tf.losses.CategoricalCrossentropy()

The `tf.losses.CategoricalCrossentropy()` function is a TensorFlow implementation of the categorical cross-entropy loss function, which is commonly used in multi-class classification problems. It calculates the cross-entropy loss between the predicted class probabilities and the true class labels.

The function takes two inputs:

- `y_true`: The true class labels, represented as a one-hot encoded tensor.
- `y_pred`: The predicted class probabilities, represented as a tensor.

The output is the cross-entropy loss as a scalar tensor.

This loss function is commonly used in deep learning models for classification problems with more than two classes. It penalizes the model more when it predicts the wrong class with high confidence, and less when it predicts the wrong class with low confidence.