I think it depends on the tensor/array you are passing to these methods and what its values would mean.
A normalization is often applied, if you provide data in a “non-image” format.
E.g. floating point values in the range [-1, 1] wouldn’t directly represent pixel data (color values) and would thus be mapped to uint8 data in the range [0, 255], which is a standard image format.
The best approach would be for you to create this mapping and pass the array in an expected format, so that neither torchvision nor matplotlib would change any values, as they are most likely trying to use their best guess on what the array might represent.