AI-MXNet

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lib/AI/MXNet/Executor/Group.pm  view on Meta::CPAN

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        symbol with the same set of parameters (e.g. unrolled RNNs with different lengths).
        In this case the memory regions of the parameters will be shared.
    logger : Logger
        Default is AI::MXNet::Logging->get_logger.
    fixed_param_names: Maybe[ArrayRef[Str]]
        Indicate parameters to be fixed during training. Parameters in this array ref will not allocate
        space for gradient, nor do gradient calculation.
    grad_req : ArrayRef[GradReq]|HashRef[GradReq]|GradReq
        Requirement for gradient accumulation. Can be 'write', 'add', or 'null'
        (default to 'write').
        Can be specified globally (str) or for each argument (array ref, hash ref).
    state_names: Maybe[ArrayRef[Str]]
=cut
 
has 'symbol'            => (is => 'ro', isa => 'AI::MXNet::Symbol', required => 1);
has 'contexts'          => (is => 'ro', isa => 'ArrayRef[AI::MXNet::Context]', required => 1);
has 'workload'          => (is => 'ro', isa => 'ArrayRef[Num]', default => sub { [] });
has 'data_shapes'       => (is => 'rw', isa => 'ArrayRef[NameShape|AI::MXNet::DataDesc]', required => 1);
has 'label_shapes'      => (is => 'rw', isa => 'Maybe[ArrayRef[NameShape|AI::MXNet::DataDesc]]');
has 'param_names'       => (is => 'ro', isa => 'ArrayRef[Str]', required => 1);
has 'for_training'      => (is => 'ro', isa => 'Bool', required => 1);

lib/AI/MXNet/Module/Base.pm  view on Meta::CPAN

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    :$force_rebind=0 : Bool
        Default is 0. This function does nothing if the executors are already
        binded. But with this as 1, the executors will be forced to rebind.
    :$shared_module= : A subclass of AI::MXNet::Module::Base
        Default is undef. This is used in bucketing. When not undef, the shared module
        essentially corresponds to a different bucket -- a module with different symbol
        but with the same sets of parameters (e.g. unrolled RNNs with different lengths).
    :$grad_req='write' : Str|ArrayRef[Str]|HashRef[Str]
        Requirement for gradient accumulation. Can be 'write', 'add', or 'null'
        (defaults to 'write').
        Can be specified globally (str) or for each argument (array ref, hash ref).
=cut
 
method bind(
    ArrayRef[AI::MXNet::DataDesc]         $data_shapes,
    Maybe[ArrayRef[AI::MXNet::DataDesc]] :$label_shapes=,
    Bool                                 :$for_training=1,
    Bool                                 :$inputs_need_grad=0,
    Bool                                 :$force_rebind=0,
    Maybe[AI::MXNet::BaseModule]         :$shared_module=,
    Str|ArrayRef[Str]|HashRef[Str]       :$grad_req='write'

lib/AI/MXNet/Module/Bucketing.pm  view on Meta::CPAN

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        Default is 1.
    :$inputs_need_grad : Bool
        Default is 0.
    :$force_rebind : Bool
        Default is 0.
    :$shared_module : AI::MXNet::Module::Bucketing
        Default is undef. This value is currently not used.
    :$grad_req : str, array ref of str, hash ref of str to str
        Requirement for gradient accumulation. Can be 'write', 'add', or 'null'
        (defaults to 'write').
        Can be specified globally (str) or for each argument (array ref, hash ref).
    :$bucket_key : str
        bucket key for binding. by default is to use the ->default_bucket_key
=cut
 
method bind(
    ArrayRef[AI::MXNet::DataDesc|NameShape]                   :$data_shapes,
    Maybe[ArrayRef[AI::MXNet::DataDesc|NameShape]]            :$label_shapes=,
    Bool                                                      :$for_training=1,
    Bool                                                      :$inputs_need_grad=0,
    Bool                                                      :$force_rebind=0,

lib/AI/MXNet/Rtc.pm  view on Meta::CPAN

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        list of output names and ndarray
    kernel : str
        the actual kernel code.
        Note that this is only the body of the kernel, i.e.
        after { and before }. Rtc will decorate the kernel.
        For example, if name = "mykernel" and
        inputs = [('x', mx.nd.zeros((10,)))]
        outputs = [('y', mx.nd.zeros((10,)))]
        kernel = "y[threadIdx.x] = x[threadIdx.x];",
        the kernel that is compile will be:
        extern "C" __global__ mykernel(float *x, float *y) {
            const int x_ndim = 1;
            const int x_dims = { 10 };
            const int y_ndim = 1;
            const int y_dims = { 10 };
 
            y[threadIdx.x] = x[threadIdx.x];
        }
=cut
 
has 'handle'              => (is => 'rw', isa => 'RtcHandle', init_arg => undef);

t/test_symbol.t  view on Meta::CPAN

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  "inputs": [], 
  "backward_source_id": -1, 
  "attr": {"ctx_group": "stage2"}
}, 
{
  "op": "BatchNorm", 
  "param": {
    "eps": "0.001", 
    "fix_gamma": "True", 
    "momentum": "0.9", 
    "use_global_stats": "False"
  }, 
  "name": "batchnorm0", 
  "inputs": [[11, 0], [12, 0], [13, 0]], 
  "backward_source_id": -1, 
  "attr": {"ctx_group": "stage2"}
}, 
{
  "op": "null", 
  "param": {}, 
  "name": "softmax_label",