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# Variables
Note: Functions taking `Tensor` arguments can also take anything accepted by
`tf.convert_to_tensor`.
[TOC]
## Variables
* `tf.Variable`
## Variable helper functions
TensorFlow provides a set of functions to help manage the set of variables
collected in the graph.
* `tf.global_variables`
* `tf.local_variables`
* `tf.model_variables`
* `tf.trainable_variables`
* `tf.moving_average_variables`
* `tf.global_variables_initializer`
* `tf.local_variables_initializer`
* `tf.variables_initializer`
* `tf.is_variable_initialized`
* `tf.report_uninitialized_variables`
* `tf.assert_variables_initialized`
* `tf.assign`
* `tf.assign_add`
* `tf.assign_sub`
## Saving and Restoring Variables
* `tf.train.Saver`
* `tf.train.latest_checkpoint`
* `tf.train.get_checkpoint_state`
* `tf.train.update_checkpoint_state`
## Sharing Variables
TensorFlow provides several classes and operations that you can use to
create variables contingent on certain conditions.
* `tf.get_variable`
* `tf.get_local_variable`
* `tf.VariableScope`
* `tf.variable_scope`
* `tf.variable_op_scope`
* `tf.get_variable_scope`
* `tf.make_template`
* `tf.no_regularizer`
* `tf.constant_initializer`
* `tf.random_normal_initializer`
* `tf.truncated_normal_initializer`
* `tf.random_uniform_initializer`
* `tf.uniform_unit_scaling_initializer`
* `tf.zeros_initializer`
* `tf.ones_initializer`
* `tf.orthogonal_initializer`
## Variable Partitioners for Sharding
* `tf.fixed_size_partitioner`
* `tf.variable_axis_size_partitioner`
* `tf.min_max_variable_partitioner`
## Sparse Variable Updates
The sparse update ops modify a subset of the entries in a dense `Variable`,
either overwriting the entries or adding / subtracting a delta. These are
useful for training embedding models and similar lookup-based networks, since
only a small subset of embedding vectors change in any given step.
Since a sparse update of a large tensor may be generated automatically during
gradient computation (as in the gradient of
`tf.gather`),
an `tf.IndexedSlices` class is provided that encapsulates a set
of sparse indices and values. `IndexedSlices` objects are detected and handled
automatically by the optimizers in most cases.
* `tf.scatter_update`
* `tf.scatter_add`
* `tf.scatter_sub`
* `tf.scatter_mul`
* `tf.scatter_div`
* `tf.scatter_min`
* `tf.scatter_max`
* `tf.scatter_nd_update`
* `tf.scatter_nd_add`
* `tf.scatter_nd_sub`
* `tf.sparse_mask`
* `tf.IndexedSlices`
### Read-only Lookup Tables
* `tf.initialize_all_tables`
* `tf.tables_initializer`
## Exporting and Importing Meta Graphs
* `tf.train.export_meta_graph`
* `tf.train.import_meta_graph`
# Deprecated functions (removed after 2017-03-02). Please don't use them.
* `tf.all_variables`
* `tf.initialize_all_variables`
* `tf.initialize_local_variables`
* `tf.initialize_variables`
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