[Feature Request] Support ONNX export of Deconvolution operator

[Lebron8997]

Currently, MXNet->ONNX model export does not support the MXNet operator:

• Deconvolution

The following code (adapted from https://github.com/NVIDIA/mxnet_to_onnx/blob/master/mx2onnx_converter/mx2onnx_converter_functions.py) may be inserted in [mxnet-ROOT]/python/mxnet/contrib/onnx/mx2onnx/_op_translations.py

@mx_op.register("Deconvolution")
def convert_deconvolution(node, **kwargs):
"""Map MXNet's deconvolution operator attributes to onnx's ConvTranspose operator
and return the created node.
"""
onnx = import_onnx_modules()
name = node["name"]
inputs = node["inputs"]

num_inputs = len(inputs)

proc_nodes = kwargs["proc_nodes"]
input_node = proc_nodes[kwargs["index_lookup"][inputs[0][0]]].name
weights_node = proc_nodes[kwargs["index_lookup"][inputs[1][0]]].name

if num_inputs > 2:
    bias_node = proc_nodes[kwargs["index_lookup"][inputs[2][0]]].name

attrs = node.get("attrs")

kernel_dims = list(parse_helper(attrs, "kernel"))
stride_dims = list(parse_helper(attrs, "stride", [1, 1]))
pad_dims = list(parse_helper(attrs, "pad", [0, 0]))
num_group = int(attrs.get("num_group", 1))
# dilations = list(parse_helper(attrs, "dilate", [1, 1]))

pad_dims = pad_dims + pad_dims

input_nodes = [input_node, weights_node]
if num_inputs > 2:
    input_nodes.append(bias_node)

deconv_node = onnx.helper.make_node(
    "ConvTranspose",
    inputs=input_nodes,
    outputs=[name],
    kernel_shape=kernel_dims,
    strides=stride_dims,
    pads=pad_dims,
    group=num_group,
    name=name
)

return [deconv_node]

[lanking520]

@Lebron8997 Thanks for your issue reporting. @Roshrini here to help you out.

[Roshrini]

@Lebron8997 This feature is already in PR #12399

[Roshrini]

@lanking520 Duplicate issue: #12807
Feel free to close one.