oneflow.nn.functional.avg_pool3d

oneflow.nn.functional.avg_pool3d(input, kernel_size, stride=None, padding=0, ceil_mode=False, count_include_pad=True, divisor_override=0)Tensor

Applies 3D average-pooling operation in \(kT \times kH \times kW\) regions by step size \(sT \times sH \times sW\) steps. The number of output features is equal to \(\lfloor\frac{\text{input planes}}{sT}\rfloor\).

The documentation is referenced from: https://pytorch.org/docs/1.10/generated/torch.nn.functional.avg_pool3d.html

See AvgPool3d for details and output shape.

Parameters
  • input – input tensor \((\text{minibatch} , \text{in_channels} , iT \times iH , iW)\)

  • kernel_size – size of the pooling region. Can be a single number or a tuple (kT, kH, kW)

  • stride – stride of the pooling operation. Can be a single number or a tuple (sT, sH, sW). Default: kernel_size

  • padding – implicit zero paddings on both sides of the input. Can be a single number or a tuple (padT, padH, padW), Default: 0

  • ceil_mode – when True, will use ceil instead of floor in the formula to compute the output shape

  • count_include_pad – when True, will include the zero-padding in the averaging calculation

  • divisor_override – if specified, it will be used as divisor, otherwise size of the pooling region will be used. Default: 0