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

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

See AvgPool3d for details and output shape.

  • input – input tensor (minibatch,in_channels,iT×iH,iW)(\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: None


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