Compute Library
 22.11
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...
 
CLKernelType type () const
 Returns the CL kernel type. 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...
 
void add_5D_tensor_argument (unsigned int &idx, const ICLTensor *tensor, const Window &window)
 Add the passed 5D tensor's parameters to the object's kernel's arguments starting from the index idx. More...
 
void add_3d_tensor_nhw_argument (unsigned int &idx, const ICLTensor *tensor)
 Add the passed NHW 3D tensor's parameters to the object's kernel's arguments by passing strides, dimensions and the offset to the first valid element in bytes. More...
 
void add_4d_tensor_nhwc_argument (unsigned int &idx, const ICLTensor *tensor)
 Add the passed NHWC 4D tensor's parameters to the object's kernel's arguments by passing strides, dimensions and the offset to the first valid element in bytes. 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...
 
virtual void run_composite_op (ITensorPack &tensors, const Window &window, cl::CommandQueue &queue, const experimental::dynamic_fusion::ClExecutionDescriptor &exec_desc)
 The execution is carried out through run_op method. But the run_op method needs to be extended to include ClExecutionDescriptor as now LWS GWS tuning will be separated from the IKernel. 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...
 
bool is_window_configured () const
 Function to check if the embedded window of this kernel has been configured. 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_3d_tensor_nhw ()
 Returns the number of arguments enqueued per NHW 3D Tensor object. More...
 
static constexpr unsigned int num_arguments_per_4d_tensor_nhwc ()
 Returns the number of arguments enqueued per NHWC 4D Tensor object. More...
 
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 83 of file CLNormalizePlanarYUVLayerKernel.cpp.

References arm_compute::ELEMENTWISE.

84  : _input(nullptr), _output(nullptr), _mean(nullptr), _std(nullptr)
85 {
87 }
Elementwise CL kernel type.
Definition: CLTypes.h:85

◆ 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 89 of file CLNormalizePlanarYUVLayerKernel.cpp.

References CLKernelLibrary::get().

90 {
91  configure(CLKernelLibrary::get().get_compile_context(), input, output, mean, std);
92 }
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 94 of file CLNormalizePlanarYUVLayerKernel.cpp.

References CLBuildOptions::add_option(), arm_compute::adjust_vec_size(), ARM_COMPUTE_ERROR_ON, ARM_COMPUTE_ERROR_ON_NULLPTR, ARM_COMPUTE_ERROR_THROW_ON, arm_compute::auto_init_if_empty(), arm_compute::calculate_max_window(), arm_compute::CHANNEL, ICloneable< T >::clone(), arm_compute::create_kernel(), ITensorInfo::data_layout(), arm_compute::test::validation::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(), arm_compute::get_padding_info(), arm_compute::has_padding_changed(), ITensor::info(), arm_compute::test::validation::input, arm_compute::is_data_type_quantized(), kernel_name, arm_compute::lower_string(), arm_compute::NHWC, num_elems_processed_per_iteration, 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::cpu::kernels::validate_arguments().

95 {
96  // Perform validation step
97  ARM_COMPUTE_ERROR_ON_NULLPTR(input, output, mean, std);
98  ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), mean->info(), std->info()));
99 
100  // Output tensor auto initialization if not yet initialized
101  auto_init_if_empty(*output->info(), *input->info()->clone());
102 
103  auto padding_info = get_padding_info({ input, output });
104 
105  _input = input;
106  _output = output;
107  _mean = mean;
108  _std = std;
109 
110  const DataLayout data_layout = input->info()->data_layout();
111 
112  // Get number of elements to process per iterations
113  const unsigned int num_elems_processed_per_iteration = (data_layout == DataLayout::NHWC) ? adjust_vec_size(16 / input->info()->element_size(),
114  input->info()->dimension(0)) :
115  (16 / input->info()->element_size());
116  const unsigned int channel_idx = get_data_layout_dimension_index(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(("-DVEC_SIZE_LEFTOVER=" + support::cpp11::to_string(input->info()->dimension(0) % num_elems_processed_per_iteration)));
124  build_opts.add_option(("-DNUM_CHANNELS=" + support::cpp11::to_string(input->info()->dimension(channel_idx))));
125 
126  std::string kernel_name = "normalize_planar_yuv_layer_";
127  if(is_data_type_quantized(dt))
128  {
129  const UniformQuantizationInfo qinfo = input->info()->quantization_info().uniform();
130  build_opts.add_option(("-DOFFSET=" + support::cpp11::to_string(qinfo.offset)));
131  build_opts.add_option(("-DSCALE=" + support::cpp11::to_string(qinfo.scale)));
132  kernel_name += "q8_";
133  }
134 
135  // Create kernel
136  kernel_name += lower_string(string_from_data_layout(data_layout));
137  _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
138 
139  // Configure kernel window
140  if(data_layout == DataLayout::NHWC)
141  {
142  Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration));
143  ICLKernel::configure_internal(win);
145  }
146  else
147  {
148  auto win_config = validate_and_configure_window_nchw(input->info(), output->info());
149  ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
150  ICLKernel::configure_internal(win_config.second);
151  }
152 
153  // Set config_id for enabling LWS tuning
154  _config_id = "normalize_planar_yuv_layer_";
155  _config_id += lower_string(string_from_data_layout(input->info()->data_layout()));
156  _config_id += "_";
157  _config_id += lower_string(string_from_data_type(dt));
158  _config_id += "_";
159  _config_id += support::cpp11::to_string(input->info()->dimension(0));
160  _config_id += "_";
161  _config_id += support::cpp11::to_string(input->info()->dimension(1));
162  _config_id += "_";
163  _config_id += support::cpp11::to_string(input->info()->dimension(2));
164 }
bool is_data_type_quantized(DataType dt)
Check if a given data type is of quantized type.
Definition: Utils.h:1030
Window calculate_max_window(const ValidRegion &valid_region, const Steps &steps, bool skip_border, BorderSize border_size)
std::string to_string(T &&value)
Convert integer and float values to string.
#define ARM_COMPUTE_ERROR_ON(cond)
If the condition is true then an error message is printed and an exception thrown.
Definition: Error.h:466
#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:353
Status validate_arguments(const ITensorInfo *src, const ITensorInfo *weights, const ITensorInfo *dst, const PadStrideInfo &conv_info)
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:404
const std::string & string_from_data_type(DataType dt)
Convert a data type identity into a string.
Definition: Utils.cpp:135
unsigned int num_elems_processed_per_iteration
std::string get_cl_type_from_data_type(const DataType &dt)
Translates a tensor data type to the appropriate OpenCL type.
Definition: CLHelpers.cpp:39
bool auto_init_if_empty(ITensorInfo &info, const TensorShape &shape, int num_channels, DataType data_type, QuantizationInfo quantization_info=QuantizationInfo())
Auto initialize the tensor info (shape, number of channels and data type) if the current assignment i...
bool has_padding_changed(const std::unordered_map< const ITensorInfo *, PaddingSize > &padding_map)
Check if the previously stored padding info has changed after configuring a kernel.
Definition: Utils.cpp:603
const std::string & string_from_data_layout(DataLayout dl)
Convert a data layout identity into a string.
Definition: Utils.cpp:123
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
const QuantizationInfo qinfo
Definition: Im2Col.cpp:155
Num samples, height, width, channels.
std::unordered_map< const ITensorInfo *, PaddingSize > get_padding_info(std::initializer_list< const ITensorInfo *> infos)
Stores padding information before configuring a kernel.
Definition: Utils.cpp:588
#define ARM_COMPUTE_ERROR_ON_NULLPTR(...)
Definition: Validate.h:157
unsigned int adjust_vec_size(unsigned int vec_size, size_t dim0)
Returns the adjusted vector size in case it is less than the input&#39;s first dimension, getting rounded down to its closest valid vector size.
Definition: Utils.h:1222
std::string kernel_name
DataType
Available data types.
Definition: Types.h:79
DataLayout
[DataLayout enum definition]
Definition: Types.h:113

◆ 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 176 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().

177 {
180 
182  Window slice = collapsed.first_slice_window_3D();
183 
184  Window slice_in = collapsed.first_slice_window_1D();
185  slice_in.set(Window::DimX, Window::Dimension(0, 0, 0));
186 
187  unsigned int idx = 2 * num_arguments_per_3D_tensor();
188  add_1D_tensor_argument(idx, _mean, slice_in);
189  add_1D_tensor_argument(idx, _std, slice_in);
190 
191  do
192  {
193  idx = 0;
194  add_3D_tensor_argument(idx, _input, slice);
195  add_3D_tensor_argument(idx, _output, slice);
196  enqueue(queue, *this, slice, lws_hint());
197  }
198  while(collapsed.slide_window_slice_3D(slice));
199 }
const Window & window() const
The maximum window the kernel can be executed on.
Definition: IKernel.cpp:28
void enqueue(cl::CommandQueue &queue, ICLKernel &kernel, const Window &window, const cl::NDRange &lws_hint=CLKernelLibrary::get().default_ndrange(), bool use_dummy_work_items=false)
Add the kernel to the command queue with the given window.
Definition: ICLKernel.cpp:32
cl::NDRange lws_hint() const
Return the Local-Workgroup-Size hint.
Definition: ICLKernel.h:383
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:226
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:313
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:915
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:178
#define ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(f, s)
Definition: Validate.h:201
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 166 of file CLNormalizePlanarYUVLayerKernel.cpp.

References ARM_COMPUTE_RETURN_ON_ERROR, ICloneable< T >::clone(), ITensorInfo::data_layout(), arm_compute::NCHW, and arm_compute::cpu::kernels::validate_arguments().

Referenced by CLNormalizePlanarYUVLayer::validate().

167 {
169  if(input->data_layout() == DataLayout::NCHW)
170  {
171  ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window_nchw(input->clone().get(), output->clone().get()).first);
172  }
173  return Status{};
174 }
#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 *src, const ITensorInfo *weights, const ITensorInfo *dst, const PadStrideInfo &conv_info)
Num samples, channels, height, width.

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