tf.contrib.learn.monitors.LoggingTrainable.run_on_all_workers

tf.erf(x, name=None) Computes the Gauss error function of x element-wise. Args: x: A Tensor of SparseTensor. Must be one of the following types: half, float32, float64. name: A name for the operation (optional). Returns: A Tensor or SparseTensor, respectively. Has the same type as x.

tf.contrib.bayesflow.stochastic_tensor.BetaTensor.distribution

tf.contrib.distributions.MultivariateNormalFull.pdf(value, name='pdf') Probability density function. 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. Raises: TypeError: if not is_continuous.

tf.contrib.distributions.Binomial.is_continuous

tf.contrib.bayesflow.stochastic_tensor.Chi2Tensor.clone(name=None, **dist_args)

tf.read_file(filename, name=None) Reads and outputs the entire contents of the input filename. Args: filename: A Tensor of type string. name: A name for the operation (optional). Returns: A Tensor of type string.

tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalFullTensor.graph

tf.contrib.learn.monitors.StepCounter.__init__(every_n_steps=100, output_dir=None, summary_writer=None)

tf.contrib.bayesflow.stochastic_tensor.UniformTensor.clone(name=None, **dist_args)