[v1.x] ONNX export rewrite tile

python/mxnet/contrib/onnx/mx2onnx/_op_translations.py

@@ -2262,37 +2262,32 @@ def convert_tile(node, **kwargs):
     """Map MXNet's Tile operator attributes to onnx's Tile
     operator and return the created node.
     """
+    from onnx.helper import make_node
     name, input_nodes, attrs = get_inputs(node, kwargs)
 
-    reps_list = convert_string_to_list(attrs["reps"])
-
-    initializer = kwargs["initializer"]
-    reps_shape_np = np.array(reps_list, dtype='int64')
-    data_type = onnx.mapping.NP_TYPE_TO_TENSOR_TYPE[reps_shape_np.dtype]
-    dims = np.shape(reps_shape_np)
-
-    output_shape_name = "reps_attr_tensor" + str(kwargs["idx"])
-    tensor_node = onnx.helper.make_tensor_value_info(output_shape_name, data_type, dims)
+    data = input_nodes[0]
+    reps = convert_string_to_list(attrs["reps"])
 
-    initializer.append(
-        onnx.helper.make_tensor(
-            name=output_shape_name,
-            data_type=data_type,
-            dims=dims,
-            vals=reps_list,
-            raw=False,
-        )
-    )
+    create_tensor([0], name+'_0', kwargs['initializer'])
+    create_tensor([1], name+'_1', kwargs['initializer'])
+    create_tensor(reps, name+'_reps', kwargs['initializer'], dtype='int64')
+    create_tensor([len(reps)], name+'_reps_len', kwargs['initializer'])
 
-    input_nodes.append(output_shape_name)
-    tile_node = onnx.helper.make_node(
-        "Tile",
-        input_nodes,
-        [name],
-        name=name
-    )
+    nodes = [
+        make_node('Shape', [data], [name+'_data_shape']),
+        make_node('Shape', [name+'_data_shape'], [name+'_data_dim']),
+        make_node('Max', [name+'_data_dim', name+'_reps_len'], [name+'_max']),
+        make_node('Sub', [name+'_max', name+'_data_dim'], [name+'_data_diff']),
+        make_node('Concat', [name+'_data_diff', name+'_0'], [name+'_concat0_out'], axis=0),
+        make_node('Pad', [name+'_data_shape', name+'_concat0_out', name+'_1'], [name+'_data_shape_pad']),
+        make_node('Reshape', [data, name+'_data_shape_pad'], [name+'_data']),
+        make_node('Sub', [name+'_max', name+'_reps_len'], [name+'_reps_diff']),
+        make_node('Concat', [name+'_reps_diff', name+'_0'], [name+'_concat1_out'], axis=0),
+        make_node('Pad', [name+'_reps', name+'_concat1_out', name+'_1'], [name+'_reps_pad']),
+        make_node('Tile', [name+'_data', name+'_reps_pad'], [name], name=name),
+    ]
 
-    return [tensor_node, tile_node]
+    return nodes
 
 
 @mx_op.register("broadcast_to")

tests/python-pytest/onnx/test_operators.py

@@ -1121,3 +1121,11 @@ def test_onnx_export_argsort(tmp_path, dtype, axis, is_ascend, dtype_i):
         kwargs['is_ascend'] = is_ascend
     M = def_model('argsort', axis=axis, dtype=dtype_i, **kwargs)
     op_export_test('argsort', M, [A], tmp_path)
+
+
+@pytest.mark.parametrize('dtype', ['int32', 'int64', 'float16', 'float32', 'float64'])
+@pytest.mark.parametrize('reps', [(2, 3), (2, ), (2, 3, 4)])
+def test_onnx_export_tile(tmp_path, dtype, reps):
+    x = mx.nd.random.normal(0, 100, (5, 6)).astype(dtype)
+    M = def_model('tile', reps=reps)
+    op_export_test('tile', M, [x], tmp_path)