tf.contrib.distributions.Gamma.entropy(name='entropy') Shanon entropy in nats. Additional documentation from Gamma: This is defined to be entropy = alpha - log(beta) + log(Gamma(alpha)) + (1-alpha)digamma(alpha) where digamma(alpha) is the digamma function.

tf.contrib.graph_editor.select_ts(*args, **kwargs) Helper to select tensors. Args: *args: list of 1) regular expressions (compiled or not) or 2) (array of) tf.Tensor. tf.Operation instances are silently ignored. **kwargs: 'graph': tf.Graph in which to perform the regex query.This is required when using regex. 'positive_filter': an elem if selected only if positive_filter(elem) is True. This is optional. 'restrict_ts_regex': a regular expression is ignored if it doesn't start with the substri

tf.contrib.bayesflow.stochastic_tensor.BernoulliTensor.value(name='value')

tf.contrib.distributions.kl(dist_a, dist_b, allow_nan=False, name=None) Get the KL-divergence KL(dist_a || dist_b). Args: dist_a: The first distribution. dist_b: The second distribution. allow_nan: If False (default), a runtime error is raised if the KL returns NaN values for any batch entry of the given distributions. If True, the KL may return a NaN for the given entry. name: (optional) Name scope to use for created operations. Returns: A Tensor with the batchwise KL-divergence between

tf.contrib.distributions.MultivariateNormalFull.sigma_det(name='sigma_det') Determinant of covariance matrix.

tf.contrib.layers.l1_regularizer(scale, scope=None) Returns a function that can be used to apply L1 regularization to weights. L1 regularization encourages sparsity. Args: scale: A scalar multiplier Tensor. 0.0 disables the regularizer. scope: An optional scope name. Returns: A function with signature l1(weights) that apply L1 regularization. Raises: ValueError: If scale is negative or if scale is not a float.

class tf.contrib.bayesflow.stochastic_tensor.GammaWithSoftplusAlphaBetaTensor GammaWithSoftplusAlphaBetaTensor is a StochasticTensor backed by the distribution GammaWithSoftplusAlphaBeta.

Static helper routines for PartialTensorShape. Includes a few common predicates on a partially known tensor shape. Member Details string tensorflow::PartialTensorShapeUtils::PartialShapeListString(const gtl::ArraySlice< PartialTensorShape > &shapes) bool tensorflow::PartialTensorShapeUtils::AreCompatible(const gtl::ArraySlice< PartialTensorShape > &shapes0, const gtl::ArraySlice< PartialTensorShape > &shapes1)

tf.contrib.learn.monitors.LoggingTrainable.every_n_step_begin(step)

tf.errors.UnavailableError.__init__(node_def, op, message) Creates an UnavailableError.