#include <Pad.h>

Collaboration diagram for luci_interpreter::kernels::Pad:

Public Member Functions
	Pad (const Tensor input, const Tensor paddings, Tensor *output)

const Tensor *	input () const

const Tensor *	paddings () const

Tensor *	output () 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 27 of file Pad.h.

Constructor & Destructor Documentation

◆ Pad()

luci_interpreter::kernels::Pad::Pad	(	const Tensor *	input,
		const Tensor *	paddings,
		Tensor *	output
	)

Definition at line 30 of file Pad.cpp.

  : Kernel({input, paddings}, {output})
{
}

References input(), and paddings().

Member Function Documentation

◆ configure()

void luci_interpreter::kernels::Pad::configure ( )

overridevirtual

Implements luci_interpreter::Kernel.

Definition at line 35 of file Pad.cpp.

{
  const Shape &input_shape = input()->shape();
  const int num_dims = input_shape.num_dims();
 
  if (num_dims > 4)
    throw std::runtime_error("Unsupported number of dimensions.");
 
  assert(output()->element_type() == input()->element_type());
  assert(paddings()->element_type() == DataType::S32);
  // Paddings shape should be [N, 2].
  assert(paddings()->shape().num_dims() == 2);
  assert(paddings()->shape().dim(0) == num_dims);
  assert(paddings()->shape().dim(1) == 2);
 
  Shape output_shape(num_dims);
  const auto *paddings_data = getTensorData<int32_t>(paddings());
  for (int i = 0; i < num_dims; ++i)
  {
    const int32_t padding_before = paddings_data[i * 2];
    const int32_t padding_after = paddings_data[i * 2 + 1];
    assert(padding_before >= 0 && padding_after >= 0);
    output_shape.dim(i) = input_shape.dim(i) + padding_before + padding_after;
  }
 
  output()->resize(output_shape);
}

References luci_interpreter::Shape::dim(), input(), luci_interpreter::Shape::num_dims(), output(), output_shape, paddings(), luci_interpreter::Tensor::resize(), and luci_interpreter::Tensor::shape().

◆ execute()

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

overridevirtual

Implements luci_interpreter::Kernel.

Definition at line 63 of file Pad.cpp.

{
  const int num_dims = input()->shape().num_dims();
 
  tflite::PadParams params{};
  params.left_padding_count = num_dims;
  params.right_padding_count = num_dims;
 
  const auto *paddings_data = getTensorData<int32_t>(paddings());
  for (int i = num_dims - 1; i >= 0; --i)
  {
    params.left_padding[i] = paddings_data[i * 2];
    params.right_padding[i] = paddings_data[i * 2 + 1];
  }
 
  switch (input()->element_type())
  {
    case DataType::FLOAT32:
    {
      const float pad_value = 0.0f;
      tflite::reference_ops::Pad(params, getTensorShape(input()), getTensorData<float>(input()),
                                 &pad_value, getTensorShape(output()),
                                 getTensorData<float>(output()));
      break;
    }
    case DataType::U8:
    {
      assert(output()->zero_point() >= std::numeric_limits<uint8_t>::min());
      assert(output()->zero_point() <= std::numeric_limits<uint8_t>::max());
      const auto pad_value = static_cast<uint8_t>(output()->zero_point());
      tflite::reference_ops::Pad(params, getTensorShape(input()), getTensorData<uint8_t>(input()),
                                 &pad_value, getTensorShape(output()),
                                 getTensorData<uint8_t>(output()));
      break;
    }
    case DataType::S8:
    {
      assert(output()->zero_point() >= std::numeric_limits<int8_t>::min());
      assert(output()->zero_point() <= std::numeric_limits<int8_t>::max());
      const auto pad_value = static_cast<int8_t>(output()->zero_point());
      tflite::reference_ops::Pad(params, getTensorShape(input()), getTensorData<int8_t>(input()),
                                 &pad_value, getTensorShape(output()),
                                 getTensorData<int8_t>(output()));
      break;
    }
    default:
      throw std::runtime_error("luci-intp Pad Unsupported type.");
  }
}