python-kerasHow do I create a custom loss function in Python with Keras?

Creating a custom loss function in Python with Keras is fairly straightforward.

Below is an example of a custom loss function written in Python with Keras:

def custom_loss(y_true, y_pred):
    return K.mean(K.square(y_true - y_pred))

This custom loss function calculates the mean of the squared difference between the true values and the predicted values.

Code explanation

• def custom_loss(y_true, y_pred): This defines the custom loss function as custom_loss and takes two arguments, y_true and y_pred, which represent the true and predicted values respectively.

• return K.mean(K.square(y_true - y_pred)) This is the body of the custom loss function and returns the mean of the squared difference between the true and predicted values.

Helpful links

• Keras Documentation: Writing your own training & evaluation loops from scratch
• Keras Documentation: Writing your own losses

Edit this code on GitHub