diff --git a/python/tvm/relax/frontend/onnx/onnx_frontend.py b/python/tvm/relax/frontend/onnx/onnx_frontend.py
index a8cb216e26bd..36ef2bdb67b5 100644
--- a/python/tvm/relax/frontend/onnx/onnx_frontend.py
+++ b/python/tvm/relax/frontend/onnx/onnx_frontend.py
@@ -2759,6 +2759,38 @@ def _impl_v11(cls, bb, inputs, attr, params):
             # edge mode - replicate border values
             return bb.emit_te(topi.nn.replicate_pad, inputs[0], pad_before, pad_after)
 
+    @classmethod
+    def _impl_v19(cls, bb, inputs, attr, params):
+        pads = get_constant(inputs[1], params)
+        constant_value = get_constant(inputs[2], params)
+        if constant_value is not None:
+            constant_value = constant_value.data.numpy().item()
+        else:
+            constant_value = 0.0
+
+        if isinstance(pads, relax.Constant):
+            pad_before, pad_after = _np.split(pads.data.numpy(), 2)
+            pad_before = _np.ndarray.tolist(pad_before)
+            pad_after = _np.ndarray.tolist(pad_after)
+        else:
+            raise ValueError("Dynamic pads are not supported yet.")
+
+        pad_mode = attr.get("mode", b"constant").decode("utf-8")
+        if pad_mode not in ["constant", "edge", "reflect", "wrap"]:
+            raise tvm.error.OpAttributeInvalid(
+                "Value " + pad_mode + ' in attribute "mode" is invalid for operator Pad.'
+            )
+
+        if pad_mode == "constant":
+            return bb.emit_te(topi.nn.pad, inputs[0], pad_before, pad_after, constant_value)
+        elif pad_mode == "reflect":
+            return bb.emit_te(topi.nn.mirror_pad, inputs[0], pad_before, pad_after, "REFLECT")
+        elif pad_mode == "wrap":
+            return bb.emit_te(topi.nn.circular_pad, inputs[0], pad_before, pad_after)
+        else:
+            # edge mode - replicate border values
+            return bb.emit_te(topi.nn.replicate_pad, inputs[0], pad_before, pad_after)
+
 
 class Tile(OnnxOpConverter):
     """Converts an onnx Tile node into an equivalent Relax expression."""
diff --git a/tests/python/relax/test_frontend_onnx.py b/tests/python/relax/test_frontend_onnx.py
index 5aff95da5a46..6630e0f16c60 100644
--- a/tests/python/relax/test_frontend_onnx.py
+++ b/tests/python/relax/test_frontend_onnx.py
@@ -3656,14 +3656,14 @@ def test_pad(dynamic):
     if dynamic:
         pytest.skip("Dynamic pad not supported")
 
-    def verify_pad(input_shape, pads, mode="constant", value=0.0):
+    def verify_pad(input_shape, pads, mode="constant", value=0.0, opset=14):
         indata = np.random.normal(size=input_shape).astype(np.float32)
         #  numpy expect result
         len_dim = len(pads) // 2
         np_pads = [(pads[i], pads[i + len_dim]) for i in range(len_dim)]
         pads = np.array(pads)
         #  onnx graph
-        if mode in ["edge", "reflect"]:
+        if mode in ["edge", "reflect", "wrap"]:
             outdata = np.pad(indata, pad_width=np_pads, mode=mode)
             node = helper.make_node("Pad", inputs=["input", "pads"], outputs=["output"], mode=mode)
             graph = helper.make_graph(
@@ -3700,7 +3700,7 @@ def verify_pad(input_shape, pads, mode="constant", value=0.0):
                 ],
             )
         model = helper.make_model(graph, producer_name="pad_test")
-        check_correctness(model)
+        check_correctness(model, opset=opset)
 
     verify_pad((2, 2), [0, 1, 0, 0], "constant", 0.0)
     verify_pad((2, 3), [1, 0, 0, 1], "constant", 0.0)
@@ -3708,6 +3708,7 @@ def verify_pad(input_shape, pads, mode="constant", value=0.0):
     verify_pad((1, 3, 4, 5), [0, 1, 1, 1, 0, 0, 1, 1], "reflect")
     verify_pad((2, 3), [1, 1, 1, 1], "edge")
     verify_pad((1, 3, 4, 5), [0, 1, 1, 1, 0, 0, 1, 1], "edge")
+    verify_pad((1, 3, 4, 5), [0, 1, 1, 1, 0, 0, 1, 1], "wrap", opset=19)
 
 
 @pytest.mark.parametrize("dynamic", [True, False])