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

        symbol(s) to run the consistency test
    ctx_list : list
        running context. See example for more detail.
    scale : float, optional
        standard deviation of the inner normal distribution. Used in initialization
    grad_req : str or list of str or dict of str to str
        gradient requirement.
=cut

my %dtypes = (
    float32 => 0,
    float64 => 1,
    float16 => 2,
    uint8   => 3,
    int32   => 4
);

func check_consistency(
    SymbolOrArrayOfSymbols              :$sym,
    ArrayRef                            :$ctx_list,
    Num                                 :$scale=1,
    Str|ArrayRef[Str]|HashRef[Str]      :$grad_req='write',
    Maybe[HashRef[AI::MXNet::NDArray]]  :$arg_params=,
    Maybe[HashRef[AI::MXNet::NDArray]]  :$aux_params=,
    Maybe[HashRef[Num]|Num]             :$tol=,
    Bool                                :$raise_on_err=1,
    Maybe[AI::MXNer::NDArray]           :$ground_truth=
)
{
    $tol //= {
        float16 => 1e-1,
        float32 => 1e-3,
        float64 => 1e-5,
        uint8   => 0,
        int32   => 0
    };
    $tol = {
        float16 => $tol,
        float32 => $tol,
        float64 => $tol,
        uint8   => $tol,
        int32   => $tol
    } unless ref $tol;

    Test::More::ok(@$ctx_list > 1);
    if(blessed $sym)
    {
        $sym = [($sym)x@$ctx_list];
    }
    else
    {
        Test::More::ok(@$sym == @$ctx_list);
    }
    my $output_names = $sym->[0]->list_outputs;
    my $arg_names    = $sym->[0]->list_arguments;
    my @exe_list;
    zip(sub {
        my ($s, $ctx) = @_;
        Test::More::is_deeply($s->list_arguments, $arg_names);
        Test::More::is_deeply($s->list_outputs, $output_names);
        push @exe_list, $s->simple_bind(grad_req=>$grad_req, %$ctx);
    }, $sym, $ctx_list);
    $arg_params //= {};
    $aux_params //= {};
    my %arg_dict = %{ $exe_list[0]->arg_dict };
    while(my ($n, $arr) = each %arg_dict)
    {
        if(not exists $arg_params->{$n})
        {
            $arg_params->{$n} = random(reverse @{ $arr->shape })*$scale;
        }
    }
    my %aux_dict = %{ $exe_list[0]->aux_dict };
    while(my ($n, $arr) = each %aux_dict)
    {
        if(not exists $aux_params->{$n})
        {
            $aux_params->{$n} = 0;
        }
    }
    for my $exe(@exe_list)
    {
        %arg_dict = %{ $exe->arg_dict };
        while(my ($name, $arr) = each %arg_dict)
        {
            $arr .= $arg_params->{$name};
        }
        %aux_dict = %{ $exe->aux_dict };
        while(my ($name, $arr) = each %aux_dict)
        {
            $arr .= $aux_params->{$name};
        }
    }
    my @dtypes = map { $_->outputs->[0]->dtype } @exe_list;
    my $max_idx = pdl(map { $dtypes{$_} } @dtypes)->maximum_ind;
    my $gt = $ground_truth;
    if(not defined $gt)
    {
        $gt = { %{ $exe_list[$max_idx]->output_dict } };
        if($grad_req ne 'null')
        {
            %{$gt} = (%{$gt}, %{ $exe_list[$max_idx]->grad_dict });
        }
    }

    # test
    for my $exe (@exe_list)
    {
        $exe->forward(0);
    }
    enumerate(sub {
        my ($i, $exe) = @_;
        if($i == $max_idx)
        {
            return;
        }
        zip(sub {
            my ($name, $arr) = @_;
            my $gtarr = $gt->{$name}->astype($dtypes[$i])->aspdl;
            $arr = $arr->aspdl;
            Test::More::ok(