Compute Library
 21.02
CLAbsoluteDifferenceKernel Class Reference

Interface for the absolute difference kernel. More...

#include <CLAbsoluteDifferenceKernel.h>

Collaboration diagram for CLAbsoluteDifferenceKernel:
[legend]

Public Member Functions

 CLAbsoluteDifferenceKernel ()
 Default constructor. More...
 
 CLAbsoluteDifferenceKernel (const CLAbsoluteDifferenceKernel &)=delete
 Prevent instances of this class from being copied (As this class contains pointers) More...
 
CLAbsoluteDifferenceKerneloperator= (const CLAbsoluteDifferenceKernel &)=delete
 Prevent instances of this class from being copied (As this class contains pointers) More...
 
 CLAbsoluteDifferenceKernel (CLAbsoluteDifferenceKernel &&)=default
 Allow instances of this class to be moved. More...
 
CLAbsoluteDifferenceKerneloperator= (CLAbsoluteDifferenceKernel &&)=default
 Allow instances of this class to be moved. More...
 
 ~CLAbsoluteDifferenceKernel ()=default
 Default destructor. More...
 
void configure (const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output)
 Set the inputs and output images. More...
 
void configure (const CLCompileContext &compile_context, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output)
 Set the inputs and output images. More...
 
void run (const Window &window, cl::CommandQueue &queue) override
 Enqueue the OpenCL kernel to process the given window on the passed OpenCL command queue. More...
 
- Public Member Functions inherited from ICLKernel
 ICLKernel ()
 Constructor. More...
 
cl::Kernel & kernel ()
 Returns a reference to the OpenCL kernel of this object. More...
 
template<typename T >
void add_1D_array_argument (unsigned int &idx, const ICLArray< T > *array, const Strides &strides, unsigned int num_dimensions, const Window &window)
 Add the passed 1D array's parameters to the object's kernel's arguments starting from the index idx. More...
 
void add_1D_tensor_argument (unsigned int &idx, const ICLTensor *tensor, const Window &window)
 Add the passed 1D tensor's parameters to the object's kernel's arguments starting from the index idx. More...
 
void add_1D_tensor_argument_if (bool cond, unsigned int &idx, const ICLTensor *tensor, const Window &window)
 Add the passed 1D tensor's parameters to the object's kernel's arguments starting from the index idx if the condition is true. More...
 
void add_2D_tensor_argument (unsigned int &idx, const ICLTensor *tensor, const Window &window)
 Add the passed 2D tensor's parameters to the object's kernel's arguments starting from the index idx. More...
 
void add_2D_tensor_argument_if (bool cond, unsigned int &idx, const ICLTensor *tensor, const Window &window)
 Add the passed 2D tensor's parameters to the object's kernel's arguments starting from the index idx if the condition is true. More...
 
void add_3D_tensor_argument (unsigned int &idx, const ICLTensor *tensor, const Window &window)
 Add the passed 3D tensor's parameters to the object's kernel's arguments starting from the index idx. More...
 
void add_4D_tensor_argument (unsigned int &idx, const ICLTensor *tensor, const Window &window)
 Add the passed 4D tensor's parameters to the object's kernel's arguments starting from the index idx. More...
 
virtual void run_op (ITensorPack &tensors, const Window &window, cl::CommandQueue &queue)
 Enqueue the OpenCL kernel to process the given window on the passed OpenCL command queue. More...
 
template<typename T >
void add_argument (unsigned int &idx, T value)
 Add the passed parameters to the object's kernel's arguments starting from the index idx. More...
 
void set_lws_hint (const cl::NDRange &lws_hint)
 Set the Local-Workgroup-Size hint. More...
 
cl::NDRange lws_hint () const
 Return the Local-Workgroup-Size hint. More...
 
void set_wbsm_hint (const cl_int &wbsm_hint)
 Set the workgroup batch size modifier hint. More...
 
cl_int wbsm_hint () const
 Return the workgroup batch size modifier hint. More...
 
const std::string & config_id () const
 Get the configuration ID. More...
 
void set_target (GPUTarget target)
 Set the targeted GPU architecture. More...
 
void set_target (cl::Device &device)
 Set the targeted GPU architecture according to the CL device. More...
 
GPUTarget get_target () const
 Get the targeted GPU architecture. More...
 
size_t get_max_workgroup_size ()
 Get the maximum workgroup size for the device the CLKernelLibrary uses. More...
 
template<unsigned int dimension_size>
void add_tensor_argument (unsigned &idx, const ICLTensor *tensor, const Window &window)
 
template<typename T , unsigned int dimension_size>
void add_array_argument (unsigned &idx, const ICLArray< T > *array, const Strides &strides, unsigned int num_dimensions, const Window &window)
 Add the passed array's parameters to the object's kernel's arguments starting from the index idx. More...
 
- Public Member Functions inherited from IKernel
 IKernel ()
 Constructor. More...
 
virtual ~IKernel ()=default
 Destructor. More...
 
virtual bool is_parallelisable () const
 Indicates whether or not the kernel is parallelisable. More...
 
virtual BorderSize border_size () const
 The size of the border for that kernel. More...
 
const Windowwindow () const
 The maximum window the kernel can be executed on. More...
 

Additional Inherited Members

- Static Public Member Functions inherited from ICLKernel
static constexpr unsigned int num_arguments_per_1D_array ()
 Returns the number of arguments enqueued per 1D array object. More...
 
static constexpr unsigned int num_arguments_per_1D_tensor ()
 Returns the number of arguments enqueued per 1D tensor object. More...
 
static constexpr unsigned int num_arguments_per_2D_tensor ()
 Returns the number of arguments enqueued per 2D tensor object. More...
 
static constexpr unsigned int num_arguments_per_3D_tensor ()
 Returns the number of arguments enqueued per 3D tensor object. More...
 
static constexpr unsigned int num_arguments_per_4D_tensor ()
 Returns the number of arguments enqueued per 4D tensor object. More...
 
static cl::NDRange gws_from_window (const Window &window)
 Get the global work size given an execution window. More...
 

Detailed Description

Interface for the absolute difference kernel.

Absolute difference is computed by:

\[ output(x,y) = | input1(x,y) - input2(x,y) | \]

Definition at line 38 of file CLAbsoluteDifferenceKernel.h.

Constructor & Destructor Documentation

◆ CLAbsoluteDifferenceKernel() [1/3]

Default constructor.

Definition at line 39 of file CLAbsoluteDifferenceKernel.cpp.

40  : _input1(nullptr), _input2(nullptr), _output(nullptr)
41 {
42 }

◆ CLAbsoluteDifferenceKernel() [2/3]

Prevent instances of this class from being copied (As this class contains pointers)

◆ CLAbsoluteDifferenceKernel() [3/3]

Allow instances of this class to be moved.

◆ ~CLAbsoluteDifferenceKernel()

Default destructor.

Member Function Documentation

◆ configure() [1/2]

void configure ( const ICLTensor input1,
const ICLTensor input2,
ICLTensor output 
)

Set the inputs and output images.

Parameters
[in]input1Source tensor. Data types supported: U8/S16.
[in]input2Source tensor. Data types supported: U8/S16.
[out]outputDestination tensor. Data types supported: U8/S16.

Definition at line 44 of file CLAbsoluteDifferenceKernel.cpp.

References CLKernelLibrary::get().

45 {
46  configure(CLKernelLibrary::get().get_compile_context(), input1, input2, output);
47 }
static CLKernelLibrary & get()
Access the KernelLibrary singleton.
void configure(const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output)
Set the inputs and output images.

◆ configure() [2/2]

void configure ( const CLCompileContext compile_context,
const ICLTensor input1,
const ICLTensor input2,
ICLTensor output 
)

Set the inputs and output images.

Parameters
[in]compile_contextThe compile context to be used.
[in]input1Source tensor. Data types supported: U8/S16.
[in]input2Source tensor. Data types supported: U8/S16.
[out]outputDestination tensor. Data types supported: U8/S16.

Definition at line 49 of file CLAbsoluteDifferenceKernel.cpp.

References ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN, ARM_COMPUTE_ERROR_ON_MSG, arm_compute::calculate_max_window(), arm_compute::create_kernel(), ITensorInfo::data_type(), arm_compute::get_cl_type_from_data_type(), ITensor::info(), arm_compute::intersect_valid_regions(), num_elems_processed_per_iteration, arm_compute::S16, arm_compute::U8, arm_compute::update_window_and_padding(), arm_compute::test::validation::valid_region, and ITensorInfo::valid_region().

50 {
54  ARM_COMPUTE_ERROR_ON_MSG(output->info()->data_type() == DataType::U8 && (input1->info()->data_type() != DataType::U8 || input2->info()->data_type() != DataType::U8),
55  "The output image can only be U8 if both input images are U8");
56 
57  _input1 = input1;
58  _input2 = input2;
59  _output = output;
60 
61  // Set kernel build options
62  std::set<std::string> build_opts;
63  build_opts.insert("-DDATA_TYPE_IN1=" + get_cl_type_from_data_type(input1->info()->data_type()));
64  build_opts.insert("-DDATA_TYPE_IN2=" + get_cl_type_from_data_type(input2->info()->data_type()));
65  build_opts.insert("-DDATA_TYPE_OUT=" + get_cl_type_from_data_type(output->info()->data_type()));
66 
67  // Create kernel
68  _kernel = create_kernel(compile_context, "absdiff", build_opts);
69 
70  // Configure kernel window
71  constexpr unsigned int num_elems_processed_per_iteration = 16;
72 
73  Window win = calculate_max_window(*input1->info(), Steps(num_elems_processed_per_iteration));
74 
78 
79  update_window_and_padding(win, input1_access, input2_access, output_access);
80 
82  input2->info()->valid_region());
83 
84  output_access.set_valid_region(win, valid_region);
85 
86  ICLKernel::configure_internal(win);
87 }
Window calculate_max_window(const ValidRegion &valid_region, const Steps &steps, bool skip_border, BorderSize border_size)
1 channel, 1 U8 per channel
virtual DataType data_type() const =0
Data type used for each element of the tensor.
const ValidRegion valid_region
Definition: Scale.cpp:221
virtual ValidRegion valid_region() const =0
Valid region of the tensor.
cl::Kernel create_kernel(const CLCompileContext &ctx, const std::string &kernel_name, const std::set< std::string > &build_opts=std::set< std::string >())
Creates an opencl kernel using a compile context.
Definition: CLHelpers.cpp:403
bool update_window_and_padding(Window &win, Ts &&... patterns)
Update window and padding size for each of the access patterns.
Definition: WindowHelpers.h:46
Class to describe a number of elements in each dimension.
Definition: Steps.h:40
#define ARM_COMPUTE_ERROR_ON_MSG(cond, msg)
Definition: Error.h:456
Implementation of a row access pattern.
std::string get_cl_type_from_data_type(const DataType &dt)
Translates a tensor data type to the appropriate OpenCL type.
Definition: CLHelpers.cpp:37
virtual ITensorInfo * info() const =0
Interface to be implemented by the child class to return the tensor&#39;s metadata.
ValidRegion intersect_valid_regions(const Ts &... regions)
Intersect multiple valid regions.
Definition: WindowHelpers.h:74
1 channel, 1 S16 per channel
#define ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(t, c,...)
Definition: Validate.h:790
unsigned int num_elems_processed_per_iteration
Container for valid region of a window.
Definition: Types.h:188
Describe a multidimensional execution window.
Definition: Window.h:39

◆ operator=() [1/2]

CLAbsoluteDifferenceKernel& operator= ( const CLAbsoluteDifferenceKernel )
delete

Prevent instances of this class from being copied (As this class contains pointers)

◆ operator=() [2/2]

Allow instances of this class to be moved.

◆ run()

void run ( const Window window,
cl::CommandQueue &  queue 
)
overridevirtual

Enqueue the OpenCL kernel to process the given window on the passed OpenCL command queue.

Note
The queue is not flushed by this method, and therefore the kernel will not have been executed by the time this method returns.
Parameters
[in]windowRegion on which to execute the kernel. (Must be a valid region of the window returned by window()).
[in,out]queueCommand queue on which to enqueue the kernel.

Reimplemented from ICLKernel.

Definition at line 89 of file CLAbsoluteDifferenceKernel.cpp.

References ICLKernel::add_2D_tensor_argument(), ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW, ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL, arm_compute::enqueue(), Window::first_slice_window_2D(), ICLKernel::lws_hint(), arm_compute::test::validation::reference::slice(), Window::slide_window_slice_2D(), and IKernel::window().

90 {
93 
95  do
96  {
97  unsigned int idx = 0;
98  add_2D_tensor_argument(idx, _input1, slice);
99  add_2D_tensor_argument(idx, _input2, slice);
100  add_2D_tensor_argument(idx, _output, slice);
101  enqueue(queue, *this, slice, lws_hint());
102  }
103  while(window.slide_window_slice_2D(slice));
104 }
Window first_slice_window_2D() const
First 2D slice of the window.
Definition: Window.h:283
const Window & window() const
The maximum window the kernel can be executed on.
Definition: IKernel.cpp:28
void enqueue(IGCKernel &kernel, const Window &window, const gles::NDRange &lws=gles::NDRange(1U, 1U, 1U))
Add the kernel to the command queue with the given window.
Definition: IGCKernel.cpp:41
cl::NDRange lws_hint() const
Return the Local-Workgroup-Size hint.
Definition: ICLKernel.h:276
bool slide_window_slice_2D(Window &slice) const
Slide the passed 2D window slice.
Definition: Window.h:323
#define ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(k)
Definition: Validate.h:941
void add_2D_tensor_argument(unsigned int &idx, const ICLTensor *tensor, const Window &window)
Add the passed 2D tensor&#39;s parameters to the object&#39;s kernel&#39;s arguments starting from the index idx...
Definition: ICLKernel.h:148
Describe a multidimensional execution window.
Definition: Window.h:39
#define ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(f, s)
Definition: Validate.h:205
SimpleTensor< T > slice(const SimpleTensor< T > &src, Coordinates starts, Coordinates ends)

The documentation for this class was generated from the following files: