Unable to call c++ op which has a `int64_t` parameter

I created a c++ function and registered it as follow:

void to_csr_index(torch::Tensor &row_ptr, const torch::Tensor &edge_index_i, int64_t num_rows) {
    auto *prow_ptr = row_ptr.data_ptr<int32_t>();
    for (uint32_t i = 0; i < edge_index_i.size(0); ++i) {
        prow_ptr[edge_index_i[i].item<int32_t>() + 1]++;
    for (int i = 0; i < num_rows; i++) {
        prow_ptr[i + 1] += prow_ptr[i];

TORCH_LIBRARY(my_ops, m) {
    m.def("to_csr_index", to_csr_index);

Then I called it with:

num_nodes = data[AtomicDataDict.NODE_FEATURES_KEY].shape[0]
row_ptr = torch.zeros(num_nodes, dtype=edge_index_i.dtype)
torch.ops.my_ops.to_csr_index(row_ptr, edge_index_i, num_nodes)

Here is the error message:

  File "/home/dym/code/torch-ff/Torch-FF/src/models/components/encoder/_edge.py", line 71, in to_csr
    torch.ops.my_ops.to_csr_index(row_ptr, edge_index_i, num_nodes)
  File "/home/dym/.conda/envs/torch2.1.0/lib/python3.10/site-packages/torch/_ops.py", line 692, in __call__
    return self._op(*args, **kwargs or {})
RuntimeError: expected scalar type Int but found Long

Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.

How to fix it?

The problem is not that the int64_t parameter, but that you pass a int64 tensor row_ptr and/or edge_index_i and then access it with the incompatible .data_ptr<int32_t>() and .item<int32_t>().
Either cast the tensors to torch.int32 aka torch.int or use int64_t in the template parameter.

Best regards


1 Like

Thank you! it works!