locnd182644 opened a new pull request, #18641:
URL: https://github.com/apache/tvm/pull/18641
### Summary
Fixed incorrect output shape of Pool op when ceil_mode = true
### Steps to Reproduce
Example: Create Pool Operator from PyTorch
```
class PoolModule(nn.Module):
def forward(self, x):
return torch.nn.AvgPool2d(2, 2, 1, True)(x)
```
```
class Module:
def main(x: R.Tensor((1, 3, 17, 17), dtype="float32")) ->
R.Tuple(R.Tensor((1, 3, 10, 10), dtype="float32")):
with R.dataflow():
lv: R.Tensor((1, 3, 10, 10), dtype="float32") =
R.nn.avg_pool2d(x, pool_size=[2, 2], strides=[2, 2], dilation=[1, 1],
padding=[1, 1, 1, 1], ceil_mode=True, count_include_pad=True, layout="NCHW",
out_layout="NCHW")
gv: R.Tuple(R.Tensor((1, 3, 10, 10), dtype="float32")) = (lv,)
R.output(gv)
return gv
```
### Expected
```
class Module:
def main(x: R.Tensor((1, 3, 17, 17), dtype="float32")) ->
R.Tuple(R.Tensor((1, 3, 9, 9), dtype="float32")):
with R.dataflow():
lv: R.Tensor((1, 3, 9, 9), dtype="float32") = R.nn.avg_pool2d(x,
pool_size=[2, 2], strides=[2, 2], dilation=[1, 1], padding=[1, 1, 1, 1],
ceil_mode=True, count_include_pad=True, layout="NCHW", out_layout="NCHW")
gv: R.Tuple(R.Tensor((1, 3, 9, 9), dtype="float32")) = (lv,)
R.output(gv)
return gv
```
### Resolve
- Citation:
https://docs.pytorch.org/docs/stable/generated/torch.nn.AvgPool2d.html
<img width="500" height="200" alt="PR1"
src="https://github.com/user-attachments/assets/52a27448-006f-409e-b8b4-65f49e908d5f";
/>
- Fixed: #18594
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