Fixed segfault when trying to permute empty tensor (pytorch#116335)

Fixes pytorch#116325.

Fixed unchecked access to first element of `dims` when permuting an empty tensor. Added test to prevent regressions.

Pull Request resolved: pytorch#116335
Approved by: https://github.com/Skylion007

aten/src/ATen/native/TensorShape.cpp

@@ -1503,8 +1503,7 @@ Tensor permute_sparse_coo(const Tensor& self, IntArrayRef dims) {
       }
       return old_values.permute(values_perm);
     }();
-
-  const auto is_coalesced = self.is_coalesced() && (dims[0] == 0);
+  const auto is_coalesced = self.is_coalesced() && (dims.empty() || dims[0] == 0);
   // TODO: apply `is_coalesced ||= new_values.size(0) < 2`.
   return _sparse_coo_tensor_with_dims_and_tensors(
        sparse_ndim, dense_ndim, new_sizes, new_indices, new_values, self.options(), is_coalesced);

test/test_sparse.py

@@ -952,6 +952,11 @@ def test_permute(self, device, dtype, coalesced, gradcheck):
             s.permute(dims=(1, 0))
         with self.assertRaisesRegex(RuntimeError, "duplicate dims"):
             s.permute(dims=(1, 1, 1))
+        # Calling permute on a sparse tensor with an empty tuple used to segfault,
+        # see https://github.com/pytorch/pytorch/issues/116325
+        x = torch.rand((), device=device, dtype=dtype).to_sparse()
+        x.permute(())
+        self.assertEqual(len(x.values()), 1)
 
         def test_shape(sparse_dims, nnz, with_size):
             ndim = len(with_size)