#include "op_plugin/AclOpsInterface.h"
#include "op_plugin/utils/OpAdapter.h"
namespace acl_op {
using npu_preparation = at_npu::native::OpPreparation;
namespace {
at::Tensor& pdist_out_npu_nocheck(
at::Tensor& result,
const at::Tensor& self,
float p)
{
at_npu::native::OpCommand cmd;
cmd.Name("Pdist")
.Input(self)
.Attr("p", p)
.Output(result)
.Run();
return result;
}
}
at::Tensor _pdist_forward(const at::Tensor& self, double p)
{
at::Tensor result;
if (self.size(0) <= 1) {
result = npu_preparation::apply_tensor(self, {0});
} else {
float p_float;
if (std::isinf(p)) {
p_float = std::numeric_limits<float>::infinity();
} else {
TORCH_CHECK(
p <= std::numeric_limits<float>::max(), "npu dose not support float64" + OPS_ERROR(ErrCode::TYPE));
p_float = static_cast<float>(p);
}
auto output_size = op_infer::pdist_npu_output_size(self);
result = npu_preparation::apply_tensor(self, output_size);
if (self.size(1) == 0) {
acl_op::fill_(result, 0);
} else {
pdist_out_npu_nocheck(result, self, p_float);
}
}
return result;
}
at::Tensor pdist(const at::Tensor& self, double p)
{
TORCH_CHECK(self.dim() == 2,
"pdist only supports 2D tensors, got: ", self.dim(), "D", OPS_ERROR(ErrCode::PARAM));
TORCH_CHECK(at::isFloatingType(
self.scalar_type()), "pdist only supports floating-point dtypes" + OPS_ERROR(ErrCode::TYPE));
TORCH_CHECK(p >= 0, "pdist only supports non-negative p values" + OPS_ERROR(ErrCode::VALUE));
return at::_pdist_forward(self, p);
}
}