Normalize — Torchvision 0.22 documentation (original) (raw)

class torchvision.transforms.Normalize(mean, std, inplace=False)[source]¶

Normalize a tensor image with mean and standard deviation. This transform does not support PIL Image. Given mean: (mean[1],...,mean[n]) and std: (std[1],..,std[n]) for nchannels, this transform will normalize each channel of the inputtorch.*Tensor i.e.,output[channel] = (input[channel] - mean[channel]) / std[channel]

Note

This transform acts out of place, i.e., it does not mutate the input tensor.

Parameters:

• mean (sequence) – Sequence of means for each channel.
• std (sequence) – Sequence of standard deviations for each channel.
• inplace (bool, optional) – Bool to make this operation in-place.

Examples using Normalize:

forward(tensor: Tensor) → Tensor[source]¶

Parameters:

tensor (Tensor) – Tensor image to be normalized.

Returns:

Normalized Tensor image.

Return type:

Tensor