Compute Library
 21.02
CLNormalizePlanarYUVLayerKernel Class Reference

Interface for the NormalizePlanarYUV layer kernel. More...

#include <CLNormalizePlanarYUVLayerKernel.h>

Collaboration diagram for CLNormalizePlanarYUVLayerKernel:
[legend]

Public Member Functions

 CLNormalizePlanarYUVLayerKernel ()
 Constructor. More...
 
 CLNormalizePlanarYUVLayerKernel (const CLNormalizePlanarYUVLayerKernel &)=delete
 Prevent instances of this class from being copied (As this class contains pointers) More...
 
CLNormalizePlanarYUVLayerKerneloperator= (const CLNormalizePlanarYUVLayerKernel &)=delete
 Prevent instances of this class from being copied (As this class contains pointers) More...
 
 CLNormalizePlanarYUVLayerKernel (CLNormalizePlanarYUVLayerKernel &&)=default
 Default Move Constructor. More...
 
CLNormalizePlanarYUVLayerKerneloperator= (CLNormalizePlanarYUVLayerKernel &&)=default
 Default move assignment operator. More...
 
 ~CLNormalizePlanarYUVLayerKernel ()=default
 Default destructor. More...
 
void configure (const ICLTensor *input, ICLTensor *output, const ICLTensor *mean, const ICLTensor *std)
 Set the input and output tensors. More...
 
void configure (const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const ICLTensor *mean, const ICLTensor *std)
 Set the input and output tensors. 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...
 

Static Public Member Functions

static Status validate (const ITensorInfo *input, const ITensorInfo *output, const ITensorInfo *mean, const ITensorInfo *std)
 Static function to check if given info will lead to a valid configuration of CLNormalizePlanarYUVLayerKernel. More...
 
- 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 NormalizePlanarYUV layer kernel.

Definition at line 34 of file CLNormalizePlanarYUVLayerKernel.h.

Constructor & Destructor Documentation

◆ CLNormalizePlanarYUVLayerKernel() [1/3]

Constructor.

Definition at line 94 of file CLNormalizePlanarYUVLayerKernel.cpp.

95  : _input(nullptr), _output(nullptr), _mean(nullptr), _std(nullptr)
96 {
97 }

◆ CLNormalizePlanarYUVLayerKernel() [2/3]

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

◆ CLNormalizePlanarYUVLayerKernel() [3/3]

Default Move Constructor.

◆ ~CLNormalizePlanarYUVLayerKernel()

Default destructor.

Member Function Documentation

◆ configure() [1/2]

void configure ( const ICLTensor input,
ICLTensor output,
const ICLTensor mean,
const ICLTensor std 
)

Set the input and output tensors.

Parameters
[in]inputSource tensor. 3 lower dimensions represent a single input with dimensions [width, height, channels]. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
[out]outputDestination tensor. Data type supported: same as input
[in]meanMean values tensor. 1 dimension with size equal to the number of input channels. Data types supported: same as input
[in]stdStandard deviation values tensor. 1 dimension with size equal to the number of input channels. Data types supported: same as input

Definition at line 99 of file CLNormalizePlanarYUVLayerKernel.cpp.

References CLKernelLibrary::get().

100 {
101  configure(CLKernelLibrary::get().get_compile_context(), input, output, mean, std);
102 }
static CLKernelLibrary & get()
Access the KernelLibrary singleton.
void configure(const ICLTensor *input, ICLTensor *output, const ICLTensor *mean, const ICLTensor *std)
Set the input and output tensors.

◆ configure() [2/2]

void configure ( const CLCompileContext compile_context,
const ICLTensor input,
ICLTensor output,
const ICLTensor mean,
const ICLTensor std 
)

Set the input and output tensors.

Parameters
[in]compile_contextThe compile context to be used.
[in]inputSource tensor. 3 lower dimensions represent a single input with dimensions [width, height, channels]. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
[out]outputDestination tensor. Data type supported: same as input
[in]meanMean values tensor. 1 dimension with size equal to the number of input channels. Data types supported: same as input
[in]stdStandard deviation values tensor. 1 dimension with size equal to the number of input channels. Data types supported: same as input

Definition at line 104 of file CLNormalizePlanarYUVLayerKernel.cpp.

References CLBuildOptions::add_option(), ARM_COMPUTE_ERROR_ON_NULLPTR, ARM_COMPUTE_ERROR_THROW_ON, arm_compute::CHANNEL, arm_compute::create_kernel(), ITensorInfo::data_layout(), ITensorInfo::data_type(), ITensorInfo::dimension(), dt, ITensorInfo::element_size(), arm_compute::get_cl_type_from_data_type(), arm_compute::get_data_layout_dimension_index(), ITensor::info(), arm_compute::test::validation::input, arm_compute::is_data_type_quantized(), kernel_name, arm_compute::lower_string(), UniformQuantizationInfo::offset, CLBuildOptions::options(), arm_compute::test::validation::qinfo, ITensorInfo::quantization_info(), UniformQuantizationInfo::scale, arm_compute::string_from_data_layout(), arm_compute::string_from_data_type(), arm_compute::support::cpp11::to_string(), QuantizationInfo::uniform(), and arm_compute::validate_arguments().

105 {
106  // Perform validation step
107  ARM_COMPUTE_ERROR_ON_NULLPTR(input, output, mean, std);
108  ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), mean->info(), std->info()));
109 
110  _input = input;
111  _output = output;
112  _mean = mean;
113  _std = std;
114 
115  const unsigned int num_elems_processed_per_iteration = 16 / input->info()->element_size();
116  const unsigned int channel_idx = get_data_layout_dimension_index(input->info()->data_layout(), DataLayoutDimension::CHANNEL);
117  const DataType dt = input->info()->data_type();
118 
119  // Set build options
120  CLBuildOptions build_opts;
121  build_opts.add_option(("-DDATA_TYPE=" + get_cl_type_from_data_type(dt)));
122  build_opts.add_option(("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration)));
123  build_opts.add_option(("-DNUM_CHANNELS=" + support::cpp11::to_string(input->info()->dimension(channel_idx))));
124 
125  std::string kernel_name = "normalize_planar_yuv_layer_";
126  if(is_data_type_quantized(dt))
127  {
128  const UniformQuantizationInfo qinfo = input->info()->quantization_info().uniform();
129  build_opts.add_option(("-DOFFSET=" + support::cpp11::to_string(qinfo.offset)));
130  build_opts.add_option(("-DSCALE=" + support::cpp11::to_string(qinfo.scale)));
131  kernel_name += "q8_";
132  }
133 
134  // Create kernel
135  kernel_name += lower_string(string_from_data_layout(input->info()->data_layout()));
136  _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
137 
138  // Configure kernel window
139  auto win_config = validate_and_configure_window(input->info(), output->info(), mean->info(), std->info());
140  ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
141  ICLKernel::configure_internal(win_config.second);
142 
143  // Set config_id for enabling LWS tuning
144  _config_id = "normalize_planar_yuv_layer_";
145  _config_id += lower_string(string_from_data_layout(input->info()->data_layout()));
146  _config_id += "_";
147  _config_id += lower_string(string_from_data_type(dt));
148  _config_id += "_";
149  _config_id += support::cpp11::to_string(input->info()->dimension(0));
150  _config_id += "_";
151  _config_id += support::cpp11::to_string(input->info()->dimension(1));
152  _config_id += "_";
153  _config_id += support::cpp11::to_string(input->info()->dimension(2));
154 }
bool is_data_type_quantized(DataType dt)
Check if a given data type is of quantized type.
Definition: Utils.h:1168
std::string to_string(T &&value)
Convert integer and float values to string.
#define ARM_COMPUTE_ERROR_THROW_ON(status)
Definition: Error.h:455
std::string lower_string(const std::string &val)
Lower a given string.
Definition: Utils.cpp:350
DataType dt
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
const std::string & string_from_data_type(DataType dt)
Convert a data type identity into a string.
Definition: Utils.cpp:135
std::string kernel_name
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
const std::string & string_from_data_layout(DataLayout dl)
Convert a data layout identity into a string.
Definition: Utils.cpp:123
const QuantizationInfo qinfo
Definition: Im2Col.cpp:155
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, const GEMMLowpOutputStageInfo *output_stage)
unsigned int num_elems_processed_per_iteration
#define ARM_COMPUTE_ERROR_ON_NULLPTR(...)
Definition: Validate.h:161
size_t get_data_layout_dimension_index(const DataLayout data_layout, const DataLayoutDimension data_layout_dimension)
Get the index of the given dimension.
Definition: Helpers.inl:193
DataType
Available data types.
Definition: Types.h:77

◆ operator=() [1/2]

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

◆ operator=() [2/2]

Default move assignment operator.

◆ 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 164 of file CLNormalizePlanarYUVLayerKernel.cpp.

References ICLKernel::add_1D_tensor_argument(), ICLKernel::add_3D_tensor_argument(), ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW, ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL, Window::collapse_if_possible(), Window::DimX, Window::DimZ, arm_compute::enqueue(), Window::first_slice_window_1D(), Window::first_slice_window_3D(), ICLKernel::lws_hint(), ICLKernel::num_arguments_per_3D_tensor(), Window::set(), arm_compute::test::validation::reference::slice(), Window::slide_window_slice_3D(), and IKernel::window().

165 {
168 
170  Window slice = collapsed.first_slice_window_3D();
171 
172  Window slice_in = collapsed.first_slice_window_1D();
173  slice_in.set(Window::DimX, Window::Dimension(0, 0, 0));
174 
175  unsigned int idx = 2 * num_arguments_per_3D_tensor();
176  add_1D_tensor_argument(idx, _mean, slice_in);
177  add_1D_tensor_argument(idx, _std, slice_in);
178 
179  do
180  {
181  idx = 0;
182  add_3D_tensor_argument(idx, _input, slice);
183  add_3D_tensor_argument(idx, _output, slice);
184  enqueue(queue, *this, slice, lws_hint());
185  }
186  while(collapsed.slide_window_slice_3D(slice));
187 }
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
void add_3D_tensor_argument(unsigned int &idx, const ICLTensor *tensor, const Window &window)
Add the passed 3D tensor&#39;s parameters to the object&#39;s kernel&#39;s arguments starting from the index idx...
Definition: ICLKernel.h:172
static constexpr size_t DimX
Alias for dimension 0 also known as X dimension.
Definition: Window.h:43
static constexpr unsigned int num_arguments_per_3D_tensor()
Returns the number of arguments enqueued per 3D tensor object.
Definition: ICLKernel.h:214
Window collapse_if_possible(const Window &full_window, size_t first, size_t last, bool *has_collapsed=nullptr) const
Collapse the dimensions between first and last if possible.
Definition: Window.inl:68
#define ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(k)
Definition: Validate.h:941
static constexpr size_t DimZ
Alias for dimension 2 also known as Z dimension.
Definition: Window.h:47
void add_1D_tensor_argument(unsigned int &idx, const ICLTensor *tensor, const Window &window)
Add the passed 1D tensor&#39;s parameters to the object&#39;s kernel&#39;s arguments starting from the index idx...
Definition: ICLKernel.h:124
#define ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(f, s)
Definition: Validate.h:205
SimpleTensor< T > slice(const SimpleTensor< T > &src, Coordinates starts, Coordinates ends)

◆ validate()

Status validate ( const ITensorInfo input,
const ITensorInfo output,
const ITensorInfo mean,
const ITensorInfo std 
)
static

Static function to check if given info will lead to a valid configuration of CLNormalizePlanarYUVLayerKernel.

Parameters
[in]inputSource tensor info. 3 lower dimensions represent a single input with dimensions [width, height, channels]. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
[out]outputDestination tensor info. Data type supported: same as input
[in]meanMean values tensor info. 1 dimension with size equal to the number of input channels. Data types supported: same as input
[in]stdStandard deviation values tensor info. 1 dimension with size equal to the number of input channels. Data types supported: same as input
Returns
a status

Definition at line 156 of file CLNormalizePlanarYUVLayerKernel.cpp.

References ARM_COMPUTE_RETURN_ON_ERROR, ICloneable< T >::clone(), and arm_compute::validate_arguments().

Referenced by CLNormalizePlanarYUVLayer::validate().

157 {
159  ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), output->clone().get(), mean->clone().get(), std->clone().get()).first);
160 
161  return Status{};
162 }
#define ARM_COMPUTE_RETURN_ON_ERROR(status)
Checks if a status contains an error and returns it.
Definition: Error.h:204
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, const GEMMLowpOutputStageInfo *output_stage)

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