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Module: tf.train

Support for training models.

See the Training guide.

Modules

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

Classes

class BytesList: A ProtocolMessage

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 ClusterDef: A ProtocolMessage

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

class Coordinator: A coordinator for threads.

class Example: A ProtocolMessage

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

class Feature: A ProtocolMessage

class FeatureList: A ProtocolMessage

class FeatureLists: A ProtocolMessage

class Features: A ProtocolMessage

class FloatList: A ProtocolMessage

class Int64List: A ProtocolMessage

class JobDef: A ProtocolMessage

class SequenceExample: A ProtocolMessage

class ServerDef: A ProtocolMessage

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.

© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/train