Module: tf.train

Support for training models.

See the Training guide.

Modules

experimental module: Public API for tf.train.experimental namespace.

Classes

class BytesList: Used in tf.train.Example protos. Holds a list of byte-strings.

class Checkpoint: Manages saving/restoring trackable values to disk.

class CheckpointManager: Manages multiple checkpoints by keeping some and deleting unneeded ones.

class CheckpointOptions: Options for constructing a Checkpoint.

class CheckpointView: Gathers and serializes a checkpoint view.

class ClusterDef: A ProtocolMessage

class ClusterSpec: Represents a cluster as a set of "tasks", organized into "jobs".

class Coordinator: A coordinator for threads.

class Example: An Example is a standard proto storing data for training and inference.

class ExponentialMovingAverage: Maintains moving averages of variables by employing an exponential decay.

class Feature: Used in tf.train.Example protos. Contains a list of values.

class FeatureList: Mainly used as part of a tf.train.SequenceExample.

class FeatureLists: Mainly used as part of a tf.train.SequenceExample.

class Features: Used in tf.train.Example protos. Contains the mapping from keys to Feature.

class FloatList: Used in tf.train.Example protos. Holds a list of floats.

class Int64List: Used in tf.train.Example protos. Holds a list of Int64s.

class JobDef: A ProtocolMessage

class SequenceExample: A SequenceExample represents a sequence of features and some context.

class ServerDef: A ProtocolMessage

class TrackableView: Gathers and serializes a trackable view.

Functions

checkpoints_iterator(...): Continuously yield new checkpoint files as they appear.

get_checkpoint_state(...): Returns CheckpointState proto from the "checkpoint" file.

latest_checkpoint(...): Finds the filename of latest saved checkpoint file.

list_variables(...): Lists the checkpoint keys and shapes of variables in a checkpoint.

load_checkpoint(...): Returns CheckpointReader for checkpoint found in ckpt_dir_or_file.

load_variable(...): Returns the tensor value of the given variable in the checkpoint.