#include <LogicalOr.h>

Collaboration diagram for luci_interpreter::kernels::LogicalOr:

Public Member Functions
	LogicalOr (const Tensor input1, const Tensor input2, Tensor *output)

const Tensor *	input1 () const

const Tensor *	input2 () 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 28 of file LogicalOr.h.

Constructor & Destructor Documentation

◆ LogicalOr()

luci_interpreter::kernels::LogicalOr::LogicalOr	(	const Tensor *	input1,
		const Tensor *	input2,
		Tensor *	output
	)

Definition at line 28 of file LogicalOr.cpp.

  : Kernel({input1, input2}, {output})
{
}

References input1(), and input2().

Member Function Documentation

◆ configure()

void luci_interpreter::kernels::LogicalOr::configure ( )

overridevirtual

Implements luci_interpreter::Kernel.

Definition at line 33 of file LogicalOr.cpp.

{
  LUCI_INTERPRETER_CHECK(input1()->element_type() == input2()->element_type());
  LUCI_INTERPRETER_CHECK(input1()->element_type() == DataType::BOOL);
  output()->resize(calculateShapeForBroadcast(input1()->shape(), input2()->shape()));
}

References luci_interpreter::kernels::calculateShapeForBroadcast(), input1(), input2(), LUCI_INTERPRETER_CHECK, output(), and luci_interpreter::Tensor::resize().

◆ execute()

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

overridevirtual

Implements luci_interpreter::Kernel.

Definition at line 40 of file LogicalOr.cpp.

{
  BinaryOpBroadcastSlow(getTensorShape(input1()), getTensorData<bool>(input1()),
                        getTensorShape(input2()), getTensorData<bool>(input2()),
                        getTensorShape(output()), getTensorData<bool>(output()),
                        [](bool x, bool y) { return x || y; });
}