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

tf.contrib.distributions.Binomial.param_static_shapes(cls, sample_shape) param_shapes with static (i.e. TensorShape) shapes.

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

tf.contrib.learn.TensorFlowRNNClassifier.weights_ Returns weights of the rnn layer.

tf.contrib.distributions.Dirichlet.get_batch_shape() Shape of a single sample from a single event index as a TensorShape

class tf.contrib.learn.monitors.PrintTensor Prints given tensors every N steps. This is an EveryN

tf.contrib.distributions.StudentTWithAbsDfSoftplusSigma.survival_function(value, name='survival_function') Survival function.

tf.image.transpose_image(image) Transpose an image by swapping the first and second dimension. See

tf.contrib.bayesflow.stochastic_tensor.WishartCholeskyTensor.distribution

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