tf.contrib.distributions.Bernoulli.prob(value, name='prob') Probability density/mass function (depending on is_continuous). 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.

tf.WholeFileReader.supports_serialize Whether the Reader implementation can serialize its state.

tf.contrib.bayesflow.stochastic_tensor.CategoricalTensor.dtype

tf.WholeFileReader.reset(name=None) Restore a reader to its initial clean state. Args: name: A name for the operation (optional). Returns: The created Operation.

tf.contrib.crf.CrfForwardRnnCell.__init__(transition_params) Initialize the CrfForwardRnnCell. Args: transition_params: A [num_tags, num_tags] matrix of binary potentials. This matrix is expanded into a [1, num_tags, num_tags] in preparation for the broadcast summation occurring within the cell.

tf.contrib.distributions.Binomial.is_reparameterized

tf.contrib.distributions.BernoulliWithSigmoidP.__init__(p=None, dtype=tf.int32, validate_args=False, allow_nan_stats=True, name='BernoulliWithSigmoidP')

tf.contrib.learn.TensorFlowEstimator.restore(cls, path, config=None) Restores model from give path. Args: path: Path to the checkpoints and other model information. config: RunConfig object that controls the configurations of the session, e.g. num_cores, gpu_memory_fraction, etc. This is allowed to be reconfigured. Returns: Estimator, object of the subclass of TensorFlowEstimator. Raises: ValueError: if path does not contain a model definition.

tf.contrib.distributions.MultivariateNormalDiagPlusVDVT.variance(name='variance') Variance.

tf.contrib.distributions.GammaWithSoftplusAlphaBeta.allow_nan_stats Python boolean describing behavior when a stat is undefined. Stats return +/- infinity when it makes sense. E.g., the variance of a Cauchy distribution is infinity. However, sometimes the statistic is undefined, e.g., if a distribution's pdf does not achieve a maximum within the support of the distribution, the mode is undefined. If the mean is undefined, then by definition the variance is undefined. E.g. the mean for Student'