bool tensorflow::Tensor::IsAligned() const Returns true iff this tensor is aligned.

tf.contrib.learn.monitors.BaseMonitor.run_on_all_workers

tensorflow::error::Code tensorflow::Status::code() const

tf.contrib.bayesflow.stochastic_tensor.InverseGammaTensor.dtype

virtual Status tensorflow::Session::Extend(const GraphDef &graph)=0 Adds operations to the graph that is already registered with the Session . The names of new operations in "graph" must not exist in the graph that is already registered.

tf.contrib.learn.BaseEstimator.__init__(model_dir=None, config=None) Initializes a BaseEstimator instance. Args: model_dir: Directory to save model parameters, graph and etc. This can also be used to load checkpoints from the directory into a estimator to continue training a previously saved model. config: A RunConfig instance.

tf.contrib.distributions.InverseGammaWithSoftplusAlphaBeta.pmf(value, name='pmf') Probability mass function. Args: value: float or double Tensor. name: The name to give this op. Returns: pmf: a Tensor of shape sample_shape(x) + self.batch_shape with values of type self.dtype. Raises: TypeError: if is_continuous.

tf.contrib.distributions.NormalWithSoftplusSigma.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.learn.LinearClassifier.bias_

tf.contrib.distributions.Laplace.std(name='std') Standard deviation.