Add a ltn.Predicate constructor that takes in a logits model

[sbadredd]

Constructors for ltn.Predicate

The constructor for ltn.Predicate accepts a model that outputs one truth degree in [0,1].

class ModelThatOutputsATruthDegree(tf.keras.Model):
    def __init__(self):
        super().__init__()
        self.dense1 = tf.keras.layers.Dense(5, activation=tf.nn.relu)
        self.dense2 = tf.keras.layers.Dense(1, activation=tf.nn.sigmoid) # returns one value in [0,1]

    def call(self, x):
        x = self.dense1(x)
        return self.dense2(x)

model = ModelThatOutputsATruthDegree()
P1 = ltn.Predicate(model)
P1(x) # -> call with a ltn Variable

Issue

Many models output several values simultaneously. For example, a model for the predicate P2 classifying images x into n classes type_1, ..., type_n will likely output n logits using the same hidden layers.

Eventually, we would expect to call the corresponding predicate using the syntax P2(x,type). This requires two additional steps:

1. Transforming the logits into values in [0,1],
2. Indexing the class using the term type.

Because this is a common use-case, we implemented a function ltn.utils.LogitsToPredicateModel for convenience. It is used in some of the examples (cf MNIST digit addition).
The syntax is:

logits_model(x) # how to call `logits_model`
P2 = ltn.Predicate(ltn.utils.LogitsToPredicateModel(logits_model), single_label=True)
P2([x,type]) # how to call the predicate

It automatically adds a final argument for class indexing and performs a sigmoid or softmax activation depending on the parameter single_label.

Proposition

It would be more elegant to have the functionality of creating a predicate from a logits model as a class constructor for ltn.Predicate.

A suggested syntax is:

P2 = ltn.Predicate.FromLogits(logits_model, activation_function="softmax", with_class_indexing=True)

• The functionality comes as a new class constructor,
• The activation function is more explicit than the single_label parameter in ltn.utils.LogitsToPredicateModel,
• with_class_indexing=False still allows creating predicates in the form of P1(x), like abovementioned.

Changes to the rest of the API

The proposition adds a new constructor but shouldn't change any other method of ltn.Predicate or any framework method in general.