| @@ -638,16 +638,23 @@ def avg_pool2d( | |||||
| Refer to :class:`~.AvgPool2d` for more information. | Refer to :class:`~.AvgPool2d` for more information. | ||||
| Args: | Args: | ||||
| inp: input tensor. | |||||
| kernel_size: size of the window. | |||||
| inp: input tensor of shape :math:`(N, C, H_{in}, W_{in})`. | |||||
| kernel_size: size of the window used to calculate the average value. | |||||
| stride: stride of the window. If not provided, its value is set to ``kernel_size``. | stride: stride of the window. If not provided, its value is set to ``kernel_size``. | ||||
| Default: None | |||||
| padding: implicit zero padding added on both sides. Default: 0 | |||||
| mode: whether to count padding values, set to "average" will do counting. | |||||
| Default: ``None`` | |||||
| padding: implicit zero padding added on both sides. Default: :math:`0` | |||||
| mode: whether to include the padding values while calculating the average, set | |||||
| to "average" will do counting. | |||||
| Default: "average_count_exclude_padding" | Default: "average_count_exclude_padding" | ||||
| Returns: | Returns: | ||||
| output tensor. | |||||
| output tensor of shape `(N, C, H_{out}, W_{out})`. | |||||
| Examples: | |||||
| >>> input = tensor(np.arange(1 * 1 * 3 * 4).astype(np.float32).reshape(1, 1, 3, 4)) | |||||
| >>> F.avg_pool2d(input, kernel_size=2, stride=2, padding=[1,0], mode="average") | |||||
| Tensor([[[[0.25 1.25] | |||||
| [6.5 8.5 ]]]], device=xpux:0) | |||||
| """ | """ | ||||
| if stride is None: | if stride is None: | ||||
| stride = kernel_size | stride = kernel_size | ||||