#include <Split.h>

Collaboration diagram for luci_interpreter::kernels::Split:

Public Member Functions
	Split (const Tensor axis, const Tensor input, std::vector< Tensor * > outputs)

const Tensor *	axis () const

const Tensor *	input () const

Tensor *	output (int index) const

void	configure () override

void	execute () const override

Public Member Functions inherited from luci_interpreter::Kernel
virtual	~Kernel ()=default

const std::vector< const Tensor * > &	getInputTensors () const

const std::vector< Tensor * > &	getOutputTensors () const

Additional Inherited Members
Protected Member Functions inherited from luci_interpreter::Kernel
	Kernel (std::vector< const Tensor * > inputs, std::vector< Tensor * > outputs)

Protected Attributes inherited from luci_interpreter::Kernel
const std::vector< const Tensor * >	_inputs

const std::vector< Tensor * >	_outputs

Detailed Description

Definition at line 28 of file Split.h.

Constructor & Destructor Documentation

◆ Split()

luci_interpreter::kernels::Split::Split	(	const Tensor *	axis,
		const Tensor *	input,
		std::vector< Tensor * >	outputs
	)

Definition at line 28 of file Split.cpp.

  : Kernel({axis, input}, std::move(outputs))
{
}

References axis(), and input().

Member Function Documentation

◆ axis()

const Tensor * luci_interpreter::kernels::Split::axis ( ) const

inline

Definition at line 33 of file Split.h.

33{ return _inputs[0]; }

luci_interpreter::Kernel::_inputs

const std::vector< const Tensor * > _inputs

Definition Kernel.h:52

References luci_interpreter::Kernel::_inputs.

Referenced by onert.experimental.train.metrics.categorical_accuracy.CategoricalAccuracy::__init__(), configure(), Split(), and onert.experimental.train.metrics.categorical_accuracy.CategoricalAccuracy::update_state().

◆ configure()

void luci_interpreter::kernels::Split::configure ( )

overridevirtual

Implements luci_interpreter::Kernel.

Definition at line 33 of file Split.cpp.

{
  assert(axis()->shape().num_elements() == 1);
  _axis_value = getTensorData<int32_t>(axis())[0];
  if (_axis_value < 0)
    _axis_value += input()->shape().num_dims();
  assert(_axis_value >= 0 && _axis_value < input()->shape().num_dims());
 
  const int32_t input_size = input()->shape().dim(_axis_value);
  assert(input_size % _outputs.size() == 0);
  const int32_t slice_size = input_size / _outputs.size();
 
  Shape output_shape = input()->shape();
  output_shape.dim(_axis_value) = slice_size;
  for (Tensor *output : _outputs)
  {
    output->resize(output_shape);
  }
}

References luci_interpreter::Kernel::_outputs, axis(), luci_interpreter::Shape::dim(), input(), luci::must_cast(), luci_interpreter::Shape::num_dims(), output(), output_shape, luci_interpreter::Tensor::resize(), and luci_interpreter::Tensor::shape().

◆ execute()

void luci_interpreter::kernels::Split::execute ( ) const

overridevirtual

Implements luci_interpreter::Kernel.

Definition at line 53 of file Split.cpp.

{
  tflite::SplitParams params{};
  params.num_split = _outputs.size();
  params.axis = _axis_value;
 
#define TF_LITE_SPLIT(scalar)                                                                    \
  {                                                                                              \
    VectorOfTensors<scalar, false> all_outputs(_outputs);                                        \
    luci_interpreter_pal::Split(params, getTensorShape(input()), getTensorData<scalar>(input()), \
                                all_outputs.shapes(), all_outputs.data());                       \
  }
 
  switch (input()->element_type())
  {
    case DataType::FLOAT32:
      TF_LITE_SPLIT(float);
      break;
    case DataType::U8:
      TF_LITE_SPLIT(uint8_t);
      break;
    default:
      throw std::runtime_error("luci-intp Split Unsupported type.");
  }
#undef TF_LITE_SPLIT
}