Which function will produce the desired output?

Explanations:

Dropout is a regularization technique used to prevent overfitting by randomly setting a fraction of input units to zero during training. It does not affect the output probabilities.

Smooth L1 loss is a loss function used in regression problems to reduce the impact of outliers. It is not used for generating probabilities in classification tasks.

Softmax is the appropriate activation function for multi-class classification. It converts the raw output values (logits) from the fully connected layer into a probability distribution over the classes.

ReLU (Rectified Linear Units) is an activation function used to introduce non-linearity in the hidden layers of a neural network. It is not used to produce probability distributions for classification.