Pytorch Notes

torch.nn.functioanl.adaptive_avg_pool2d(input, output_size)
Applies a 2D adaptive average pooling over an input signal composed of several input planes.

 torch.nn.functional.adaptive_avg_pool3d(input, output_size)
Applies a 3D adaptive average pooling over an input signal composed of several input planes

 Class: torch.nn.Parameter

 A kind of Tensor that is to be considered a module parameter.
parameters: data(Tensor)
torch.nn.functional.interpolate(input, size, scale_factor, mode= 'nearest', align_corners)

 Down/up samples the input to either the given size or the given scale_factor. The algorithm used for interpolation is determined by mode.

 torch.cat(tensors, dim = 0, out = None)
concatenates the given of seq tensors in the given dimension. All tensors must be either have the same shape or be empty.

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