Lyken17 commented on issue #8182:
URL: https://github.com/apache/tvm/issues/8182#issuecomment-877677173
happened to be here. It was surprising the issue was not solved after so
long time. For anyone who also had this trouble, you may refer following code
to support `group` parameter in transposed convolution
```python
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",
)
```
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