tf.contrib.distributions.Poisson.sample_n(n, seed=None, name='sample_n') Generate n samples. Args: n: Scalar Tensor of type int32 or int64, the number of observations to sample. seed: Python integer seed for RNG name: name to give to the op. Returns: samples: a Tensor with a prepended dimension (n,). Raises: TypeError: if n is not an integer type.

tf.contrib.distributions.Multinomial.dtype The DType of Tensors handled by this Distribution.

tf.contrib.distributions.MultivariateNormalDiag.sample_n(n, seed=None, name='sample_n') Generate n samples. Args: n: Scalar Tensor of type int32 or int64, the number of observations to sample. seed: Python integer seed for RNG name: name to give to the op. Returns: samples: a Tensor with a prepended dimension (n,). Raises: TypeError: if n is not an integer type.

tf.contrib.bayesflow.stochastic_tensor.CategoricalTensor.input_dict

tf.contrib.distributions.Mixture.pdf(value, name='pdf') Probability density function. Args: value: float or double Tensor. name: The name to give this op. Returns: prob: a Tensor of shape sample_shape(x) + self.batch_shape with values of type self.dtype. Raises: TypeError: if not is_continuous.

tf.contrib.distributions.QuantizedDistribution.log_survival_function(value, name='log_survival_function') Log survival function. Given random variable X, the survival function is defined: log_survival_function(x) = Log[ P[X > x] ] = Log[ 1 - P[X <= x] ] = Log[ 1 - cdf(x) ] Typically, different numerical approximations can be used for the log survival function, which are more accurate than 1 - cdf(x) when x >> 1. Additional document

tf.contrib.graph_editor.reroute_b2a(sgv0, sgv1) Re-route the inputs and outputs of sgv1 to sgv0 (see _reroute).

class tf.contrib.bayesflow.stochastic_tensor.InverseGammaTensor InverseGammaTensor is a StochasticTensor backed by the distribution InverseGamma.

class tf.contrib.bayesflow.stochastic_tensor.StudentTTensor StudentTTensor is a StochasticTensor backed by the distribution StudentT.

tf.contrib.graph_editor.SubGraphView.__nonzero__() Allows for implicit boolean conversion.