- class mmcv.cnn.ConvAWS2d(in_channels: int, out_channels: int, kernel_size: Union[int, Tuple[int, int]], stride: Union[int, Tuple[int, int]] = 1, padding: Union[int, Tuple[int, int]] = 0, dilation: Union[int, Tuple[int, int]] = 1, groups: int = 1, bias: bool = True)¶
AWS (Adaptive Weight Standardization)
in_channels (int) – Number of channels in the input image
out_channels (int) – Number of channels produced by the convolution
groups (int, optional) – Number of blocked connections from input channels to output channels. Default: 1
bias (bool, optional) – If set True, adds a learnable bias to the output. Default: True
- forward(x: torch.Tensor) → torch.Tensor¶
Defines the computation performed at every call.
Should be overridden by all subclasses.
Although the recipe for forward pass needs to be defined within this function, one should call the
Moduleinstance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.