StandardScaler expects a numpy array, not a torch.utils.data.Dataset as its input.
The FashionMNIST dataset stores the data as a numpy array in its internal .data attribute.
Since you want to apply scikit-learn preprocessing methods to it, I would recommend to write a custom Dataset by deriving from FashionMNIST and to fit_transform the StandardScaler in the __init__ method and transform the data in the __getitem__.
If you want to use the same scaler for the training and validation (and test) datasets, you could create the object once and pass it to the custom dataset implementations.