tf.contrib.learn.monitors.ValidationMonitor.every_n_post_step(step, session) Callback after a step is finished or end() is called. Args: step: int, the current value of the global step. session: Session object.

tf.contrib.learn.monitors.LoggingTrainable.__init__(scope=None, every_n=100, first_n=1) Initializes LoggingTrainable monitor. Args: scope: An optional string to match variable names using re.match. every_n: Print every N steps. first_n: Print first N steps.

class tf.contrib.learn.monitors.SummarySaver Saves summaries every N steps.

tf.round(x, name=None) Rounds the values of a tensor to the nearest integer, element-wise. For example: # 'a' is [0.9, 2.5, 2.3, -4.4] tf.round(a) ==> [ 1.0, 3.0, 2.0, -4.0 ] Args: x: A Tensor of type float32 or float64. name: A name for the operation (optional). Returns: A Tensor of same shape and type as x.

tf.contrib.distributions.DirichletMultinomial.parameters Dictionary of parameters used by this Distribution.

tf.contrib.learn.monitors.LoggingTrainable.epoch_begin(epoch) Begin epoch. Args: epoch: int, the epoch number. Raises: ValueError: if we've already begun an epoch, or epoch < 0.

tf.contrib.distributions.MultivariateNormalFull.mode(name='mode') Mode.

tf.contrib.learn.monitors.ExportMonitor.begin(max_steps=None) Called at the beginning of training. When called, the default graph is the one we are executing. Args: max_steps: int, the maximum global step this training will run until. Raises: ValueError: if we've already begun a run.

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

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.