def test_soft_round_values_and_gradients_are_finite(self, alpha):
x = tf.linspace(0., 1., 11) # covers exact integers and half-integers
with tf.GradientTape() as tape:
tape.watch(x)
y = round_ops.soft_round(x, alpha=alpha)
dy = tape.gradient(y, x)
self.assertAllEqual(tf.math.is_finite(y), tf.ones(x.shape, dtype=bool))
self.assertAllEqual(tf.math.is_finite(dy), tf.ones(x.shape,
dtype=bool))
def test_soft_round_layer_soft_rounds(self):
alpha = 5.0
layer = soft_round.SoftRound(alpha=alpha)
x = tf.linspace(-5.0, 5.0, num=50)
y = layer(x)
self.assertAllClose(y, round_ops.soft_round(x, alpha=alpha))
def transform(self, x):
return round_ops.soft_round(x, self._alpha)
def test_soft_inverse_is_actual_inverse(self):
x = tf.constant([-1.25, -0.75, 0.75, 1.25], dtype=tf.float32)
y = round_ops.soft_round(x, alpha=2.0)
x2 = round_ops.soft_round_inverse(y, alpha=2.0)
self.assertAllClose(x, x2)
def test_soft_round_large_alpha_is_round(self):
# We don't care what happens exactly near half-integer values:
for offset in range(-5, 5):
x = tf.linspace(offset - 0.499, offset + 0.499, 100)
y = round_ops.soft_round(x, alpha=2000.0)
self.assertAllClose(tf.round(x), y, atol=0.02)
def test_soft_round_small_alpha_is_identity(self):
x = tf.linspace(-2., 2., 50)
y = round_ops.soft_round(x, alpha=1e-13)
self.assertAllClose(x, y)