AvgPool3d¶

class dragon.vm.torch.nn.AvgPool3d(
  kernel_size,
  stride=1,
  padding=0,
  ceil_mode=False
)[source]¶

Apply the 3d average pooling.

This module excepts the input size \((N, C, D, H, W)\), and output size is \((N, C, D_{\text{out}}, H_{\text{out}}, W_{\text{out}})\), where \(N\) is the batch size, \(C\) is the number of channels, \(D\), \(H\) and \(W\) are the depth, height and width of data.

Examples:

m = torch.nn.AvgPool3d(2, 2)
x = torch.ones(2, 2, 2, 2, 2)
y = m(x)

See also

torch.nn.functional.avg_pool3d(…)