diff --git a/python/tvm/relay/frontend/onnx.py b/python/tvm/relay/frontend/onnx.py
index 5471f67ea106..170784bfb007 100644
--- a/python/tvm/relay/frontend/onnx.py
+++ b/python/tvm/relay/frontend/onnx.py
@@ -945,8 +945,9 @@ def _impl_v1(cls, inputs, attr, params):
         else:
             attr["layout"] = onnx_default_layout(dims=(len(input_shape) - 2), op_name="LpPool")
 
-        p = _expr.const(attr["p"], dtype)
-        reci_p = _expr.const(1.0 / attr["p"], dtype)
+        p_value = attr.get("p", 2)
+        p = _expr.const(p_value, dtype)
+        reci_p = _expr.const(1.0 / p_value, dtype)
         data = _op.power(data, p)
 
         out = AttrCvt(
diff --git a/tests/python/frontend/onnx/test_forward.py b/tests/python/frontend/onnx/test_forward.py
index 9e0eb1f75217..33c20d7c10e3 100644
--- a/tests/python/frontend/onnx/test_forward.py
+++ b/tests/python/frontend/onnx/test_forward.py
@@ -3185,15 +3185,18 @@ def verify_max_roi_pool(x_shape, rois_shape, pooled_shape, spatial_scale, out_sh
 @tvm.testing.parametrize_targets
 def test_lppool(target, dev):
     def verify_lppool(x_shape, kernel_shape, p, strides, pads, out_shape, auto_pad="NOTSET"):
+        kwargs = {}
+        if p is not None:
+            kwargs["p"] = p
         if pads is None:
             pool_node = helper.make_node(
                 "LpPool",
                 inputs=["x"],
                 outputs=["y"],
                 kernel_shape=kernel_shape,
-                p=p,
                 auto_pad=auto_pad,
                 strides=strides,
+                **kwargs,
             )
         else:
             pool_node = helper.make_node(
@@ -3201,9 +3204,9 @@ def verify_lppool(x_shape, kernel_shape, p, strides, pads, out_shape, auto_pad="
                 inputs=["x"],
                 outputs=["y"],
                 kernel_shape=kernel_shape,
-                p=p,
                 pads=pads,
                 strides=strides,
+                **kwargs,
             )
 
         graph = helper.make_graph(
@@ -3296,6 +3299,15 @@ def verify_lppool(x_shape, kernel_shape, p, strides, pads, out_shape, auto_pad="
         out_shape=[1, 1, 16, 16, 16],
         auto_pad="SAME_UPPER",
     )
+    # Pool2D with empty p
+    verify_lppool(
+        x_shape=[1, 1, 32, 32],
+        kernel_shape=[3, 3],
+        p=None,
+        strides=[1, 1],
+        pads=[1, 1, 1, 1],
+        out_shape=[1, 1, 32, 32],
+    )
 
 
 def verify_rnn(