add relabeling

csrc/cpu/relabel_cpu.cpp

+#include "relabel_cpu.h"
+
+#include "utils.h"
+
+std::tuple<torch::Tensor, torch::Tensor> relabel_cpu(torch::Tensor col,
+                                                     torch::Tensor idx) {
+
+  CHECK_CPU(col);
+  CHECK_CPU(idx);
+  CHECK_INPUT(idx.dim() == 1);
+
+  auto col_data = col.data_ptr<int64_t>();
+  auto idx_data = idx.data_ptr<int64_t>();
+
+  std::vector<int64_t> cols;
+  std::vector<int64_t> n_ids;
+  std::unordered_map<int64_t, int64_t> n_id_map;
+
+  int64_t i;
+  for (int64_t n = 0; n < idx.size(0); n++) {
+    i = idx_data[n];
+    n_id_map[i] = n;
+    n_ids.push_back(i);
+  }
+
+  int64_t c;
+  for (int64_t e = 0; e < col.size(0); e++) {
+    c = col_data[e];
+
+    if (n_id_map.count(c) == 0) {
+      n_id_map[c] = n_ids.size();
+      n_ids.push_back(c);
+    }
+
+    cols.push_back(n_id_map[c]);
+  }
+
+  int64_t n_len = n_ids.size(), e_len = cols.size();
+  auto out_col = torch::from_blob(cols.data(), {e_len}, col.options()).clone();
+  auto out_idx = torch::from_blob(n_ids.data(), {n_len}, col.options()).clone();
+
+  return std::make_tuple(out_col, out_idx);
+}

csrc/cpu/relabel_cpu.h

+#pragma once
+
+#include <torch/extension.h>
+
+std::tuple<torch::Tensor, torch::Tensor> relabel_cpu(torch::Tensor col,
+                                                     torch::Tensor idx);

csrc/relabel.cpp

+#include <Python.h>
+#include <torch/script.h>
+
+#include "cpu/relabel_cpu.h"
+
+#ifdef _WIN32
+PyMODINIT_FUNC PyInit__relabel(void) { return NULL; }
+#endif
+
+std::tuple<torch::Tensor, torch::Tensor> relabel(torch::Tensor col,
+                                                 torch::Tensor idx) {
+  if (col.device().is_cuda()) {
+#ifdef WITH_CUDA
+    AT_ERROR("No CUDA version supported");
+#else
+    AT_ERROR("Not compiled with CUDA support");
+#endif
+  } else {
+    return relabel_cpu(col, idx);
+  }
+}
+
+static auto registry =
+    torch::RegisterOperators().op("torch_sparse::relabel", &relabel);

torch_sparse/__init__.py

@@ -7,7 +7,7 @@ __version__ = '0.6.6'
 
 for library in [
         '_version', '_convert', '_diag', '_spmm', '_spspmm', '_metis', '_rw',
-        '_saint', '_sample'
+        '_saint', '_sample', '_relabel'
 ]:
     torch.ops.load_library(importlib.machinery.PathFinder().find_spec(
         library, [osp.dirname(__file__)]).origin)