LostTech.TensorFlow : API Documentation

Type MultiHostDatasetInitializerHook

Namespace tensorflow_estimator.python.estimator.tpu.util

Parent SessionRunHook

Interfaces IMultiHostDatasetInitializerHook

Public instance methods

object after_create_session(object session, object coord)

Called when new TensorFlow session is created.

This is called to signal the hooks that a new session has been created. This has two essential differences with the situation in which `begin` is called:

* When this is called, the graph is finalized and ops can no longer be added to the graph. * This method will also be called as a result of recovering a wrapped session, not only at the beginning of the overall session.
Parameters
object session
A TensorFlow Session that has been created.
object coord
A Coordinator object which keeps track of all threads.

object after_create_session_dyn(object session, object coord)

Called when new TensorFlow session is created.

This is called to signal the hooks that a new session has been created. This has two essential differences with the situation in which `begin` is called:

* When this is called, the graph is finalized and ops can no longer be added to the graph. * This method will also be called as a result of recovering a wrapped session, not only at the beginning of the overall session.
Parameters
object session
A TensorFlow Session that has been created.
object coord
A Coordinator object which keeps track of all threads.

void after_run(SessionRunContext run_context, SessionRunValues run_values)

Called after each call to run().

The `run_values` argument contains results of requested ops/tensors by `before_run()`.

The `run_context` argument is the same one send to `before_run` call. `run_context.request_stop()` can be called to stop the iteration.

If `session.run()` raises any exceptions then `after_run()` is not called.
Parameters
SessionRunContext run_context
A `SessionRunContext` object.
SessionRunValues run_values
A SessionRunValues object.

object after_run_dyn(object run_context, object run_values)

Called after each call to run().

The `run_values` argument contains results of requested ops/tensors by `before_run()`.

The `run_context` argument is the same one send to `before_run` call. `run_context.request_stop()` can be called to stop the iteration.

If `session.run()` raises any exceptions then `after_run()` is not called.
Parameters
object run_context
A `SessionRunContext` object.
object run_values
A SessionRunValues object.

SessionRunArgs before_run(SessionRunContext run_context)

Called before each call to run().

You can return from this call a `SessionRunArgs` object indicating ops or tensors to add to the upcoming `run()` call. These ops/tensors will be run together with the ops/tensors originally passed to the original run() call. The run args you return can also contain feeds to be added to the run() call.

The `run_context` argument is a `SessionRunContext` that provides information about the upcoming `run()` call: the originally requested op/tensors, the TensorFlow Session.

At this point graph is finalized and you can not add ops.
Parameters
SessionRunContext run_context
A `SessionRunContext` object.
Returns
SessionRunArgs
None or a `SessionRunArgs` object.

object before_run_dyn(object run_context)

Called before each call to run().

You can return from this call a `SessionRunArgs` object indicating ops or tensors to add to the upcoming `run()` call. These ops/tensors will be run together with the ops/tensors originally passed to the original run() call. The run args you return can also contain feeds to be added to the run() call.

The `run_context` argument is a `SessionRunContext` that provides information about the upcoming `run()` call: the originally requested op/tensors, the TensorFlow Session.

At this point graph is finalized and you can not add ops.
Parameters
object run_context
A `SessionRunContext` object.
Returns
object
None or a `SessionRunArgs` object.

void begin()

Called once before using the session.

When called, the default graph is the one that will be launched in the session. The hook can modify the graph by adding new operations to it. After the `begin()` call the graph will be finalized and the other callbacks can not modify the graph anymore. Second call of `begin()` on the same graph, should not change the graph.

object begin_dyn()

Called once before using the session.

When called, the default graph is the one that will be launched in the session. The hook can modify the graph by adding new operations to it. After the `begin()` call the graph will be finalized and the other callbacks can not modify the graph anymore. Second call of `begin()` on the same graph, should not change the graph.

void end(object session)

Called at the end of session.

The `session` argument can be used in case the hook wants to run final ops, such as saving a last checkpoint.

If `session.run()` raises exception other than OutOfRangeError or StopIteration then `end()` is not called. Note the difference between `end()` and `after_run()` behavior when `session.run()` raises OutOfRangeError or StopIteration. In that case `end()` is called but `after_run()` is not called.
Parameters
object session
A TensorFlow Session that will be soon closed.

object end_dyn(object session)

Called at the end of session.

The `session` argument can be used in case the hook wants to run final ops, such as saving a last checkpoint.

If `session.run()` raises exception other than OutOfRangeError or StopIteration then `end()` is not called. Note the difference between `end()` and `after_run()` behavior when `session.run()` raises OutOfRangeError or StopIteration. In that case `end()` is called but `after_run()` is not called.
Parameters
object session
A TensorFlow Session that will be soon closed.

Public properties

object PythonObject get;