torch.nn.functional.avg_pool2d(input, kernel_size, stride=None, padding=0, ceil_mode=False, count_include_pad=True, divisor_override=None) Tensor

Applies 2D average-pooling operation in kH×kWkH \times kW regions by step size sH×sWsH \times sW steps. The number of output features is equal to the number of input planes.

See AvgPool2d for details and output shape.

  • input – 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 (kH, kW)

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

  • padding – implicit zero paddings on both sides of the input. Can be a single number or a tuple (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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