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 regions by step size steps. The number of output features is equal to the number of input planes.
AvgPool2dfor details and output shape.
input – input tensor
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:
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:
count_include_pad – when True, will include the zero-padding in the averaging calculation. Default:
divisor_override – if specified, it will be used as divisor, otherwise size of the pooling region will be used. Default: None