diff --git a/paddle/phi/api/lib/api_custom_impl.cc b/paddle/phi/api/lib/api_custom_impl.cc
index 88fefb8eac99da13d921811f02430c8e2a78290d..056b9d79c84e2db5b0815639e4c2495b0a8867cd 100644
--- a/paddle/phi/api/lib/api_custom_impl.cc
+++ b/paddle/phi/api/lib/api_custom_impl.cc
@@ -714,7 +714,11 @@ std::vector<Tensor> split_impl(const Tensor& x,
   // Calculate the number of out tensors
   size_t out_number;
   if (num_or_sections.size() == 1) {
-    out_number = num_or_sections.GetData()[0];
+    if (num_or_sections.GetData()[0] < 0) {
+      out_number = 1;
+    } else {
+      out_number = num_or_sections.GetData()[0];
+    }
   } else {
     out_number = num_or_sections.size();
   }
diff --git a/paddle/phi/infermeta/unary.cc b/paddle/phi/infermeta/unary.cc
index bdcef965be2585adc523835b9b18fdc645af3178..14f0951c3d26ea76f2b25fc13e09d3f7cc3dee63 100644
--- a/paddle/phi/infermeta/unary.cc
+++ b/paddle/phi/infermeta/unary.cc
@@ -2947,7 +2947,7 @@ void SplitInferMeta(const MetaTensor& x,
   // step1: get formated sections
   std::vector<int64_t> sections;
   // num_or_sections is a number
-  if (num_or_sections_data.size() == 1) {
+  if (num_or_sections_data.size() == 1 && num_or_sections_data[0] > 0) {
     int num = num_or_sections_data.at(0);
 
     PADDLE_ENFORCE_EQ(input_axis_dim % num,
diff --git a/python/paddle/fluid/tests/unittests/test_split_op.py b/python/paddle/fluid/tests/unittests/test_split_op.py
index e3f72d7b41ca26bdc46ab49b256bf96a954b7dc4..4f438e26a7bb6fa1a0f87e944fe3338db5b89c7e 100644
--- a/python/paddle/fluid/tests/unittests/test_split_op.py
+++ b/python/paddle/fluid/tests/unittests/test_split_op.py
@@ -503,6 +503,21 @@ class API_TestDygraphSplit(unittest.TestCase):
         self.assertTrue(np.allclose(ex_x1, x1_out))
         self.assertTrue(np.allclose(ex_x2, x2_out))
 
+    def func_negative_one_section(self):
+        with fluid.dygraph.guard():
+            input_1 = np.random.random([4, 6, 6]).astype("int32")
+            # input is a variable which shape is [4, 6, 6]
+            input = paddle.to_tensor(input_1)
+            num1 = paddle.full(shape=[1], fill_value=1, dtype='int32')
+            x0 = paddle.split(input, num_or_sections=[-1], axis=num1)
+            x0_out = x0[0].numpy()
+        self.assertTrue(np.array_equal(x0_out, input.numpy()))
+
+    def test_negative_one_section(self):
+        with _test_eager_guard():
+            self.func_negative_one_section()
+        self.func_negative_one_section()
+
 
 class API_TestEmptySplit(unittest.TestCase):