def testBijectiveAndFinite32bit(self):
with self.test_session():
bijector = Softplus(event_ndims=0)
x = np.linspace(-20., 20., 100).astype(np.float32)
y = np.logspace(-10, 10, 100).astype(np.float32)
assert_bijective_and_finite(
bijector, x, y, rtol=1e-2, atol=1e-2)
def testBijectiveAndFinite(self):
with self.test_session():
x = np.linspace(-7., 7., 100).astype(np.float32)
eps = 1e-3
y = np.linspace(eps, 1. - eps, 100).astype(np.float32)
bijector_test_util.assert_bijective_and_finite(
sigmoid.Sigmoid(), x, y, atol=0., rtol=1e-4)
def testBijectiveAndFinite(self):
with self.test_session():
bijector = power_transform_lib.PowerTransform(
power=0.2, event_ndims=0, validate_args=True)
x = np.linspace(-4.999, 10, num=10).astype(np.float32)
y = np.logspace(0.001, 10, num=10).astype(np.float32)
bijector_test_util.assert_bijective_and_finite(bijector, x, y, rtol=1e-3)
def testBijectiveAndFinite(self):
with self.test_session():
bijector = PowerTransform(
power=0.2, event_ndims=0, validate_args=True)
x = np.linspace(-4.999, 10, num=10).astype(np.float32)
y = np.logspace(0.001, 10, num=10).astype(np.float32)
assert_bijective_and_finite(bijector, x, y, rtol=1e-3)
def testBijectiveAndFiniteWithNegativeHingeSoftness32Bit(self):
with self.test_session():
bijector = Softplus(event_ndims=0, hinge_softness=-0.7)
x = np.linspace(-20., 20., 100).astype(np.float32)
y = -np.logspace(-10, 10, 100).astype(np.float32)
assert_bijective_and_finite(
bijector, x, y, rtol=1e-2, atol=1e-2)
def testBijectiveAndFinite16bit(self):
with self.test_session():
bijector = Softplus(event_ndims=0)
# softplus(-20) is zero, so we can't use such a large range as in 32bit.
x = np.linspace(-10., 20., 100).astype(np.float16)
# Note that float16 is only in the open set (0, inf) for a smaller
# logspace range. The actual range was (-7, 4), so use something smaller
# for the test.
y = np.logspace(-6, 3, 100).astype(np.float16)
assert_bijective_and_finite(bijector, x, y, rtol=1e-1, atol=1e-3)
def testBijectiveAndFinite32bit(self):
with self.test_session():
bijector = softplus_lib.Softplus(event_ndims=0)
x = np.linspace(-20., 20., 100).astype(np.float32)
y = np.logspace(-10, 10, 100).astype(np.float32)
bijector_test_util.assert_bijective_and_finite(bijector,
x,
y,
rtol=1e-2,
atol=1e-2)
def testBijectiveAndFinite(self):
with self.test_session():
x = np.linspace(-7., 7., 100).astype(np.float32)
eps = 1e-3
y = np.linspace(eps, 1. - eps, 100).astype(np.float32)
bijector_test_util.assert_bijective_and_finite(sigmoid.Sigmoid(),
x,
y,
atol=0.,
rtol=1e-4)
def testBijectiveAndFinite16bit(self):
with self.test_session():
bijector = Softplus(event_ndims=0)
# softplus(-20) is zero, so we can't use such a large range as in 32bit.
x = np.linspace(-10., 20., 100).astype(np.float16)
# Note that float16 is only in the open set (0, inf) for a smaller
# logspace range. The actual range was (-7, 4), so use something smaller
# for the test.
y = np.logspace(-6, 3, 100).astype(np.float16)
assert_bijective_and_finite(
bijector, x, y, rtol=1e-1, atol=1e-3)
def testBijectiveAndFinite(self):
with self.test_session():
softmax = softmax_centered_lib.SoftmaxCentered(event_ndims=1)
x = np.linspace(-50, 50, num=10).reshape(5, 2).astype(np.float32)
# Make y values on the simplex with a wide range.
y_0 = np.ones(5).astype(np.float32)
y_1 = (1e-5 * rng.rand(5)).astype(np.float32)
y_2 = (1e1 * rng.rand(5)).astype(np.float32)
y = np.array([y_0, y_1, y_2])
y /= y.sum(axis=0)
y = y.T # y.shape = [5, 3]
bijector_test_util.assert_bijective_and_finite(softmax, x, y)
def testBijectiveAndFinite(self):
with self.test_session():
softmax = softmax_centered_lib.SoftmaxCentered(event_ndims=1)
x = np.linspace(-50, 50, num=10).reshape(5, 2).astype(np.float32)
# Make y values on the simplex with a wide range.
y_0 = np.ones(5).astype(np.float32)
y_1 = (1e-5 * rng.rand(5)).astype(np.float32)
y_2 = (1e1 * rng.rand(5)).astype(np.float32)
y = np.array([y_0, y_1, y_2])
y /= y.sum(axis=0)
y = y.T # y.shape = [5, 3]
bijector_test_util.assert_bijective_and_finite(softmax, x, y)
def testBijectiveAndFinite(self):
with self.test_session():
bijector = Exp(event_ndims=0)
x = np.linspace(-10, 10, num=10).astype(np.float32)
y = np.logspace(-10, 10, num=10).astype(np.float32)
assert_bijective_and_finite(bijector, x, y)
def testBijectiveAndFinite(self):
with self.test_session():
bijector = exp_lib.Exp(event_ndims=0)
x = np.linspace(-10, 10, num=10).astype(np.float32)
y = np.logspace(-10, 10, num=10).astype(np.float32)
bijector_test_util.assert_bijective_and_finite(bijector, x, y)
def testBijectiveAndFiniteWithNegativeHingeSoftness32Bit(self):
with self.test_session():
bijector = Softplus(event_ndims=0, hinge_softness=-0.7)
x = np.linspace(-20., 20., 100).astype(np.float32)
y = -np.logspace(-10, 10, 100).astype(np.float32)
assert_bijective_and_finite(bijector, x, y, rtol=1e-2, atol=1e-2)
