def test_dropout_transfer_probability_zero():
length = random.randint(1, 20)
# Can't actually be zero, but can be close enough
dropout_transfer = mlp.DropoutTransfer(mlp.LinearTransfer(), 1e-16, length)
# Should not allow zero active, defaults to 1
assert list(dropout_transfer._active_neurons).count(1.0) == 1
assert list(dropout_transfer._active_neurons).count(0.0) == length - 1
def test_dropout_transfer_probability_one():
length = random.randint(1, 20)
dropout_transfer = mlp.DropoutTransfer(mlp.LinearTransfer(), 1.0, length)
assert (dropout_transfer._active_neurons == numpy.array(
[1.0] * length)).all(), 'All should be active'
# Random input
input_vec = numpy.random.random(length)
assert (dropout_transfer(input_vec) == input_vec).all()