Class AvgPool2d

imperative/python/megengine/module/pooling.py:85–151

r"""Applies a 2D average pooling over an input. For instance, given an input of the size :math:`(N, C, H_{\text{in}}, W_{\text{in}})` and :attr:`kernel_size` :math:`(kH, kW)`, this layer generates the output of the size :math:`(N, C, H_{\text{out}}, W_{\text{out}})` through a process de

class AvgPool2d(_PoolNd):
    r"""Applies a 2D average pooling over an input.

    For instance, given an input of the size :math:`(N, C, H_{\text{in}}, W_{\text{in}})` and
    :attr:`kernel_size` :math:`(kH, kW)`, this layer generates the output of
    the size :math:`(N, C, H_{\text{out}}, W_{\text{out}})` through a process described as:

    .. math::

        out(N_i, C_j, h, w)  = \frac{1}{kH * kW} \sum_{m=0}^{kH-1} \sum_{n=0}^{kW-1}
                               input(N_i, C_j, stride[0] \times h + m, stride[1] \times w + n)

    If :attr:`padding` is non-zero, then the input is implicitly zero-padded on
    both sides for :attr:`padding` number of points.

    Args:
        kernel_size(Union[int, Tuple[int, int]]): the size of the window.
        stride(Union[int, Tuple[int, int]]): the stride of the window. Default value is ``kernel_size``.
        padding(Union[int, Tuple[int, int]]): implicit zero padding to be added on both sides.Default: 0.
        mode(str): whether to include the padding values while calculating the average, set
            to "average" will do counting.
            Default: "average_count_exclude_padding"
    
    Shape:
        - Input: :math:`(N, C, H_{in}, W_{in})` or :math:`(C, H_{in}, W_{in})`.
        - Output: :math:`(N, C, H_{out}, W_{out})` or :math:`(C, H_{out}, W_{out})`, where

          .. math::
              H_{out} = \left\lfloor\frac{H_{in}  + 2 \times \text{padding}[0] -
                \text{kernel\_size}[0]}{\text{stride}[0]} + 1\right\rfloor

          .. math::
              W_{out} = \left\lfloor\frac{W_{in}  + 2 \times \text{padding}[1] -
                \text{kernel\_size}[1]}{\text{stride}[1]} + 1\right\rfloor

    Returns:
        Return type: module. The instance of the ``AvgPool2d`` module.

    Examples:
        >>> import numpy as np
        >>> m = M.AvgPool2d(kernel_size=2, stride=2, padding=[1,0], mode="average")
        >>> inp = mge.tensor(np.arange(1 * 1 * 3 * 4).astype(np.float32).reshape(1, 1, 3, 4))
        >>> output = m(inp)
        >>> output
        Tensor([[[[0.25 1.25]
                  [6.5  8.5 ]]]], device=xpux:0)

    """

    def __init__(
        self,
        kernel_size: Union[int, Tuple[int, int]],
        stride: Union[int, Tuple[int, int]] = None,
        padding: Union[int, Tuple[int, int]] = 0,
        mode: str = "average_count_exclude_padding",
        **kwargs
    ):
        super(AvgPool2d, self).__init__(kernel_size, stride, padding, **kwargs)