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package AI::TensorFlow::Libtensorflow::Tensor;
# ABSTRACT: A multi-dimensional array of elements of a single data type
$AI::TensorFlow::Libtensorflow::Tensor::VERSION = '0.0.7';
use strict;
use warnings;
use namespace::autoclean;
use AI::TensorFlow::Libtensorflow::Lib qw(arg);
use FFI::Platypus::Closure;
use FFI::Platypus::Buffer qw(window);
use List::Util qw(product);

my $ffi = AI::TensorFlow::Libtensorflow::Lib->ffi;
$ffi->mangler(AI::TensorFlow::Libtensorflow::Lib->mangler_default);

$ffi->load_custom_type('AI::TensorFlow::Libtensorflow::Lib::FFIType::TFPtrSizeScalarRef'
	=> 'tf_tensor_buffer'
);



$ffi->attach( [ 'NewTensor' => 'New' ] =>
	[
		arg 'TF_DataType' => 'dtype',

		# const int64_t* dims, int num_dims
		arg 'tf_dims_buffer'   => [ qw(dims num_dims) ],

		# void* data, size_t len
		arg 'tf_tensor_buffer' => [ qw(data len) ],

		arg 'opaque'      => 'deallocator',  # tensor_deallocator_t (deallocator)
		arg 'opaque'      => 'deallocator_arg',
	],
	=> 'TF_Tensor' => sub {
		my ($xs, $class,
			$dtype, $dims, $data,
			$deallocator, $deallocator_arg,
		) = @_;
		my $deallocator_closure = $ffi->closure( $deallocator );
		$deallocator_closure->sticky;
		my $deallocator_ptr = $ffi->cast(
			'tensor_deallocator_t', 'opaque',
			$deallocator_closure );

		my $obj = $xs->(
			$dtype,
			$dims,
			$data,
			$deallocator_ptr, $deallocator_arg,
		);

		# Return early if no TF_Tensor created
		# TODO should this throw an exception instead?
		return unless $obj;

		$obj->{_deallocator_closure} = $deallocator_closure;

		$obj;
	});


# C: TF_AllocateTensor
#
# Constructor
$ffi->attach( [ 'AllocateTensor', 'Allocate' ],
	[
		arg 'TF_DataType'     => 'dtype',
		arg 'tf_dims_buffer'  => [ qw(dims num_dims) ],
		arg 'size_t'          => 'len',
	],
	=> 'TF_Tensor' => sub {
		my ($xs, $class, @rest) = @_;
		my ($dtype, $dims, $len) = @rest;
		if( ! defined $len ) {
			$len = product($dtype->Size, @$dims);
		}
		my $obj = $xs->($dtype, $dims, $len);
	}
);

$ffi->attach( [ 'DeleteTensor' => 'DESTROY' ],
	[ arg 'TF_Tensor' => 't' ]
	=> 'void'
	=> sub {
		my ($xs, $self) = @_;
		$xs->($self);
		if( exists $self->{_deallocator_closure} ) {
			$self->{_deallocator_closure}->unstick;
		}
	}
);

$ffi->attach( [ 'TensorData' => 'Data' ],
	[ arg 'TF_Tensor' => 'self' ],
	=> 'opaque'
	=> sub {
		my ($xs, @rest) = @_;
		my ($self) = @rest;
		my $data_p = $xs->(@rest);
		window(my $buffer, $data_p, $self->ByteSize);
		\$buffer;
	}
);

$ffi->attach( [ 'TensorByteSize' => 'ByteSize' ],
	[ arg 'TF_Tensor' => 'self' ],
	=> 'size_t'
);

$ffi->attach( [ 'TensorType' => 'Type' ],
	[ arg 'TF_Tensor' => 'self' ],
	=> 'TF_DataType'
);

$ffi->attach( [ 'NumDims' => 'NumDims' ],
	[ arg 'TF_Tensor' => 'self' ],
	=> 'int',
);

$ffi->attach( [ 'TensorElementCount' => 'ElementCount' ] =>
	[ arg 'TF_Tensor' => 'self' ]
	=> 'int64_t'
);

$ffi->attach( [ 'Dim' => 'Dim' ],
	[
		arg 'TF_Tensor' => 't',
		arg 'int'       => 'dim_index',
	],
	=> 'int64_t',
);

$ffi->attach(  [ 'TensorMaybeMove' => 'MaybeMove' ] =>
	[ arg 'TF_Tensor' => 'self' ],
	=> 'TF_Tensor',
);

$ffi->attach( ['TensorIsAligned' => 'IsAligned'] => [
	arg TF_Tensor => 't'
] => 'bool' );

eval {# TF v2.10.0
$ffi->attach(  [ 'SetShape' => 'SetShape' ] =>
	[
		arg 'TF_Tensor' => 'self',
		arg 'tf_dims_buffer'   => [ qw(dims num_dims) ],
	]
	=> 'void'
);
};

$ffi->attach( [  'TensorBitcastFrom' => 'BitcastFrom' ] => [
	arg TF_Tensor => 'from',
	arg TF_DataType => 'type',
	arg TF_Tensor => 'to',
	arg 'tf_dims_buffer'   => [ qw(new_dims num_new_dims) ],
	arg TF_Status => 'status',
] => 'void' );

#### Array helpers ####
use FFI::C::ArrayDef;
use FFI::C::StructDef;
my $adef = FFI::C::ArrayDef->new(
	$ffi,
	name => 'TF_Tensor_array',
	members => [
		FFI::C::StructDef->new(
			$ffi,
			members => [
				p => 'opaque'
			]
		)
	],
);
sub _adef {
	$adef;
}
sub _as_array {
	my $class = shift;
	my $array = $class->_adef->create(0 + @_);
	for my $idx (0..@_-1) {
		next unless defined $_[$idx];
		$array->[$idx]->p($ffi->cast('TF_Tensor', 'opaque', $_[$idx]));
	}
	$array;
}
sub _from_array {
	my ($class, $array) = @_;
	return [
		map {
			$ffi->cast(
				'opaque',
				'TF_Tensor',
				$array->[$_]->p)
		} 0.. $array->count - 1
	]
}

#### Data::Printer ####
sub _data_printer {
	my ($self, $ddp) = @_;

	my @data = (
		[ Type => $ddp->maybe_colorize( $self->Type, 'class' ), ],
		[ Dims =>  sprintf "%s %s %s",
				$ddp->maybe_colorize('[', 'brackets'),
				join(" ",
					map $ddp->maybe_colorize( $self->Dim($_), 'number' ),
						0..$self->NumDims-1),
				$ddp->maybe_colorize(']', 'brackets'),
		],
		[ NumDims => $ddp->maybe_colorize( $self->NumDims, 'number' ), ],