NAME
AI::MXNet::Callback - A collection of predefined callback functions.
|
DESCRIPTION
A collection of predefined callback functions, mainly to be used in AI::MXNet::Module::Base::fit.
|
SYNOPSIS
my $model = mx->mod->Module(
symbol => $net,
context => $contexts
);
$model->fit(
$data_iter,
eval_metric => mx->metric->Perplexity,
kvstore => $kv_store,
optimizer => $optimizer,
optimizer_params => {
learning_rate => $lr,
momentum => $mom,
wd => $wd,
clip_gradient => 5,
rescale_grad => 1/$batch_size,
lr_scheduler => AI::MXNet::FactorScheduler->new(step => 1000, factor => 0.99)
},
initializer => mx->init->Xavier(factor_type => "in", magnitude => 2.34),
num_epoch => $num_epoch,
batch_end_callback => mx->callback->Speedometer($batch_size, $disp_batches),
($chkp_epoch ? (epoch_end_callback => [mx->callback->module_checkpoint($model, $chkp_prefix, $chkp_epoch), \&sample]) : ())
);
|
module_checkpoint
Callback to save the module setup in the checkpoint files.
Parameters
----------
$mod : subclass of AI::MXNet::Module::Base
The module to checkpoint.
$prefix : Str
The file prefix to checkpoint to
$period=1 : Int
How many epochs to wait before checkpointing. Default is 1.
$save_optimizer_states=0 : Bool
Whether to save optimizer states for later training.
Returns
-------
$callback : sub ref
The callback function that can be passed as iter_end_callback to fit.
|
log_train_metric
Callback to log the training evaluation result every period.
Parameters
----------
$period : Int
The number of batches after which to log the training evaluation metric.
$auto_reset : Bool
Whether to reset the metric after the logging.
Returns
-------
$callback : sub ref
The callback function that can be passed as iter_epoch_callback to fit.
|
NAME
AI::MXNet::Speedometer - A callback that logs training speed
|
DESCRIPTION
Calculate and log training speed periodically.
Parameters
----------
batch_size: int
batch_size of data
frequent: int
How many batches between calculations.
Defaults to calculating & logging every 50 batches.
auto_reset: Bool
Reset the metric after each log, defaults to true.
|
NAME
AI::MXNet::ProgressBar - A callback to show a progress bar.
|
DESCRIPTION
Shows a progress bar.
Parameters
----------
total: Int
batch size, default is 1
length: Int
the length of the progress bar, default is 80 chars
|
NAME
AI::MXNet::LogValidationMetricsCallback - A callback to log the eval metrics at the end of an epoch.
|