torch.nn.functional.avg_pool3d

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 $kT \times kH \times kW$ regions by step size $sT \times sH \times sW$ steps. The number of output features is equal to $\lfloor\frac{\text{input planes}}{sT}\rfloor$.

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: None