diff --git a/mindspore/ccsrc/optimizer/irpass/reshape_eliminate.h b/mindspore/ccsrc/optimizer/irpass/reshape_eliminate.h
index 5e7ce7cdd73..f1f73de4d93 100644
--- a/mindspore/ccsrc/optimizer/irpass/reshape_eliminate.h
+++ b/mindspore/ccsrc/optimizer/irpass/reshape_eliminate.h
@@ -88,7 +88,9 @@ class TwoReshapeEliminater : public AnfVisitor {
 
     auto fg = node->func_graph();
     if (fg != nullptr && x_ != nullptr && shape_ != nullptr) {
-      return fg->NewCNode({NewValueNode(prim_), x_, shape_});
+      auto new_node = fg->NewCNode({NewValueNode(prim_), x_, shape_});
+      new_node->set_abstract(node->abstract());
+      return new_node;
     }
     return nullptr;
   }
diff --git a/tests/ut/python/parallel/test_auto_parallel_reshape.py b/tests/ut/python/parallel/test_auto_parallel_reshape.py
index 0f987ddcb03..5b71d47a44c 100644
--- a/tests/ut/python/parallel/test_auto_parallel_reshape.py
+++ b/tests/ut/python/parallel/test_auto_parallel_reshape.py
@@ -45,7 +45,6 @@ class GradWrap(nn.Cell):
         return C.grad_all(self.network)(x)
 
 
-# core dump, step_auto_parallel should SetInputs for transpose axis
 def test_reshape_matmul():
     class Net(nn.Cell):
         def __init__(self):
@@ -68,6 +67,28 @@ def test_reshape_matmul():
     net.set_auto_parallel()
     _executor.compile(net, x)
 
+def test_reshape_reshape():
+    class Net(nn.Cell):
+        def __init__(self):
+            super().__init__()
+            self.reshape = P.Reshape()
+            self.relu = P.ReLU()
+
+        def construct(self, x):
+            x = self.relu(x)
+            out = self.reshape(x, (64, 28))
+            out = self.reshape(out, (64, 28, 1))
+            return out
+
+    size = 8
+    context.set_auto_parallel_context(device_num=size, global_rank=0)
+    x = Tensor(np.ones([8 * size, 28, 1, 1]), dtype=ms.float32)
+
+    net = GradWrap(NetWithLoss(Net()))
+    context.set_auto_parallel_context(parallel_mode="auto_parallel")
+    net.set_auto_parallel()
+    _executor.compile(net, x)
+
 
 def test_reshape_auto_1():
     class Net(nn.Cell):