Pooling
Pooling methods compatible with fastai & fastxtend’s XResNet
BlurPool
BlurPool (stride:int=2, ks:int=3, padding:int=0, ndim:int=2, ceil_mode:bool=False)
Compute blur (anti-aliasing) and downsample a given feature map.
| Type | Default | Details | |
|---|---|---|---|
| stride | int | 2 | The stride size for pooling |
| ks | int | 3 | The kernel size for pooling |
| padding | int | 0 | Unused, for fastai compatibility |
| ndim | int | 2 | Unused, for fastai compatibility |
| ceil_mode | bool | False | Unused, for fastai compatibility |
| Returns | BlurPool2D |
Stride and ks are reversed to match Average Pooling inputs in XResNet, where AveragePool2D(ks=2, stride=None) results in same output shape as BlurPool2D(ks=3, stride=2).
MaxBlurPool
MaxBlurPool (stride:int=2, ks:int=3, padding:int=0, ndim:int=2, ceil_mode:int=True, max_ks:int=2)
Compute pools and blurs and downsample a given feature map. Equivalent to nn.Sequential(nn.MaxPool2d(...), BlurPool2D(...))
| Type | Default | Details | |
|---|---|---|---|
| stride | int | 2 | The stride size for blur pooling |
| ks | int | 3 | The kernel size for blur pooling |
| padding | int | 0 | Unused, for fastai compatibility |
| ndim | int | 2 | Unused, for fastai compatibility |
| ceil_mode | int | True | If True, output size matches conv2d with same kernel size |
| max_ks | int | 2 | The kernel size for max pooling |
| Returns | MaxBlurPool2D |
Stride and ks are reversed to match Average Pooling inputs in XResNet, where AveragePool2D(ks=2, stride=None) results in same output shape as MaxBlurPool2D(ks=3, stride=2).