diff --git a/paddle/phi/infermeta/spmd_rules/reshape.cc b/paddle/phi/infermeta/spmd_rules/reshape.cc
index 9ca886f0dc637..20e1120aa6fda 100644
--- a/paddle/phi/infermeta/spmd_rules/reshape.cc
+++ b/paddle/phi/infermeta/spmd_rules/reshape.cc
@@ -125,6 +125,17 @@ std::vector<std::shared_ptr<DimTrans>> MakeReshapeDimTrans(
       for (auto in_dim : src_dims) {
         if (src_shape[in_dim] > 1) {
           input_dims.emplace_back(std::make_shared<InputDim>(in_dim));
+        } else if (src_shape[in_dim] == 1 && s == 1 && t == 1) {
+          // NOTE: for the case like:
+          //    shape: [1, 512, 4096] --> [1, 2, 256, 4096],
+          //    input dims_mapping: [0, 1, -1]
+          //    expected output dims_mapping: [0, 1, -1, -1] (not [-1, 1, -1,
+          //    -1])
+          // In this case, the dim0 in target shape is 1 and it is from
+          // dim0 in source shape. make the dim0's transformation be InputDim
+          // rather than Singleton so that the sharding status can be
+          // propagated.
+          input_dims.emplace_back(std::make_shared<InputDim>(in_dim));
         }
       }
       std::shared_ptr<DimTrans> flatten = make_flatten(input_dims);
diff --git a/test/auto_parallel/spmd_rules/test_reshape_rule.py b/test/auto_parallel/spmd_rules/test_reshape_rule.py
index 80ec33aecfcdb..e70761e705cb0 100644
--- a/test/auto_parallel/spmd_rules/test_reshape_rule.py
+++ b/test/auto_parallel/spmd_rules/test_reshape_rule.py
@@ -291,6 +291,22 @@ def test_reshape_infer_forward(self):
             infered_output_dist_attrs[0].dims_mapping, [1, -1, 0, -1]
         )
 
+        # shape: [1, 2048, 12288] --> [0, 0, 6, 2048]
+        # dims_mapping: [0, -1, 1] --> [0, -1, 1], [0, -1, 1, -1]
+        self.x_dist_tensor_spec.shape = [1, 2048, 12288]
+        self.attrs["shape"] = [0, 0, 6, 2048]
+        self.x_dist_tensor_spec.set_dims_mapping([0, -1, 1])
+        result_dist_attrs = self.rule.infer_forward(
+            self.x_dist_tensor_spec, self.attrs['shape']
+        )
+        infered_input_dist_attrs = result_dist_attrs[0]
+        infered_output_dist_attrs = result_dist_attrs[1]
+
+        self.assertEqual(infered_input_dist_attrs[0].dims_mapping, [0, -1, 1])
+        self.assertEqual(
+            infered_output_dist_attrs[0].dims_mapping, [0, -1, 1, -1]
+        )
+
         # shape: [6, 12, 48, 24] --> [3, 24, 6, -1, -1]
         # raise error
         self.attrs["shape"] = [3, 24, 6, -1, -1]