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tf.identity(self.loc)
_variance(self)
tf.zeros_like(self.loc)
_mode(self)
self.mean()
_sample_n(self, n, seed=None)
tf.convert_to_tensor(self.loc)
tf.concat([[n], self._batch_shape_tensor(loc=loc)
self._event_shape_tensor(loc=loc)
_default_event_space_bijector(self)
_parameter_control_dependencies(self, is_init)
tensorshape_util.rank(self.loc.shape)
tensorshape_util.rank(self.loc.shape)
ValueError(msg)
assert_util.assert_rank_at_least(self.loc, 1, message=msg)
tensor_util.is_ref(self.atol)
tensor_util.is_ref(self.rtol)
Deterministic(_BaseDeterministic)
function (pmf)
function (cdf)
pmf(x; loc)
cdf(x; loc)
tfp.distributions.Deterministic(0.)
constant.prob(0.)
constant.prob(2.)
tfp.distributions.Deterministic(loc)
constant.prob(x)
pmf(x; loc)
Abs(x - loc)
Abs(loc)
point (or batch of points)
statistics (e.g., mean, mode, variance)
dict(locals()
super(Deterministic, self)
_params_event_ndims(cls)
dict(loc=0, atol=0, rtol=0)
_batch_shape_tensor(self, loc=None)
tf.shape(self.loc if loc is None else loc)
tf.broadcast_dynamic_shape(tf.shape(self.atol)
tf.shape(self.rtol)
_batch_shape(self)
tf.broadcast_static_shape(self.atol.shape, self.rtol.shape)
_event_shape_tensor(self, loc=None)
tf.constant([], dtype=tf.int32)
_event_shape(self)
tf.TensorShape([])
_prob(self, x)
tf.convert_to_tensor(self.loc)
tf.cast(tf.abs(x - loc)
self._slack(loc)
_cdf(self, x)
tf.identity(self.loc)
tf.cast(x >= loc - self._slack(loc)
VectorDeterministic(_BaseDeterministic)
function (pmf)
pmf(x; loc)
Abs(x - loc)
Abs(loc)
tfd.Deterministic([0., 2.])
constant.prob([0., 2.])
constant.prob([0., 3.])
tfd.VectorDeterministic(loc)
constant.prob([[0., 1.], [1.9, 3.], [3.99, 5.]])
self.prob([])
pmf(x; loc)
Abs(x - loc)
Abs(loc)
point (or batch of points)
statistics (e.g., mean, mode, variance)
dict(locals()
super(VectorDeterministic, self)
_params_event_ndims(cls)
dict(loc=1, atol=1, rtol=1)
_batch_shape_tensor(self, loc=None)
tf.shape(self.loc if loc is None else loc)
tf.broadcast_dynamic_shape(tf.shape(self.atol)
tf.shape(self.rtol)
_batch_shape(self)
tf.broadcast_static_shape(self.atol.shape, self.rtol.shape)
_event_shape_tensor(self, loc=None)
tf.shape(self.loc if loc is None else loc)
_event_shape(self)
_prob(self, x)
tf.convert_to_tensor(self.loc)
tf.reduce_all(tf.abs(x - loc)
self._slack(loc)
_sample_control_dependencies(self, x)
assertions.append(assert_util.assert_rank_at_least(x, 1)
self.event_shape_tensor()
tf.gather(tf.shape(x)
tf.rank(x)
kullback_leibler.RegisterKL(_BaseDeterministic, distribution.Distribution)
_kl_deterministic_distribution(a, b, name=None)
KL(a || b)
KL(a || b)
tf.name_scope(name or 'kl_deterministic_distribution')
b.log_prob(a.loc)
TestAppConfig(AppConfig)
__init__(self, start, end)
start.copy()