class torch.nn.quantized.functional.avg_pool3d(input, kernel_size, stride=None, padding=0, ceil_mode=False, count_include_pad=True, divisor_override=None)[source]

Applies 3D average-pooling operation in kD timeskH×kWkD \ times kH \times kW regions by step size sD×sH×sWsD \times sH \times sW steps. The number of output features is equal to the number of input planes.


The input quantization parameters propagate to the output.

  • input – quantized input tensor (minibatch,in_channels,iH,iW)(\text{minibatch} , \text{in\_channels} , iH , iW)

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

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

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

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

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

  • 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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