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()