Support conv2d transpose operator with groups > 1

[YuhengHuang42]

Currently TVM doesn't support Conv2d transpose with groups > 1. When turning Pytorch model to Relay there will be an error.

Detail discussion could be seen at: https://discuss.tvm.apache.org/t/pytorch-error-when-turning-a-simple-pytorch-model-to-relay/10158

P.S. It may be better if TVM can show some warnings saying that a specific parameter for an op is unsupported, rather than just gives some kind of error?

[Lyken17]

happened to be here. It was surprising the issue was not solved after so long time. TranposedConv2d is an important operator in GAN related applications. For anyone who also had this trouble, you may refer following code to support group parameter in transposed convolution

    out_c = simplify(out_c)
    out_channels = simplify(out_c * groups)

    out_h = simplify(in_h - filter_h + 1)
    out_w = simplify(in_w - filter_w + 1)
    dc = te.reduce_axis((0, in_c // groups), name="dc")
    dh = te.reduce_axis((0, filter_h), name="dh")
    dw = te.reduce_axis((0, filter_w), name="dw")
    
    # data: batch, in_channels, out_h, out_w
    # weight: out_channels // G, in_channels, out_h, out_w
    return te.compute(
        (batch, out_channels, out_h, out_w),
        lambda b, c, h, w: te.sum(
            data_pad[
                b, 
                c // (out_channels // groups) * (in_channels // groups) + dc, 
                h + dh, 
                w + dw
            ].astype(out_dtype)
            * kernel_transform[
                c % (out_channels // groups), 
                c // (out_channels // groups) * (in_channels // groups) + dc, 
                dh, 
                dw
            ].astype(out_dtype),
            axis=[dc, dh, dw],
        ),
        tag="conv2d_transpose_nchw",
    )

[tqchen]

Thanks @Lyken17 , do you mind to send a PR to resolve the case?

[Lyken17]

@tqchen Sure, I can craft a PR.