megengine.functional.nn.max_pool2d¶

max_pool2d(inp, kernel_size, stride=None, padding=0)[源代码]¶

对输入张量进行二维最大池化。

更多信息参见 MaxPool2d。

参数

inp (Tensor) – input tensor of shape \((N, C, H_{\text{in}}, W_{\text{in}})\).
kernel_size (Union[int, Tuple[int, int]]) – size of the window used to calculate the max value.
stride (Union[int, Tuple[int, int], None]) – stride of the window. Default value is kernel_size.
padding (Union[int, Tuple[int, int]]) – implicit zero padding added on both sides. Default: 0.

返回类型

Tensor

返回

output tensor of shape (N, C, H_{text{out}}, W_{text{out}}).

实际案例

>>> import numpy as np
>>> input = Tensor(np.arange(1 * 1 * 3 * 4).astype(np.float32).reshape(1, 1, 3, 4))
>>> F.nn.max_pool2d(input, 2, 1, 0)
Tensor([[[[ 5.  6.  7.]
   [ 9. 10. 11.]]]], device=xpux:0)

megengine.functional.nn.avg_pool2d

megengine.functional.nn.adaptive_avg_pool2d