Support for training models.
See the Training guide.
experimental
module: Public API for tf.train.experimental namespace.
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
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