transforms.Normalize

`transforms.Normalize` is a data preprocessing step in PyTorch that normalizes the input data. It takes in a mean and standard deviation value and applies a normalization formula to the input data.

The normalization formula is:

input[channel] = (input[channel] - mean[channel]) / std[channel]

where `channel` represents the color channel (e.g. red, green, blue) of the input data.

The purpose of normalization is to bring the input data to a common scale, making it easier for the model to learn from the data. It reduces the impact of the scale of the input data on the performance of the model.

`transforms.Normalize` is commonly used in computer vision tasks, such as image classification, object detection, and segmentation.