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

tf.contrib.learn.DNNRegressor.get_variable_names() Returns list of all variable names in this model. Returns: List of names.

class tf.ReaderBase Base class for different Reader types, that produce a record every step. Conceptually, Readers convert string 'work units' into records (key, value pairs). Typically the 'work units' are filenames and the records are extracted from the contents of those files. We want a single record produced per step, but a work unit can correspond to many records. Therefore we introduce some decoupling using a queue. The queue contains the work units and the Reader dequeues from the queue

void tensorflow::TensorShape::set_dim(int d, int64 size) Modifies the size of the dimension d to be size REQUIRES: 0 <= d < dims() REQUIRES: size >= 0

tf.contrib.bayesflow.stochastic_tensor.BetaTensor.__init__(name=None, dist_value_type=None, loss_fn=score_function, **dist_args)

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.