Understanding Loss Functions In PyTorch For Deep Learning Models

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*Memos:

My post explains layers in PyTorch.
My post explains activation functions in PyTorch.
My post explains optimizers in PyTorch.

A loss function is the function which can get the mean(average) of the sum of the losses(differences) between model's predictions and train or test data to optimize a model during training or to evaluate how good a model is during testing. *Loss function is also called Cost Function or Error Function.
There are popular loss functions as shown below:
(1) L1 Loss:

can compute the mean(average) of the sum of the absolute losses(differences) bet...