The Perl Toolchain Summit needs more sponsors. If your company depends on Perl, please support this very important event.

NAME

    AI::MXNet::Gluon::Data::Sampler

DESCRIPTION

    Base class for samplers.

    All samplers should subclass AI::MXNet::Gluon::Data::Sampler 
    and define method 'len' and 'next'
    methods.

NAME

    AI::MXNet::Gluon::Data::Sampler::SequentialSampler

DESCRIPTION

    Samples elements from [0, length) sequentially.

    Parameters
    ----------
    length : int
        Length of the sequence.

NAME

    AI::MXNet::Gluon::Data::Sampler::RandomSampler

DESCRIPTION

    Samples elements from [0, length) randomly without replacement.

    Parameters
    ----------
    length : int
        Length of the sequence.

NAME

    AI::MXNet::Gluon::Data::Sampler::BatchSampler

DESCRIPTION

    Wraps over another AI::MXNet::Gluon::Data::Sampler and return mini-batches of samples.

    Parameters
    ----------
    sampler : AI::MXNet::Gluon::Data::Sampler
        The source Sampler.
    batch_size : int
        Size of mini-batch.
    last_batch : {'keep', 'discard', 'rollover'}
        Specifies how the last batch is handled if batch_size does not evenly
        divide sequence length.

        If 'keep', the last batch will be returned directly, but will contain
        less element than `batch_size` requires.

        If 'discard', the last batch will be discarded.

        If 'rollover', the remaining elements will be rolled over to the next
        iteration.

    Examples
    --------
    >>> $sampler = gluon->data->SequentialSampler(10)
    >>> $batch_sampler = gluon->data->BatchSampler($sampler, batch_size => 3, last_batch => 'keep');
    >>> @{ $batch_sampler }
    [[0, 1, 2], [3, 4, 5], [6, 7, 8], [9]]