diff --git a/mindspore/python/mindspore/ops/_grad_experimental/grad_sparse_ops.py b/mindspore/python/mindspore/ops/_grad_experimental/grad_sparse_ops.py
index d9470173b39..bcba86d5a4a 100644
--- a/mindspore/python/mindspore/ops/_grad_experimental/grad_sparse_ops.py
+++ b/mindspore/python/mindspore/ops/_grad_experimental/grad_sparse_ops.py
@@ -133,7 +133,7 @@ def get_bprop_sparse_softmax(self):
         default_values = _create_tensor(0, values.dtype)
         out_dout = mul(out, dout)
         sp_product = sparse_to_dense(indices, shape, out_dout, default_values)
-        sum_reduced = -reduce_sum(sp_product, -1)
+        sum_reduced = -1 * reduce_sum(sp_product, -1)
         sp_sum = sparse_dense_cwise_add(indices, dout, shape, sum_reduced)
         grad_x = mul(sp_sum, out)
         return zeros_like(indices), grad_x, zeros_like(shape)
@@ -387,7 +387,7 @@ def get_bprop_sparse_reorder(self):
     def bprop(indices, values, shape, out, dout):
         num_entries = F.shape(indices)[0]
         start = Tensor(0, dtype=mstype.int32)
-        limit = Tensor(num_entries, dtype=mstype.int32)
+        limit = P.Cast()(num_entries, mstype.int32)
         delta = Tensor(1, dtype=mstype.int32)
         entry_indices = range_op(start, limit, delta)
         output = sparse_reorder_op(indices, entry_indices, shape)