Custom loss function in Keras based on the input data

Question

I am trying to create the custom loss function using Keras. I want to compute the loss function based on the input and predicted the output of the neural network.

I

Answer 1

You could wrap your custom loss with another function that takes the input tensor as an argument:

def customloss(x):
    def loss(y_true, y_pred):
        # Use x here as you wish
        err = K.mean(K.square(y_pred - y_true), axis=-1)
        return err

    return loss

And then compile your model as follows:

model.compile('sgd', customloss(x))

where x is your input tensor.

NOTE: Not tested.