NAME

    AI::MXNet::Gluon::Parameter - A Container holding parameters (weights) of AI::MXNEt::Gluon::Block(s).

DESCRIPTION

    AI::MXNet::Gluon::Parameter holds a copy of the parameter on each AI::MXNet::Context after
    it is initialized with AI::MXNet::Gluon::Parameter->initialize(...)`. If grad_req is
    not 'null', it will also hold a gradient array on each AI::MXNet::Context

        $ctx = mx->gpu(0);
        $x = mx->nd->zeros([16, 100], ctx=>$ctx);
        $w = mx->gluon->Parameter('fc_weight', shape=>[64, 100], init=>mx->init->Xavier());
        $b = mx->gluon->Parameter('fc_bias', shape=>[64], init=>mx->init->Zero());
        $w->initialize(ctx=>$ctx);
        $b->initialize(ctx=>ctx);
        $out = mx->nd->FullyConnected($x, $w->data($ctx), $b->data($ctx), num_hidden=>64);

    Parameters
    ----------
    name : str
        Name of this parameter.
    grad_req : {'write', 'add', 'null'}, default 'write'
        Specifies how to update gradient to grad arrays.

        - 'write' means everytime gradient is written to grad NDArray.
        - 'add' means everytime gradient is added to the grad NDArray. You need
          to manually call zero_grad() to clear the gradient buffer before each
          iteration when using this option.
        - 'null' means gradient is not requested for this parameter. gradient arrays
          will not be allocated.
    shape : array ref of int or int, default undef
        Shape of this parameter. By default shape is not specified. Parameter with
        unknown shape can be used for `Symbol` API, but `init` will throw an error
        when using `NDArray` API.
    dtype : Dtype, default 'float32'
        Data type of this parameter. For example, 'float64'.
    lr_mult : float, default 1.0
        Learning rate multiplier. Learning rate will be multiplied by lr_mult
        when updating this parameter with optimizer.
    wd_mult : float, default 1.0
        Weight decay multiplier (L2 regularizer coefficient). Works similar to lr_mult.
    init : Initializer, default None
        Initializer of this parameter. Will use the global initializer by default.
    stype: {'default', 'row_sparse', 'csr'}, defaults to 'default'.
        The storage type of the parameter.
    grad_stype: {'default', 'row_sparse', 'csr'}, defaults to 'default'.
        The storage type of the parameter's gradient.


    Attributes
    ----------
    grad_req : {'write', 'add', 'null'}
        This can be set before or after initialization. Setting grad_req to null
        with $x->grad_req = 'null' saves memory and computation when you don't
        need gradient w.r.t x.

initialize

        Initializes parameter and gradient arrays. Only used for `NDArray` API.

        Parameters
        ----------
        :$init : Initializer
            The initializer to use. Overrides AI::MXNet::Gluon::Parameter->init and default_init.
        :$ctx : AI::MXNet::Context or array ref of AI::MXNet::Context, defaults to AI::MXNet::Context->current_ctx().
            Initialize Parameter on given context. If ctx is a list of Context, a
            copy will be made for each context.
            Copies are independent arrays. User is responsible for keeping
            their values consistent when updating. Normally gluon->Trainer does this for you.
        :$default_init : Initializer
            Default initializer is used when both 'init' and AI::MXNet::Gluon::Parameter->init are undefined.
        :$force_reinit : bool, default False
            Whether to force re-initialization if parameter is already initialized.

        Examples
        --------
        >>> $weight = mx->gluon->Parameter('weight', shape=>[2, 2]);
        >>> $weight->initialize(ctx=>mx->cpu(0));
        >>> print $weight->data
        [[-0.01068833  0.01729892]
         [ 0.02042518 -0.01618656]]
        <NDArray 2x2 @cpu(0)>
        >>> print $weight->grad()
        [[ 0.  0.]
         [ 0.  0.]]
        <NDArray 2x2 @cpu(0)>
        >>> $weight->initialize(ctx=>[mx->gpu(0), mx->gpu(1)]);
        >>> print $weight->data(mx->gpu(0));
        [[-0.00873779 -0.02834515]
         [ 0.05484822 -0.06206018]]
        <NDArray 2x2 @gpu(0)>
        >>> print $weight->data(mx->gpu(1))
        [[-0.00873779 -0.02834515]
         [ 0.05484822 -0.06206018]]
        <NDArray 2x2 @gpu(1)>

reset_ctx

        Re-assign Parameter to other contexts.

        :$ctx : AI::MXNet::Context or array ref of AI::MXNet::Context, default AI::MXNet::Context->current_ctx.
        Assign Parameter to given context. If ctx is a list of Context, a
        copy will be made for each context.

set_data

    Sets this parameter's value on all contexts to data.

row_sparse_data

        Returns a copy of the 'row_sparse' parameter on the same context as row_id's.
        The copy only retains rows whose ids occur in provided row ids.
        The parameter must have been initialized on this context before.

        Parameters
        ----------
        $row_id: AI::MXNet::NDArray
            Row ids to retain for the 'row_sparse' parameter.

        Returns
        -------
        AI::MXNet::NDArray on row_id's context

list_row_sparse_data

        Returns copies of the 'row_sparse' parameter on all contexts, in the same order
        as creation. The copy only retains rows whose ids occur in provided row ids.
        The parameter must have been initialized before.

        Parameters
        ----------
        $row_id: AI::MXNet::NDArray
            Row ids to retain for the 'row_sparse' parameter.

        Returns
        -------
        array ref of AI::MXNet::NDArrays

data

        Returns a copy of this parameter on one context. Must have been
        initialized on this context before. For sparse parameters, use
        row_sparse_data instead.

        Parameters
        ----------
        ctx : Context
            Desired context.

        Returns
        -------
        NDArray on ctx

list_data

        Returns copies of this parameter on all contexts, in the same order
        as creation. For sparse parameters, use list_row_sparse_data
        instead.

grad

        Returns a gradient buffer for this parameter on one context.

        Parameters
        ----------
        ctx : Context
            Desired context.

list_grad

        Returns gradient buffers on all contexts, in the same order
        as 'values'.

list_ctx

        Returns a list of contexts this parameter is initialized on.

zero_grad

        Sets gradient buffer on all contexts to 0. No action is taken if
        parameter is uninitialized or doesn't require gradient.

var

        Returns a symbol representing this parameter.

cast

    Cast data and gradient of this Parameter to a new data type.

    Parameters
     ----------
    $dtype : Dtype
    The new data type.

NAME

    AI::MXNet::Gluon::Constant - A constant parameter for holding immutable tensors.

DESCRIPTION

    A constant parameter for holding immutable tensors.
    Constants are ignored by autograd and Trainer, thus their values
    will not change during training. But you can still update their values
    manually with the set_data method.

    Constants can be created with either

        $const = mx->gluon->Constant('const', [[1,2],[3,4]]);

    or

        package Block;
        use AI::MXNet::Gluon::Mouse;
        extends 'AI::MXNet::Gluon::Block';
        sub BUILD
        {
            $self->const($self->params->get_constant('const', [[1,2],[3,4]]));
        }

    Constructor Attributes
    ----------
    name : str
        Name of the parameter.
    value : AcceptableInput (perl array, pdl, ndarray, etc)
        Initial value for the constant.

NAME

    AI::MXNet::Gluon::ParameterDict - A dictionary managing a set of parameters.

DESCRIPTION

    Parameters
    ----------
    prefix : str, default ''
        The prefix to be prepended to all Parameters' names created by this dict.
    shared : ParameterDict or undef
        If not undef, when this dict's `get` method creates a new parameter, will
        first try to retrieve it from `shared` dict. Usually used for sharing
        parameters with another `Block`.

get

        Retrieves a 'AI::MXNet::Gluon::Parameter' with name '$self->prefix.$name'. If not found,
        'get' will first try to retrieve it from 'shared' dict. If still not
        found, 'get' will create a new 'AI::MXNet::Gluon::Parameter' with key-word arguments and
        insert it to self.

        Parameters
        ----------
        name : str
            Name of the desired Parameter. It will be prepended with this dictionary's
            prefix.
        %kwargs : hash
            The rest of key-word arguments for the created `Parameter`.

        Returns
        -------
        Parameter
            The created or retrieved `Parameter`.

update

    Copies all Parameters in $other to self.

get_constant

        Retrieves AI::MXNet::Gluon::Constant with name $self->prefix.$name. If not found,
        'get' will first try to retrieve it from "shared" dictionary. If still not
        found, 'get' will create a new Constant with key-word
        arguments and insert it to self.

        Parameters
        ----------
        name : str
            Name of the desired Constant. It will be prepended with this dictionary's
            prefix.
        value : array-like
            Initial value of constant.

        Returns
        -------
        Constant
            The created or retrieved Constant.

initialize

        Initializes all Parameters managed by this dictionary to be used for 'NDArray'
        API. It has no effect when using 'Symbol' API.

        Parameters
        ----------
        :$init : Initializer
            Global default Initializer to be used when AI::MXNet::Gluon::Parameter->init is undef.
            Otherwise, AI::MXNet::Gluon::Parameter->init takes precedence.
        :$ctx : AI::MXNet::Context or array ref of AI::MXNet::Context objects
            Keeps a copy of Parameters on one or many context(s).
        :$force_reinit : bool, default False
            Whether to force re-initialization if parameter is already initialized.
        :$verbose : bool, default False
            Whether to force re-initialization if parameter is already initialized.

zero_grad

    Sets all Parameters' gradient buffer to 0.

reset_ctx

    Re-assign all Parameters to other contexts.

    $ctx : AI::MXNet::Context or array ref of AI::MXNet::Context objects, defaults to AI::MXNet::Context->current_ctx().
            Assign Parameter to given context. If $ctx is an array ref of AI::MXNet::Context objects, a
            copy will be made for each context.

setattr

        Set an attribute to a new value for all Parameters.

        For example, set grad_req to null if you don't need gradient w.r.t a
        model's Parameters::

            $model->collect_params()->setattr(grad_req => 'null');

        or change the learning rate multiplier::

            $model->collect_params()->setattr(lr_mult => 0.5);

        Parameters
        ----------
        $name : str
            Name of the attribute.
        $value : valid type for attribute name
            The new value for the attribute.

save

    Save parameters to file.

    $filename : str
        Path to parameter file.
    $strip_prefix : str, default ''
    Strip prefix from parameter names before saving.

        Load parameters from file.

        $filename : str
            Path to parameter file.
        :$ctx : AI::MXNet::Context or array ref of AI::MXNet::Context objects
            Context(s) initialize loaded parameters on.
        :$allow_missing : bool, default False
            Whether to silently skip loading parameters not represents in the file.
        :$ignore_extra : bool, default False
            Whether to silently ignore parameters from the file that are not
            present in this ParameterDict.
        :$restore_prefix : str, default ''
            prepend prefix to names of stored parameters before loading.