tf.contrib.distributions.Multinomial.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.BernoulliWithSigmoidPTensor.entropy(name='entropy')

tf.contrib.learn.LinearRegressor.get_variable_value(name) Returns value of the variable given by name. Args: name: string, name of the tensor. Returns: Numpy array - value of the tensor.

tf.contrib.distributions.BetaWithSoftplusAB.is_reparameterized

Status tensorflow::Env::CreateDir(const string &dirname) Creates the specified directory.

tf.contrib.bayesflow.stochastic_tensor.MixtureTensor.input_dict

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

tf.contrib.distributions.Beta.a Shape parameter.

tf.contrib.distributions.Exponential.log_prob(value, name='log_prob') Log probability density/mass function (depending on is_continuous). Args: value: float or double Tensor. name: The name to give this op. Returns: log_prob: a Tensor of shape sample_shape(x) + self.batch_shape with values of type self.dtype.

tf.errors.AbortedError.__init__(node_def, op, message) Creates an AbortedError.