# Create Custom Session Run Hooks

Create a set of session run hooks, used to record information during training of an estimator. See Details for more information on the various hooks that can be defined.

session_run_hook(begin = function() { },
after_create_session = function(session, coord) { },
before_run = function(context) { }, after_run = function(context,
values) { }, end = function(session) { })

## Arguments

 begin function(): An R function, to be called once before using the session. after_create_session function(session, coord): An R function, to be called once the new TensorFlow session has been created. before_run function(run_context): An R function to be called before a run. after_run function(run_context, run_values): An R function to be called after a run. end function(session): An R function to be called at the end of the session. Typically, you'll want to define a before_run() hook that defines the set of tensors you're interested in for a particular run, and then you'll use the resulting values of those tensors in your after_run() hook. The tensors requested in your before_run() hook will be made available as part of the second argument in the after_run() hook (the values argument).

session_run_args()
Other session_run_hook wrappers: hook_checkpoint_saver, hook_global_step_waiter, hook_history_saver, hook_logging_tensor, hook_nan_tensor, hook_progress_bar, hook_step_counter, hook_stop_at_step, hook_summary_saver