def testScalarCongruency(self):
bijector = tfb.Expm1()
bijector_test_util.assert_scalar_congruency(bijector,
lower_x=-5.,
upper_x=2.5,
eval_func=self.evaluate,
rtol=0.15)
def testMatchesExpm1(self):
bijector = tfb.Expm1()
x = np.random.randn(30)
y = np.expm1(x)
self.assertAllClose(y, self.evaluate(bijector.forward(x)))
# Disable caching.
self.assertAllClose(x, self.evaluate(bijector.inverse(tf.identity(y))))
def disabled_testFailureCase(self):
# TODO(b/140229057): This test should pass.
dist = tfd.Chi(df=np.float32(27.744131))
dist = tfd.TransformedDistribution(
bijector=tfb.NormalCDF(), distribution=dist, batch_shape=[4])
dist = tfb.Expm1()(dist)
samps = 1.7182817 + tf.zeros_like(dist.sample(seed=test_util.test_seed()))
self.assertAllClose(dist.log_prob(samps)[0], dist[0].log_prob(samps[0]))
def disabled_testFailureCase(self): # pylint: disable=invalid-name
# TODO(b/140229057): This test should pass.
dist = tfd.Chi(df=np.float32(27.744131) * np.ones((4,)).astype(np.float32))
dist = tfd.TransformedDistribution(
bijector=tfb.NormalCDF(), distribution=dist)
dist = tfb.Expm1()(dist)
samps = 1.7182817 + tf.zeros_like(dist.sample(seed=test_util.test_seed()))
self.assertAllClose(dist.log_prob(samps)[0], dist[0].log_prob(samps[0]))
def testBijectiveAndFinite(self):
bijector = tfb.Expm1()
x = np.linspace(-5, 5, num=20).astype(np.float32)
y = np.logspace(-5, 5, num=20).astype(np.float32)
bijector_test_util.assert_bijective_and_finite(bijector,
x,
y,
eval_func=self.evaluate,
event_ndims=0)
def testBijector(self):
bijector = tfb.Expm1()
self.assertStartsWith(bijector.name, 'expm1')
x = [[[-1.], [1.4]]]
y = np.expm1(x)
self.assertAllClose(y, self.evaluate(bijector.forward(x)))
self.assertAllClose(x, self.evaluate(bijector.inverse(y)))
self.assertAllClose(
-np.squeeze(np.log1p(y), axis=-1),
self.evaluate(bijector.inverse_log_det_jacobian(y, event_ndims=1)))
self.assertAllClose(
self.evaluate(-bijector.inverse_log_det_jacobian(np.expm1(x),
event_ndims=1)),
self.evaluate(bijector.forward_log_det_jacobian(x, event_ndims=1)))
def testBijectorIsInvertExpm1(self):
x = np.linspace(0., 10., num=200)
log1p = tfb.Log1p()
invert_expm1 = tfb.Invert(tfb.Expm1())
self.assertAllClose(self.evaluate(log1p.forward(x)),
self.evaluate(invert_expm1.forward(x)))
self.assertAllClose(self.evaluate(log1p.inverse(x)),
self.evaluate(invert_expm1.inverse(x)))
self.assertAllClose(
self.evaluate(log1p.forward_log_det_jacobian(x, event_ndims=1)),
self.evaluate(
invert_expm1.forward_log_det_jacobian(x, event_ndims=1)))
self.assertAllClose(
self.evaluate(log1p.inverse_log_det_jacobian(x, event_ndims=1)),
self.evaluate(
invert_expm1.inverse_log_det_jacobian(x, event_ndims=1)))
