NAME
AI::MXNet::Executor - The actual executing object of MXNet.
SYNOPSIS
my $executor = $sym->bind(
ctx => mx->Context('cpu'),
args => [$lhs_arr, $rhs_arr],
args_grad => [$lhs_grad, $rhs_grad]
);
$executor->forward(1);
print $executor->outputs->[0]->aspdl;
new
Constructor, used by AI::MXNet::Symbol->bind and by AI::MXNet::Symbol->simple_bind.
Parameters
----------
handle: ExecutorHandle
ExecutorHandle is generated by calling bind.
See Also
--------
AI::MXNet::Symbol->bind : how to create the AI::MXNet::Executor.
outputs
The output ndarrays bound to this executor.
Returns
-------
An array ref with AI::MXNet::NDArray objects bound to the heads of the executor.
forward
Calculate the outputs specified by the bound symbol.
Parameters
----------
$is_train=0: Bool, optional
whether this forward is for evaluation purpose. If True,
a backward call is expected to follow. Otherwise following
backward is invalid.
%kwargs
Additional specification of input arguments.
Examples
--------
>>> # doing forward by specifying data
>>> $texec->forward(1, data => $mydata);
>>> # doing forward by not specifying things, but copy to the executor before hand
>>> $mydata->copyto($texec->arg_dict->{'data'});
>>> $texec->forward(1);
>>> # doing forward by specifying data and get outputs
>>> my $outputs = $texec->forward(1, data => $mydata);
>>> print $outputs->[0]->aspdl;
backward
Do a backward pass to get the gradient of the arguments.
Parameters
----------
$out_grads : NDArray or an array ref of NDArrays or hash ref of NDArrays, optional.
The gradient on the outputs to be propagated back.
This parameter is only needed when bind is called
on outputs that are not a loss function.
$is_train : Bool, default 1
Whether this backward is for training or inference. Note that in rare
cases you want to call backward with is_train=0 to get gradient
during inference.
set_monitor_callback
Install callback.
Parameters
----------
$callback : CodeRef
Takes a string and an NDArrayHandle.
arg_dict
Get a hash ref representation of the argument arrays.
Returns
-------
$arg_dict : HashRef[AI::MXNet::NDArray]
The map that maps a name of the arguments to the NDArrays.
grad_dict
Get a hash ref representation of the gradient arrays.
Returns
-------
$grad_dict : HashRef[AI::MXNet::NDArray]
The map that maps a name of the arguments to the gradient NDArrays.
aux_dict
Get a hash ref representation of the auxiliary states arrays.
Returns
-------
$aux_dict : HashRef[AI::MXNet::NDArray]
The map that maps a name of the auxiliary states to the NDArrays.
output_dict
Get a hash ref representation of the output arrays.
Returns
-------
$output_dict : HashRef[AI::MXNet::NDArray]
The map that maps a name of the outputs to the NDArrays.
copy_params_from
Copy parameters from arg_params, aux_params into the executor's internal array.
Parameters
----------
$arg_params : HashRef[AI::MXNet::NDArray]
Parameters, hash ref of name to NDArray of arguments
$aux_params= : Maybe[HashRef[AI::MXNet::NDArray]], optional
Parameters, hash ref of name to NDArray of auxiliary states.
$allow_extra_params= : Bool, optional
Whether to allow extra parameters that are not needed by symbol
If this is True, no error will be thrown when arg_params or aux_params
contain extra parameters that is not needed by the executor.
reshape
Returns new executor with the same symbol and shared memory,
but different input/output shapes.
For runtime reshaping, variable length sequences, etc.
The returned executor shares state with the current one,
and cannot be used in parallel with it.
Parameters
----------
$kwargs : HashRef[Shape]
new shape for arguments.
:$partial_shaping : Bool
Whether to allow changing the shape of unspecified arguments.
:$allow_up_sizing : Bool
Whether to allow allocating new ndarrays that's larger than the original.
Returns
-------
$exec : AI::MXNet::Executor
A new executor that shares memory with self.
debug_str
A debug string about the internal execution plan.
Returns
-------
$debug_str : Str
Debug string of the executor.