Type Scaffold
Namespace tensorflow.train
Parent PythonObjectContainer
Interfaces IScaffold
Structure to create or gather pieces commonly needed to train a model. When you build a model for training you usually need ops to initialize
variables, a `Saver` to checkpoint them, an op to collect summaries for
the visualizer, and so on. Various libraries built on top of the core TensorFlow library take care of
creating some or all of these pieces and storing them in well known
collections in the graph. The `Scaffold` class helps pick these pieces from
the graph collections, creating and adding them to the collections if needed. If you call the scaffold constructor without any arguments, it will pick
pieces from the collections, creating default ones if needed when
`scaffold.finalize()` is called. You can pass arguments to the constructor to
provide your own pieces. Pieces that you pass to the constructor are not
added to the graph collections. The following pieces are directly accessible as attributes of the `Scaffold`
object: * `saver`: A `tf.compat.v1.train.Saver` object taking care of saving the
variables.
Picked from and stored into the `SAVERS` collection in the graph by default.
* `init_op`: An op to run to initialize the variables. Picked from and
stored into the `INIT_OP` collection in the graph by default.
* `ready_op`: An op to verify that the variables are initialized. Picked
from and stored into the `READY_OP` collection in the graph by default.
* `ready_for_local_init_op`: An op to verify that global state has been
initialized and it is alright to run `local_init_op`. Picked from and
stored into the `READY_FOR_LOCAL_INIT_OP` collection in the graph by
default. This is needed when the initialization of local variables depends
on the values of global variables.
* `local_init_op`: An op to initialize the local variables. Picked
from and stored into the `LOCAL_INIT_OP` collection in the graph by default.
* `summary_op`: An op to run and merge the summaries in the graph. Picked
from and stored into the `SUMMARY_OP` collection in the graph by default. You can also pass the following additional pieces to the constructor: * `init_feed_dict`: A session feed dictionary that should be used when
running the init op.
* `init_fn`: A callable to run after the init op to perform additional
initializations. The callable will be called as
`init_fn(scaffold, session)`.
Methods
Properties
Public static methods
object default_local_init_op()
Returns an op that groups the default local init ops. This op is used during session initialization when a Scaffold is
initialized without specifying the local_init_op arg. It includes
`tf.compat.v1.local_variables_initializer`,
`tf.compat.v1.tables_initializer`, and also
initializes local session resources.
Returns
-
object
- The default Scaffold local init op.
object default_local_init_op_dyn()
Returns an op that groups the default local init ops. This op is used during session initialization when a Scaffold is
initialized without specifying the local_init_op arg. It includes
`tf.compat.v1.local_variables_initializer`,
`tf.compat.v1.tables_initializer`, and also
initializes local session resources.
Returns
-
object
- The default Scaffold local init op.
object get_or_default(string arg_name, string collection_key, object default_constructor)
Get from cache or create a default operation.
object get_or_default_dyn(object arg_name, object collection_key, object default_constructor)
Get from cache or create a default operation.