class torch.nn.AdaptiveAvgPool2d(output_size)[source]

Applies a 2D adaptive average pooling over an input signal composed of several input planes.

The output is of size H x W, for any input size. The number of output features is equal to the number of input planes.

Parameters

output_size – the target output size of the image of the form H x W. Can be a tuple (H, W) or a single H for a square image H x H. H and W can be either a int, or None which means the size will be the same as that of the input.

Shape:
• Input: $(N, C, H_{in}, W_{in})$ or $(C, H_{in}, W_{in})$.

• Output: $(N, C, S_{0}, S_{1})$ or $(C, S_{0}, S_{1})$, where $S=\text{output\_size}$.

Examples

>>> # target output size of 5x7