# Module: tf.compat.v1.train
Public API for tf._api.v2.train namespace ## Modules [`experimental`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/experimental) module: Public API for tf._api.v2.train.experimental namespace [`queue_runner`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/queue_runner) module: Public API for tf._api.v2.train.queue_runner namespace ## Classes [`class AdadeltaOptimizer`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/AdadeltaOptimizer): Optimizer that implements the Adadelta algorithm. [`class AdagradDAOptimizer`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/AdagradDAOptimizer): Adagrad Dual Averaging algorithm for sparse linear models. [`class AdagradOptimizer`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/AdagradOptimizer): Optimizer that implements the Adagrad algorithm. [`class AdamOptimizer`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/AdamOptimizer): Optimizer that implements the Adam algorithm. [`class BytesList`](https://www.tensorflow.org/api_docs/python/tf/train/BytesList): Used in [`tf.train.Example`](https://www.tensorflow.org/api_docs/python/tf/train/Example) protos. Holds a list of byte-strings. [`class Checkpoint`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/Checkpoint): Groups trackable objects, saving and restoring them. [`class CheckpointManager`](https://www.tensorflow.org/api_docs/python/tf/train/CheckpointManager): Manages multiple checkpoints by keeping some and deleting unneeded ones. [`class CheckpointOptions`](https://www.tensorflow.org/api_docs/python/tf/train/CheckpointOptions): Options for constructing a Checkpoint. [`class CheckpointSaverHook`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/CheckpointSaverHook): Saves checkpoints every N steps or seconds. [`class CheckpointSaverListener`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/CheckpointSaverListener): Interface for listeners that take action before or after checkpoint save. [`class ChiefSessionCreator`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/ChiefSessionCreator): Creates a tf.compat.v1.Session for a chief. [`class ClusterDef`](https://www.tensorflow.org/api_docs/python/tf/train/ClusterDef): A ProtocolMessage [`class ClusterSpec`](https://www.tensorflow.org/api_docs/python/tf/train/ClusterSpec): Represents a cluster as a set of "tasks", organized into "jobs". [`class Coordinator`](https://www.tensorflow.org/api_docs/python/tf/train/Coordinator): A coordinator for threads. [`class Example`](https://www.tensorflow.org/api_docs/python/tf/train/Example): An `Example` is a standard proto storing data for training and inference. [`class ExponentialMovingAverage`](https://www.tensorflow.org/api_docs/python/tf/train/ExponentialMovingAverage): Maintains moving averages of variables by employing an exponential decay. [`class Feature`](https://www.tensorflow.org/api_docs/python/tf/train/Feature): Used in [`tf.train.Example`](https://www.tensorflow.org/api_docs/python/tf/train/Example) protos. Contains a list of values. [`class FeatureList`](https://www.tensorflow.org/api_docs/python/tf/train/FeatureList): Mainly used as part of a [`tf.train.SequenceExample`](https://www.tensorflow.org/api_docs/python/tf/train/SequenceExample). [`class FeatureLists`](https://www.tensorflow.org/api_docs/python/tf/train/FeatureLists): Mainly used as part of a [`tf.train.SequenceExample`](https://www.tensorflow.org/api_docs/python/tf/train/SequenceExample). [`class Features`](https://www.tensorflow.org/api_docs/python/tf/train/Features): Used in [`tf.train.Example`](https://www.tensorflow.org/api_docs/python/tf/train/Example) protos. Contains the mapping from keys to `Feature`. [`class FeedFnHook`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/FeedFnHook): Runs `feed_fn` and sets the `feed_dict` accordingly. [`class FinalOpsHook`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/FinalOpsHook): A hook which evaluates `Tensors` at the end of a session. [`class FloatList`](https://www.tensorflow.org/api_docs/python/tf/train/FloatList): Used in [`tf.train.Example`](https://www.tensorflow.org/api_docs/python/tf/train/Example) protos. Holds a list of floats. [`class FtrlOptimizer`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/FtrlOptimizer): Optimizer that implements the FTRL algorithm. [`class GlobalStepWaiterHook`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/GlobalStepWaiterHook): Delays execution until global step reaches `wait_until_step`. [`class GradientDescentOptimizer`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/GradientDescentOptimizer): Optimizer that implements the gradient descent algorithm. [`class Int64List`](https://www.tensorflow.org/api_docs/python/tf/train/Int64List): Used in [`tf.train.Example`](https://www.tensorflow.org/api_docs/python/tf/train/Example) protos. Holds a list of Int64s. [`class JobDef`](https://www.tensorflow.org/api_docs/python/tf/train/JobDef): A ProtocolMessage [`class LoggingTensorHook`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/LoggingTensorHook): Prints the given tensors every N local steps, every N seconds, or at end. [`class LooperThread`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/LooperThread): A thread that runs code repeatedly, optionally on a timer. [`class MomentumOptimizer`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/MomentumOptimizer): Optimizer that implements the Momentum algorithm. [`class MonitoredSession`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/MonitoredSession): Session-like object that handles initialization, recovery and hooks. [`class NanLossDuringTrainingError`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/NanLossDuringTrainingError): Unspecified run-time error. [`class NanTensorHook`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/NanTensorHook): Monitors the loss tensor and stops training if loss is NaN. [`class Optimizer`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/Optimizer): Base class for optimizers. [`class ProfilerHook`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/ProfilerHook): Captures CPU/GPU profiling information every N steps or seconds. [`class ProximalAdagradOptimizer`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/ProximalAdagradOptimizer): Optimizer that implements the Proximal Adagrad algorithm. [`class ProximalGradientDescentOptimizer`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/ProximalGradientDescentOptimizer): Optimizer that implements the proximal gradient descent algorithm. [`class QueueRunner`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/QueueRunner): Holds a list of enqueue operations for a queue, each to be run in a thread. [`class RMSPropOptimizer`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/RMSPropOptimizer): Optimizer that implements the RMSProp algorithm (Tielemans et al. [`class Saver`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/Saver): Saves and restores variables. [`class SaverDef`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/SaverDef): A ProtocolMessage [`class Scaffold`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/Scaffold): Structure to create or gather pieces commonly needed to train a model. [`class SecondOrStepTimer`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/SecondOrStepTimer): Timer that triggers at most once every N seconds or once every N steps. [`class SequenceExample`](https://www.tensorflow.org/api_docs/python/tf/train/SequenceExample): A `SequenceExample` represents a sequence of features and some context. [`class Server`](https://www.tensorflow.org/api_docs/python/tf/distribute/Server): An in-process TensorFlow server, for use in distributed training. [`class ServerDef`](https://www.tensorflow.org/api_docs/python/tf/train/ServerDef): A ProtocolMessage [`class SessionCreator`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/SessionCreator): A factory for tf.Session. [`class SessionManager`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/SessionManager): Training helper that restores from checkpoint and creates session. [`class SessionRunArgs`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/SessionRunArgs): Represents arguments to be added to a `Session.run()` call. [`class SessionRunContext`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/SessionRunContext): Provides information about the `session.run()` call being made. [`class SessionRunHook`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/SessionRunHook): Hook to extend calls to MonitoredSession.run(). [`class SessionRunValues`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/SessionRunValues): Contains the results of `Session.run()`. [`class SingularMonitoredSession`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/SingularMonitoredSession): Session-like object that handles initialization, restoring, and hooks. [`class StepCounterHook`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/StepCounterHook): Hook that counts steps per second. [`class StopAtStepHook`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/StopAtStepHook): Hook that requests stop at a specified step. [`class SummarySaverHook`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/SummarySaverHook): Saves summaries every N steps. [`class Supervisor`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/Supervisor): A training helper that checkpoints models and computes summaries. [`class SyncReplicasOptimizer`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/SyncReplicasOptimizer): Class to synchronize, aggregate gradients and pass them to the optimizer. [`class VocabInfo`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/VocabInfo): Vocabulary information for warm-starting. [`class WorkerSessionCreator`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/WorkerSessionCreator): Creates a tf.compat.v1.Session for a worker. ## Functions [`MonitoredTrainingSession(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/MonitoredTrainingSession): Creates a `MonitoredSession` for training. [`NewCheckpointReader(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/NewCheckpointReader): A function that returns a CheckPointReader. [`add_queue_runner(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/add_queue_runner): Adds a `QueueRunner` to a collection in the graph. (deprecated) [`assert_global_step(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/assert_global_step): Asserts `global_step_tensor` is a scalar int `Variable` or `Tensor`. [`basic_train_loop(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/basic_train_loop): Basic loop to train a model. [`batch(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/batch): Creates batches of tensors in `tensors`. (deprecated) [`batch_join(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/batch_join): Runs a list of tensors to fill a queue to create batches of examples. (deprecated) [`checkpoint_exists(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/checkpoint_exists): Checks whether a V1 or V2 checkpoint exists with the specified prefix. (deprecated) [`checkpoints_iterator(...)`](https://www.tensorflow.org/api_docs/python/tf/train/checkpoints_iterator): Continuously yield new checkpoint files as they appear. [`cosine_decay(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/cosine_decay): Applies cosine decay to the learning rate. [`cosine_decay_restarts(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/cosine_decay_restarts): Applies cosine decay with restarts to the learning rate. [`create_global_step(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/create_global_step): Create global step tensor in graph. [`do_quantize_training_on_graphdef(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/do_quantize_training_on_graphdef): A general quantization scheme is being developed in `tf.contrib.quantize`. (deprecated) [`exponential_decay(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/exponential_decay): Applies exponential decay to the learning rate. [`export_meta_graph(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/export_meta_graph): Returns `MetaGraphDef` proto. [`generate_checkpoint_state_proto(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/generate_checkpoint_state_proto): Generates a checkpoint state proto. [`get_checkpoint_mtimes(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/get_checkpoint_mtimes): Returns the mtimes (modification timestamps) of the checkpoints. (deprecated) [`get_checkpoint_state(...)`](https://www.tensorflow.org/api_docs/python/tf/train/get_checkpoint_state): Returns CheckpointState proto from the "checkpoint" file. [`get_global_step(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/get_global_step): Get the global step tensor. [`get_or_create_global_step(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/get_or_create_global_step): Returns and create (if necessary) the global step tensor. [`global_step(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/global_step): Small helper to get the global step. [`import_meta_graph(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/import_meta_graph): Recreates a Graph saved in a `MetaGraphDef` proto. [`init_from_checkpoint(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/init_from_checkpoint): Replaces [`tf.Variable`](https://www.tensorflow.org/api_docs/python/tf/Variable) initializers so they load from a checkpoint file. [`input_producer(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/input_producer): Output the rows of `input_tensor` to a queue for an input pipeline. (deprecated) [`inverse_time_decay(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/inverse_time_decay): Applies inverse time decay to the initial learning rate. [`latest_checkpoint(...)`](https://www.tensorflow.org/api_docs/python/tf/train/latest_checkpoint): Finds the filename of latest saved checkpoint file. [`limit_epochs(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/limit_epochs): Returns tensor `num_epochs` times and then raises an `OutOfRange` error. (deprecated) [`linear_cosine_decay(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/linear_cosine_decay): Applies linear cosine decay to the learning rate. [`list_variables(...)`](https://www.tensorflow.org/api_docs/python/tf/train/list_variables): Lists the checkpoint keys and shapes of variables in a checkpoint. [`load_checkpoint(...)`](https://www.tensorflow.org/api_docs/python/tf/train/load_checkpoint): Returns `CheckpointReader` for checkpoint found in `ckpt_dir_or_file`. [`load_variable(...)`](https://www.tensorflow.org/api_docs/python/tf/train/load_variable): Returns the tensor value of the given variable in the checkpoint. [`match_filenames_once(...)`](https://www.tensorflow.org/api_docs/python/tf/io/match_filenames_once): Save the list of files matching pattern, so it is only computed once. [`maybe_batch(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/maybe_batch): Conditionally creates batches of tensors based on `keep_input`. (deprecated) [`maybe_batch_join(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/maybe_batch_join): Runs a list of tensors to conditionally fill a queue to create batches. (deprecated) [`maybe_shuffle_batch(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/maybe_shuffle_batch): Creates batches by randomly shuffling conditionally-enqueued tensors. (deprecated) [`maybe_shuffle_batch_join(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/maybe_shuffle_batch_join): Create batches by randomly shuffling conditionally-enqueued tensors. (deprecated) [`natural_exp_decay(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/natural_exp_decay): Applies natural exponential decay to the initial learning rate. [`noisy_linear_cosine_decay(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/noisy_linear_cosine_decay): Applies noisy linear cosine decay to the learning rate. [`piecewise_constant(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/piecewise_constant): Piecewise constant from boundaries and interval values. [`piecewise_constant_decay(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/piecewise_constant): Piecewise constant from boundaries and interval values. [`polynomial_decay(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/polynomial_decay): Applies a polynomial decay to the learning rate. [`range_input_producer(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/range_input_producer): Produces the integers from 0 to limit-1 in a queue. (deprecated) [`remove_checkpoint(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/remove_checkpoint): Removes a checkpoint given by `checkpoint_prefix`. (deprecated) [`replica_device_setter(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/replica_device_setter): Return a `device function` to use when building a Graph for replicas. [`sdca_fprint(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/sdca_fprint): Computes fingerprints of the input strings. [`sdca_optimizer(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/sdca_optimizer): Distributed version of Stochastic Dual Coordinate Ascent (SDCA) optimizer for [`sdca_shrink_l1(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/sdca_shrink_l1): Applies L1 regularization shrink step on the parameters. [`shuffle_batch(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/shuffle_batch): Creates batches by randomly shuffling tensors. (deprecated) [`shuffle_batch_join(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/shuffle_batch_join): Create batches by randomly shuffling tensors. (deprecated) [`slice_input_producer(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/slice_input_producer): Produces a slice of each `Tensor` in `tensor_list`. (deprecated) [`start_queue_runners(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/start_queue_runners): Starts all queue runners collected in the graph. (deprecated) [`string_input_producer(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/string_input_producer): Output strings (e.g. filenames) to a queue for an input pipeline. (deprecated) [`summary_iterator(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/summary_iterator): Returns a iterator for reading `Event` protocol buffers from an event file. [`update_checkpoint_state(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/update_checkpoint_state): Updates the content of the 'checkpoint' file. (deprecated) [`warm_start(...)`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/warm_start): Warm-starts a model using the given settings. [`write_graph(...)`](https://www.tensorflow.org/api_docs/python/tf/io/write_graph): Writes a graph proto to a file.