remove useless codes

Author: zhijxu-MS

tf2onnx/tfonnx.py

@@ -1060,7 +1060,6 @@ def upsample_op9(ctx, node, name, args):
     # first create "scales" info for onnx upsample
     # if shape of input and output known then  "scale" is calculated statically and set as a const node
     shape = ctx.get_shape(node.input[0])
-    added_nodes = []
     if shape and shape[2] != -1 and shape[1] != -1 and node.inputs[1].is_const():
         target_shape = node.inputs[1].get_tensor_value()
         n, h, w, c = shape
@@ -1069,7 +1068,6 @@ def upsample_op9(ctx, node, name, args):
         # the reason not storing data at raw field is because of the bug: https://github.com/onnx/onnx/issues/1852
         scale_val = np.array([1.0, 1.0, float(nh) / h, float(nw) / w]).astype(np.float32)
         scales = ctx.make_const(utils.make_name("scales"), scale_val, raw=False)
-        added_nodes.append(scales)
     else:
         ori_shape = ctx.make_node("Shape", [node.input[0]])
         ori_shape_hw = ctx.make_node("Slice", ori_shape.output, {"axes": [0], "starts": [1], "ends": [3]})
@@ -1083,9 +1081,6 @@ def upsample_op9(ctx, node, name, args):
         const_one_array = ctx.make_const(utils.make_name("one"), np.array([1.0, 1.0]).astype(np.float32))
         # scales is nchw
         scales = ctx.make_node("Concat", [const_one_array.output[0], scales_hw.output[0]], {"axis": 0})
-        added_nodes.extend([ori_shape, ori_shape_hw, ori_shape_hw_float, target_hw_float,
-                            scales_hw, const_one_array, scales])
-
     # because onnxruntime only supports to scale the last two dims so transpose is inserted
     input_nchw = ctx.make_node("Transpose", [node.input[0]], {"perm": [0, 3, 1, 2]})
     upsample = ctx.make_node("Upsample", [input_nchw.output[0], scales.output[0]], attr={"mode": args[0]})