How to prepare the training data set for primitives with boolean type? (Question)

[dongchen-coder]

Just following incur.py, I am trying to add a primitive '<' which takes two ints and returns a boolean.

def _le(x, y): return lambda x, y: x < y

primitives = [
        ...
        Primitive("loc_le", arrow(tint, tint, tboolean), _le),
]

def leGen():
        x = random.choice(range(500))
        y = random.choice(range(500))
        return {"i": (x, y), "o": x < y}

training_examples = [
        ...
        {"name": "le_train",  "examples": [leGen()  for _ in range(50000)]},
]
training = [get_tint_task(item) for item in training_examples]

It seems that all my tint -> tint -> tint tasks are passed but for tasks with tboolean are failed.

HIT add_train w/ (lambda (lambda (add $0 $1))) ; log prior = -6.761573 ; log likelihood = 0.000000
HIT sub_train w/ (lambda (lambda (sub $1 $0))) ; log prior = -6.761573 ; log likelihood = 0.000000
HIT mul_train w/ (lambda (lambda (mul $0 $1))) ; log prior = -6.761573 ; log likelihood = 0.000000
HIT div_train w/ (lambda (lambda (div $1 $0))) ; log prior = -6.761573 ; log likelihood = 0.000000
MISS le_train
Hits 4/5 tasks

My guess is the training data, which contains python booleans True/False, are not recognized by Ocaml.

What is the right way to specify boolean data for training in python script with ocaml backend.

Thanks!

[dongchen-coder]

Using python False and True will be good. I located the bug that I introduced in get_tiny_task.