Compute Library
 19.08
CLNormalizationLayerKernel Class Reference

Interface for the normalization layer kernel. More...

#include <CLNormalizationLayerKernel.h>

Collaboration diagram for CLNormalizationLayerKernel:
[legend]

Public Member Functions

 CLNormalizationLayerKernel ()
 Constructor. More...
 
 CLNormalizationLayerKernel (const CLNormalizationLayerKernel &)=delete
 Prevent instances of this class from being copied (As this class contains pointers) More...
 
CLNormalizationLayerKerneloperator= (const CLNormalizationLayerKernel &)=delete
 Prevent instances of this class from being copied (As this class contains pointers) More...
 
 CLNormalizationLayerKernel (CLNormalizationLayerKernel &&)=default
 Default Move Constructor. More...
 
CLNormalizationLayerKerneloperator= (CLNormalizationLayerKernel &&)=default
 Default move assignment operator. More...
 
void configure (const ICLTensor *input, ICLTensor *output, NormalizationLayerInfo norm_info)
 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...
 
BorderSize border_size () const override
 The size of the border for that kernel. 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...
 
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...
 
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<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...
 
template<unsigned int dimension_size>
void add_tensor_argument (unsigned &idx, const ICLTensor *tensor, const Window &window)
 
- 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...
 
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, NormalizationLayerInfo norm_info)
 Static function to check if given info will lead to a valid configuration of CLNormalizationLayerKernel. 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 normalization layer kernel.

Definition at line 35 of file CLNormalizationLayerKernel.h.

Constructor & Destructor Documentation

◆ CLNormalizationLayerKernel() [1/3]

Constructor.

Definition at line 97 of file CLNormalizationLayerKernel.cpp.

98  : _input(nullptr), _output(nullptr), _border_size(0), _is_norm_across_width(false)
99 {
100 }

◆ CLNormalizationLayerKernel() [2/3]

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

◆ CLNormalizationLayerKernel() [3/3]

Default Move Constructor.

Member Function Documentation

◆ border_size()

BorderSize border_size ( ) const
overridevirtual

The size of the border for that kernel.

Returns
The width in number of elements of the border.

Reimplemented from IKernel.

Definition at line 102 of file CLNormalizationLayerKernel.cpp.

103 {
104  return _border_size;
105 }

Referenced by CLNormalizationLayer::configure().

◆ configure()

void configure ( const ICLTensor input,
ICLTensor output,
NormalizationLayerInfo  norm_info 
)

Set the input and output tensors.

Parameters
[in]inputSource tensor. 3 lower dims represent a single input with dimensions [width, height, IFM], and an optional 4th dimension for batch of inputs. Data types supported: F16/F32. Data layouts supported: NCHW/NHWC.
[out]outputDestination tensor. Output will have the same number of dimensions as input. Data types supported: same as input. Data layouts supported: same as input.
[in]norm_infoNormalization layer information like the normalization type, normalization size and other parameters.

Definition at line 107 of file CLNormalizationLayerKernel.cpp.

108 {
109  ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
110 
111  // Output tensor auto initialization if not yet initialized
112  auto_init_if_empty(*output->info(), *input->info()->clone());
113 
114  // Perform validation step
115  ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), norm_info));
116 
117  _input = input;
118  _output = output;
119 
120  const DataLayout data_layout = input->info()->data_layout();
121  const unsigned int norm_idx = get_normalization_dimension_index(data_layout, norm_info);
122  _is_norm_across_width = norm_idx == 0;
123  const unsigned int border_width = _is_norm_across_width ? num_elems_processed_per_iteration - 1 : 0;
124  _border_size = BorderSize(0, border_width);
125 
126  const bool is_in_map_2D = (norm_info.type() == NormType::IN_MAP_2D);
127 
128  // Set build options
129  CLBuildOptions build_opts;
130  build_opts.add_option(("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type())));
131  build_opts.add_option(("-DCOEFF=" + float_to_string_with_full_precision(norm_info.scale_coeff())));
132  build_opts.add_option(("-DBETA=" + float_to_string_with_full_precision(norm_info.beta())));
133  build_opts.add_option(("-DKAPPA=" + float_to_string_with_full_precision(norm_info.kappa())));
134  build_opts.add_option(("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration)));
135  build_opts.add_option(("-DRADIUS=" + support::cpp11::to_string(norm_info.norm_size() / 2)));
136  build_opts.add_option(("-DNUM_SLICES=" + support::cpp11::to_string(input->info()->dimension(2))));
137  build_opts.add_option_if(is_in_map_2D, "-DIN_MAP_2D");
138  build_opts.add_option_if(norm_info.is_in_map() || (data_layout == DataLayout::NHWC && norm_info.is_cross_map()), "-DWIDTH_SIZE=" + support::cpp11::to_string(input->info()->dimension(0)));
139 
140  // Create kernel
141  std::string kernel_name;
142  if(norm_info.is_in_map())
143  {
144  kernel_name = "normalization_layer_in_map_" + lower_string(string_from_data_layout(data_layout));
145  }
146  else
147  {
149  {
150  kernel_name = "normalization_layer_cross_map";
151  }
152  else
153  {
154  // 1D Cross-Map normalization in NHWC is the same as 1D In-Map normalization in NCHW
155  kernel_name = "normalization_layer_in_map_nchw";
156  }
157  }
158  _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
159 
160  // Configure kernel window
161  auto win_config = validate_and_configure_window(input->info(), output->info(), norm_info);
162  ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
163  ICLKernel::configure_internal(win_config.second);
164 
165  // Set config_id for enabling LWS tuning
166  _config_id = "normalization_layer_";
167  _config_id += lower_string(string_from_data_type(input->info()->data_type()));
168  _config_id += "_";
169  _config_id += support::cpp11::to_string(static_cast<std::underlying_type<NormType>::type>(norm_info.type()));
170  _config_id += "_";
171  _config_id += support::cpp11::to_string(norm_info.norm_size());
172  _config_id += "_";
173  _config_id += support::cpp11::to_string(input->info()->dimension(0));
174  _config_id += "_";
175  _config_id += support::cpp11::to_string(input->info()->dimension(1));
176 }
float scale_coeff() const
Return the scaling factor of the normalization function.
Definition: Types.h:1642
const DataLayout data_layout
Definition: Im2Col.cpp:146
float kappa() const
Get the kappa value.
Definition: Types.h:1616
bool is_in_map() const
Check if normalization is not cross map.
Definition: Types.h:1631
virtual size_t dimension(size_t index) const =0
Return the size of the requested dimension.
Container for 2D border size.
Definition: Types.h:259
const StringSet & options() const
Gets the current options list set.
std::pair< Status, Window > validate_and_configure_window(ITensorInfo *input, ITensorInfo *weights, ITensorInfo *biases, ITensorInfo *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier, const Size2D &dilation)
uint32_t norm_size() const
Get the normalization size.
Definition: Types.h:1601
NormType type() const
Get the normalization type.
Definition: Types.h:1596
std::string to_string(T &&value)
Convert integer and float values to string.
virtual DataType data_type() const =0
Data type used for each element of the tensor.
bool is_cross_map() const
Check if normalization is cross map.
Definition: Types.h:1626
static CLKernelLibrary & get()
Access the KernelLibrary singleton.
#define ARM_COMPUTE_ERROR_THROW_ON(status)
Definition: Error.h:327
std::string lower_string(const std::string &val)
Lower a given string.
Definition: Utils.cpp:327
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...
Definition: Helpers.inl:201
void add_option(std::string option)
Adds option to the existing build option list.
const std::string & string_from_data_type(DataType dt)
Convert a data type identity into a string.
Definition: Utils.cpp:144
std::string float_to_string_with_full_precision(float val)
Create a string with the float in full precision.
Definition: Utils.h:1066
std::string get_cl_type_from_data_type(const DataType &dt)
Translates a tensor data type to the appropriate OpenCL type.
Definition: CLHelpers.cpp:35
virtual std::unique_ptr< T > clone() const =0
Provide a clone of the current object of class T.
virtual ITensorInfo * info() const =0
Interface to be implemented by the child class to return the tensor's metadata.
float beta() const
Get the beta value.
Definition: Types.h:1611
void add_option_if(bool cond, std::string option)
Adds option if a given condition is true;.
std::unique_ptr< Kernel > create_kernel()
Helper function to create and return a unique_ptr pointed to a CL/GLES kernel object.
Definition: Helpers.h:86
Num samples, channels, height, width.
#define ARM_COMPUTE_ERROR_ON_NULLPTR(...)
Definition: Validate.h:161
const std::string & string_from_data_layout(DataLayout dl)
Convert a data layout identity into a string.
Definition: Utils.cpp:132
Num samples, height, width, channels.
unsigned int get_normalization_dimension_index(DataLayout layout, const NormalizationLayerInfo &info)
Calculate the normalization dimension index for a given normalization type.
Definition: Helpers.h:726
DataLayout
[DataLayout enum definition]
Definition: Types.h:114
Normalization applied within the same map in 2D region.
virtual DataLayout data_layout() const =0
Get the data layout of the tensor.

References CLBuildOptions::add_option(), CLBuildOptions::add_option_if(), ARM_COMPUTE_ERROR_ON_NULLPTR, ARM_COMPUTE_ERROR_THROW_ON, arm_compute::auto_init_if_empty(), NormalizationLayerInfo::beta(), ICloneable< T >::clone(), arm_compute::create_kernel(), arm_compute::test::validation::data_layout, ITensorInfo::data_layout(), ITensorInfo::data_type(), ITensorInfo::dimension(), arm_compute::float_to_string_with_full_precision(), CLKernelLibrary::get(), arm_compute::get_cl_type_from_data_type(), arm_compute::get_normalization_dimension_index(), arm_compute::IN_MAP_2D, ITensor::info(), NormalizationLayerInfo::is_cross_map(), NormalizationLayerInfo::is_in_map(), NormalizationLayerInfo::kappa(), arm_compute::lower_string(), arm_compute::NCHW, arm_compute::NHWC, NormalizationLayerInfo::norm_size(), CLBuildOptions::options(), NormalizationLayerInfo::scale_coeff(), arm_compute::string_from_data_layout(), arm_compute::string_from_data_type(), arm_compute::support::cpp11::to_string(), NormalizationLayerInfo::type(), and arm_compute::validate_and_configure_window().

Referenced by CLNormalizationLayer::configure().

◆ operator=() [1/2]

CLNormalizationLayerKernel& operator= ( const CLNormalizationLayerKernel )
delete

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.

Implements ICLKernel.

Definition at line 186 of file CLNormalizationLayerKernel.cpp.

187 {
190 
191  const int collapsed_dimension = _is_norm_across_width ? Window::DimZ : 4;
192  Window window_collapsed = window.collapse_if_possible(ICLKernel::window(), collapsed_dimension);
193  Window slice = window_collapsed.first_slice_window_3D();
194 
195  do
196  {
197  unsigned int idx = 0;
198  add_3D_tensor_argument(idx, _input, slice);
199  add_3D_tensor_argument(idx, _output, slice);
200  enqueue(queue, *this, slice, lws_hint());
201  }
202  while(window_collapsed.slide_window_slice_3D(slice));
203 }
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:39
cl::NDRange lws_hint() const
Return the Local-Workgroup-Size hint.
Definition: ICLKernel.h:247
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.
Definition: ICLKernel.h:158
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:54
bool slide_window_slice_3D(Window &slice) const
Slide the passed 3D window slice.
Definition: Window.h:319
static constexpr size_t DimZ
Alias for dimension 2 also known as Z dimension.
Definition: Window.h:47
Window first_slice_window_3D() const
First 3D slice of the window.
Definition: Window.h:275
#define ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(f, s)
Definition: Validate.h:205
Describe a multidimensional execution window.
Definition: Window.h:39
#define ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(k)
Definition: Validate.h:940
SimpleTensor< T > slice(const SimpleTensor< T > &src, Coordinates starts, Coordinates ends)

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

◆ validate()

Status validate ( const ITensorInfo input,
const ITensorInfo output,
NormalizationLayerInfo  norm_info 
)
static

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

Parameters
[in]inputSource tensor. 3 lower dims represent a single input with dimensions [width, height, IFM], and an optional 4th dimension for batch of inputs. Data types supported: F16/F32. Data layouts supported: NCHW/NHWC.
[in]outputDestination tensor. Output will have the same number of dimensions as input. Data types supported: same as input. Data layouts supported: same as input.
[in]norm_infoNormalization layer information like the normalization type, normalization size and other parameters.
Returns
a status

Definition at line 178 of file CLNormalizationLayerKernel.cpp.

179 {
180  ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, norm_info));
181  ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), output->clone().get(), norm_info).first);
182 
183  return Status{};
184 }
std::pair< Status, Window > validate_and_configure_window(ITensorInfo *input, ITensorInfo *weights, ITensorInfo *biases, ITensorInfo *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier, const Size2D &dilation)
#define ARM_COMPUTE_RETURN_ON_ERROR(status)
Checks if a status contains an error and returns it.
Definition: Error.h:193
Status class.
Definition: Error.h:52
virtual std::unique_ptr< T > clone() const =0
Provide a clone of the current object of class T.

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

Referenced by CLNormalizationLayer::validate().


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