output_size(self, dim);
npu_preparation::CheckOut(
{self},
out,
self,
output_size);
TORCH_CHECK(self.dim() > 0, "glu does not support 0-dimensional at::Tensors" + OPS_ERROR(ErrCode::NOT_SUPPORT));
auto wrap_dim = at::maybe_wrap_dim(dim, self.dim());
const int64_t n_in = self.size(wrap_dim);
TORCH_CHECK(n_in % 2 == 0, "Halving dimension must be even, but dimension ", wrap_dim, " is size ", n_in,
OPS_ERROR(ErrCode::PARAM));
if (!npu_utils::check_match(&out)) {
at::Tensor contiguous_result = npu_utils::format_contiguous(out);
glu_npu_out_nocheck(contiguous_result, self, dim);
npu_utils::format_fresh_view(out, contiguous_result);
} else {
glu_npu_out_nocheck(out, self, dim);
}
return out;
}
at::Tensor glu(const at::Tensor& self, int64_t dim)
{
TORCH_CHECK(self.dim() > 0, "glu does not support 0-dimensional at::Tensors" + OPS_ERROR(ErrCode::NOT_SUPPORT));
auto wrap_dim = at::maybe_wrap_dim(dim, self.dim());
const int64_t n_in = self.size(wrap_dim);
TORCH_CHECK(n_in % 2 == 0, "Halving dimension must be even, but dimension ", wrap_dim, " is size ", n_in,
OPS_ERROR(ErrCode::PARAM));
auto output_size = op_infer::glu_npu_output_size(self, dim);
at::Tensor result = npu_preparation::apply_tensor(self, output_size);
glu_npu_out_nocheck(result, self, dim);
return result;
}
}