diff --git a/python/tvm/relay/frontend/onnx.py b/python/tvm/relay/frontend/onnx.py
index ffeb0dd731713..1e02910c01698 100644
--- a/python/tvm/relay/frontend/onnx.py
+++ b/python/tvm/relay/frontend/onnx.py
@@ -2114,6 +2114,16 @@ def _impl_v9(cls, inputs, attr, params):
         return _op.transpose(output, axes=(1, 0))
 
 
+
+class ReverseSequence(OnnxOpConverter):
+    """Operator converter for ReverseSequence"""
+
+    @classmethod
+    def _impl_v10(cls, inputs, attr, params):
+
+        return _op.reverse_sequence(inputs[0], inputs[1], attr["time_axis"], attr["batch_axis"])
+
+
 class TopK(OnnxOpConverter):
     """Operator converter for TopK"""
 
@@ -2801,6 +2811,7 @@ def _get_convert_map(opset):
         "QuantizeLinear": QuantizeLinear.get_converter(opset),
         "DequantizeLinear": DequantizeLinear.get_converter(opset),
         "DynamicQuantizeLinear": DynamicQuantizeLinear.get_converter(opset),
+        "ReverseSequence": ReverseSequence.get_converter(opset),
     }
 
 
diff --git a/tests/python/frontend/onnx/test_forward.py b/tests/python/frontend/onnx/test_forward.py
index 6d22b5afd0df4..5ddd353c6d550 100644
--- a/tests/python/frontend/onnx/test_forward.py
+++ b/tests/python/frontend/onnx/test_forward.py
@@ -4328,6 +4328,51 @@ def verify_embedding_bag(num_embedding, embedding_dim, data_shape, num_bags=None
     verify_embedding_bag(32, 2, [3, 3])
 
 
+def verify_reverse_sequence(x, sequence_lens, batch_axis, time_axis):
+    node = onnx.helper.make_node(
+        "ReverseSequence",
+        inputs=["x", "sequence_lens"],
+        outputs=["y"],
+        time_axis=time_axis,
+        batch_axis=batch_axis,
+    )
+
+    graph = helper.make_graph(
+        [node],
+        "reverse_sequence_test",
+        inputs=[
+            helper.make_tensor_value_info("x", TensorProto.FLOAT, list(x.shape)),
+            helper.make_tensor_value_info(
+                "sequence_lens", TensorProto.INT64, list(sequence_lens.shape)
+            ),
+        ],
+        outputs=[helper.make_tensor_value_info("y", TensorProto.FLOAT, list(x.shape))],
+    )
+
+    model = helper.make_model(graph, producer_name="reverse_sequence_test")
+    verify_with_ort_with_inputs(model, [x, sequence_lens], list(x.shape))
+
+
+@tvm.testing.uses_gpu
+def test_reverse_sequence():
+    x = np.array(
+        [[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11], [12, 13, 14, 15]],
+        dtype=np.float32,
+    )
+    sequence_lens = np.array([1, 2, 3, 4], dtype=np.int64)
+    y = np.array(
+        [[0, 5, 10, 15], [4, 1, 6, 11], [8, 9, 2, 7], [12, 13, 14, 3]],
+        dtype=np.float32,
+    )
+    verify_reverse_sequence(x, sequence_lens, 0, 1)
+
+    y = np.array(
+        [[0, 1, 2, 3], [5, 4, 6, 7], [10, 9, 8, 11], [15, 14, 13, 12]],
+        dtype=np.float32,
+    )
+    verify_reverse_sequence(x, sequence_lens, 1, 0)
+
+
 if __name__ == "__main__":
     test_flatten()
     test_reshape()
@@ -4407,4 +4452,8 @@ def verify_embedding_bag(num_embedding, embedding_dim, data_shape, num_bags=None
     test_softplus()
     test_cumsum()
     test_wrong_input()
+<<<<<<< HEAD
     test_aten()
+=======
+    test_reverse_sequence()
+>>>>>>> 726b946b9... add onnx reverse sequence op