tf.contrib.distributions.Chi2WithAbsDf.validate_args Python boolean indicated possibly expensive checks are enabled.

tf.contrib.distributions.BernoulliWithSigmoidP.event_shape(name='event_shape') Shape of a single sample from a single batch as a 1-D int32 Tensor. Args: name: name to give to the op Returns: event_shape: Tensor.

tf.contrib.distributions.StudentT.cdf(value, name='cdf') Cumulative distribution function. Given random variable X, the cumulative distribution function cdf is: cdf(x) := P[X <= x] Args: value: float or double Tensor. name: The name to give this op. Returns: cdf: a Tensor of shape sample_shape(x) + self.batch_shape with values of type self.dtype.

tf.contrib.bayesflow.stochastic_tensor.TransformedDistributionTensor.input_dict

tf.contrib.distributions.DirichletMultinomial.n Parameter defining this distribution.

class tf.contrib.graph_editor.Transformer Transform a subgraph into another one. By default, the constructor create a transform which copy a subgraph and replaces inputs with placeholders. This behavior can be modified by changing the handlers.

tf.contrib.metrics.streaming_recall(*args, **kwargs) Computes the recall of the predictions with respect to the labels. (deprecated arguments) SOME ARGUMENTS ARE DEPRECATED. They will be removed after 2016-10-19. Instructions for updating: ignore_mask is being deprecated. Instead use weights with values 0.0 and 1.0 to mask values. For example, weights=tf.logical_not(mask). The streaming_recall function creates two local variables, true_positives and false_negatives, that are used to compute th

tf.ReaderBase.read(queue, name=None) Returns the next record (key, value pair) produced by a reader. Will dequeue a work unit from queue if necessary (e.g. when the Reader needs to start reading from a new file since it has finished with the previous file). Args: queue: A Queue or a mutable string Tensor representing a handle to a Queue, with string work items. name: A name for the operation (optional). Returns: A tuple of Tensors (key, value). key: A string scalar Tensor. value: A strin

tf.contrib.distributions.MultivariateNormalCholesky.name Name prepended to all ops created by this Distribution.

tf.contrib.distributions.LaplaceWithSoftplusScale.cdf(value, name='cdf') Cumulative distribution function. Given random variable X, the cumulative distribution function cdf is: cdf(x) := P[X <= x] Args: value: float or double Tensor. name: The name to give this op. Returns: cdf: a Tensor of shape sample_shape(x) + self.batch_shape with values of type self.dtype.