DeformableConv2d¶

class DeformableConv2d(in_channels, out_channels, kernel_size, stride=1, padding=0, dilation=1, groups=1, bias=True, conv_mode='cross_correlation', compute_mode='default', **kwargs)[source]¶

Deformable Convolution.

Parameters

in_channels (int) – number of input channels.
out_channels (int) – number of output channels.
kernel_size (Union[int, Tuple[int, int]]) – size of weight on spatial dimensions. If kernel_size is an int, the actual kernel size would be (kernel_size, kernel_size).
stride (Union[int, Tuple[int, int]]) – stride of the 2D convolution operation. Default: 1
padding (Union[int, Tuple[int, int]]) – size of the paddings added to the input on both sides of its spatial dimensions. Only zero-padding is supported. Default: 0
dilation (Union[int, Tuple[int, int]]) – dilation of the 2D convolution operation. Default: 1
groups (int) – number of groups into which the input and output channels are divided, so as to perform a grouped convolution. When groups is not 1, in_channels and out_channels must be divisible by groups, and the shape of weight should be (groups, out_channel // groups, in_channels // groups, height, width). Default: 1
bias (bool) – whether to add a bias onto the result of convolution. Default: True
conv_mode (str) – Supports cross_correlation. Default: cross_correlation
compute_mode (str) – When set to “default”, no special requirements will be placed on the precision of intermediate results. When set to “float32”, “float32” would be used for accumulator and intermediate result, but only effective when input and output are of float16 dtype.

Note

weight usually has shape (out_channels, in_channels, height, width) , if groups is not 1, shape will be (groups, out_channels // groups, in_channels // groups, height, width)
bias usually has shape (1, out_channels, *1)

LocalConv2d

SlidingWindow