torch.nn.functional.avg_pool2d¶
-
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 regions by step size steps. The number of output features is equal to the number of input planes.
See
AvgPool2d
for details and output shape.- Parameters
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:
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