Compute Library
 22.08
CLMeanStdDevNormalizationKernel Class Reference

Interface for the kernel to normalize the input 2D tensor across the first dimension with respect to mean and standard deviation of the same dimension. More...

#include <CLMeanStdDevNormalizationKernel.h>

Collaboration diagram for CLMeanStdDevNormalizationKernel:
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Public Member Functions

 CLMeanStdDevNormalizationKernel ()
 Default constructor. More...
 
 CLMeanStdDevNormalizationKernel (const CLMeanStdDevNormalizationKernel &)=delete
 Prevent instances of this class from being copied (As this class contains pointers) More...
 
CLMeanStdDevNormalizationKerneloperator= (const CLMeanStdDevNormalizationKernel &)=delete
 Prevent instances of this class from being copied (As this class contains pointers) More...
 
 CLMeanStdDevNormalizationKernel (CLMeanStdDevNormalizationKernel &&)=default
 Allow instances of this class to be moved. More...
 
CLMeanStdDevNormalizationKerneloperator= (CLMeanStdDevNormalizationKernel &&)=default
 Allow instances of this class to be moved. More...
 
 ~CLMeanStdDevNormalizationKernel ()=default
 Default destructor. More...
 
void configure (ICLTensor *input, ICLTensor *output=nullptr, float epsilon=1e-8f)
 Initialise the kernel's input and outputs. More...
 
void configure (const CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output=nullptr, float epsilon=1e-8f)
 Initialise the kernel's input and outputs. 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=nullptr, float epsilon=1e-8f)
 Static function to check if given info will lead to a valid configuration of CLMeanStdDevNormalizationKernel. 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 kernel to normalize the input 2D tensor across the first dimension with respect to mean and standard deviation of the same dimension.

Definition at line 34 of file CLMeanStdDevNormalizationKernel.h.

Constructor & Destructor Documentation

◆ CLMeanStdDevNormalizationKernel() [1/3]

Default constructor.

Definition at line 59 of file CLMeanStdDevNormalizationKernel.cpp.

References arm_compute::ELEMENTWISE.

60  : _input(nullptr), _output(nullptr), _run_in_place(false)
61 {
63 }
Elementwise CL kernel type.
Definition: CLTypes.h:85

◆ CLMeanStdDevNormalizationKernel() [2/3]

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

◆ CLMeanStdDevNormalizationKernel() [3/3]

Allow instances of this class to be moved.

◆ ~CLMeanStdDevNormalizationKernel()

Default destructor.

Member Function Documentation

◆ configure() [1/2]

void configure ( ICLTensor input,
ICLTensor output = nullptr,
float  epsilon = 1e-8f 
)

Initialise the kernel's input and outputs.

Note
If the output tensor is a nullptr, the normalization will be performed in-place.
Parameters
[in,out]inputSource tensor with 2 dimensions. In case of output tensor = nullptr, this tensor will store the result of the normalization. Data types supported: F16/F32.
[out]output(Optional) Destination tensor. It can be nullptr in case of in-place computation. Data type supported: same as input
[in]epsilon(Optional) Small float to avoid division by zero in case of zero standard deviation. Defaults to 1e-8.

Definition at line 65 of file CLMeanStdDevNormalizationKernel.cpp.

References CLKernelLibrary::get().

66 {
67  configure(CLKernelLibrary::get().get_compile_context(), input, output, epsilon);
68 }
static CLKernelLibrary & get()
Access the KernelLibrary singleton.
void configure(ICLTensor *input, ICLTensor *output=nullptr, float epsilon=1e-8f)
Initialise the kernel&#39;s input and outputs.

◆ configure() [2/2]

void configure ( const CLCompileContext compile_context,
ICLTensor input,
ICLTensor output = nullptr,
float  epsilon = 1e-8f 
)

Initialise the kernel's input and outputs.

Note
If the output tensor is a nullptr, the normalization will be performed in-place.
Parameters
[in]compile_contextThe compile context to be used.
[in,out]inputSource tensor with 2 dimensions. In case of output tensor = nullptr, this tensor will store the result of the normalization. Data types supported: F16/F32.
[out]output(Optional) Destination tensor. It can be nullptr in case of in-place computation. Data type supported: same as input
[in]epsilon(Optional) Small float to avoid division by zero in case of zero standard deviation. Defaults to 1e-8.

Definition at line 70 of file CLMeanStdDevNormalizationKernel.cpp.

References CLBuildOptions::add_option(), arm_compute::adjust_vec_size(), ARM_COMPUTE_ERROR_ON_NULLPTR, ARM_COMPUTE_ERROR_THROW_ON, arm_compute::auto_init_if_empty(), arm_compute::calculate_max_window(), arm_compute::create_kernel(), ITensorInfo::data_type(), ITensorInfo::dimension(), ITensorInfo::element_size(), arm_compute::quantization::epsilon, arm_compute::float_to_string_with_full_precision(), arm_compute::get_cl_type_from_data_type(), ITensor::info(), arm_compute::test::validation::input, arm_compute::lower_string(), num_elems_processed_per_iteration, arm_compute::string_from_data_type(), arm_compute::support::cpp11::to_string(), and CLMeanStdDevNormalizationKernel::validate().

71 {
73 
74  _run_in_place = (output == nullptr) || (output == input);
75 
76  ARM_COMPUTE_ERROR_THROW_ON(CLMeanStdDevNormalizationKernel::validate(input->info(), (output != nullptr) ? output->info() : nullptr, epsilon));
77 
78  if(output != nullptr)
79  {
80  auto_init_if_empty(*output->info(), *input->info());
81  }
82 
83  _input = input;
84  _output = output;
85 
86  const unsigned int num_elems_processed_per_iteration = adjust_vec_size(16 / input->info()->element_size(), input->info()->dimension(0));
87 
88  // Set build options
89  CLBuildOptions build_opts;
90  build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()));
91  build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration));
92  build_opts.add_option("-DEPSILON=" + float_to_string_with_full_precision(epsilon));
93  build_opts.add_option("-DWIDTH=" + support::cpp11::to_string(input->info()->dimension(0)));
94  build_opts.add_option_if(_run_in_place, "-DIN_PLACE");
95 
96  // Create kernel
97  _kernel = create_kernel(compile_context, "mean_stddev_normalization", build_opts.options());
98 
99  // Configure kernel window
100  Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration));
101  ICLKernel::configure_internal(win);
102 
103  // Set config_id for enabling LWS tuning
104  _config_id = "mean_stddev_normalization_layer_";
105  _config_id += lower_string(string_from_data_type(input->info()->data_type()));
106  _config_id += "_";
107  _config_id += support::cpp11::to_string(input->info()->dimension(0));
108  _config_id += "_";
109  _config_id += support::cpp11::to_string(input->info()->dimension(1));
110 }
static Status validate(const ITensorInfo *input, const ITensorInfo *output=nullptr, float epsilon=1e-8f)
Static function to check if given info will lead to a valid configuration of CLMeanStdDevNormalizatio...
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_THROW_ON(status)
Definition: Error.h:455
std::string lower_string(const std::string &val)
Lower a given string.
Definition: Utils.cpp:351
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
std::string float_to_string_with_full_precision(float val)
Create a string with the float in full precision.
Definition: Utils.h:1124
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...
#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

◆ operator=() [1/2]

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 118 of file CLMeanStdDevNormalizationKernel.cpp.

References ICLKernel::add_2D_tensor_argument(), ICLKernel::add_2D_tensor_argument_if(), ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW, ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL, ITensorInfo::dimension(), Window::DimX, arm_compute::enqueue(), Window::first_slice_window_2D(), ITensor::info(), ICLKernel::lws_hint(), Window::set_dimension_step(), arm_compute::test::validation::reference::slice(), Window::slide_window_slice_2D(), and IKernel::window().

119 {
122 
124  // Set slice step equal to width to force gws[0] to 1, as each thread normalizes across all rows
125  slice.set_dimension_step(Window::DimX, _input->info()->dimension(0));
126 
127  do
128  {
129  unsigned int idx = 0;
130  add_2D_tensor_argument(idx, _input, slice);
131  add_2D_tensor_argument_if((!_run_in_place), idx, _output, slice);
132 
133  enqueue(queue, *this, slice, lws_hint());
134  }
135  while(window.slide_window_slice_2D(slice));
136 }
Window first_slice_window_2D() const
First 2D slice of the window.
Definition: Window.h:297
const Window & window() const
The maximum window the kernel can be executed on.
Definition: IKernel.cpp:28
void add_2D_tensor_argument_if(bool cond, 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:214
virtual size_t dimension(size_t index) const =0
Return the size of the requested dimension.
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:384
bool slide_window_slice_2D(Window &slice) const
Slide the passed 2D window slice.
Definition: Window.h:337
static constexpr size_t DimX
Alias for dimension 0 also known as X dimension.
Definition: Window.h:43
virtual ITensorInfo * info() const =0
Interface to be implemented by the child class to return the tensor&#39;s metadata.
#define ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(k)
Definition: Validate.h:915
void set_dimension_step(size_t dimension, int step)
Set the step of a given dimension.
Definition: Window.inl:167
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:203
#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 = nullptr,
float  epsilon = 1e-8f 
)
static

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

Parameters
[in]inputSource tensor info with 2 dimensions. In case of output tensor info = nullptr, this tensor will store the result of the normalization. Data types supported: F16/F32.
[in]output(Optional) Destination tensor info. It can be nullptr in case of in-place computation. Data type supported: same as input
[in]epsilon(Optional) Small float to avoid division by zero in case of zero standard deviation. Defaults to 1e-8.
Returns
a status

Definition at line 112 of file CLMeanStdDevNormalizationKernel.cpp.

References ARM_COMPUTE_RETURN_ON_ERROR, and arm_compute::cpu::kernels::validate_arguments().

Referenced by CLMeanStdDevNormalizationKernel::configure(), and CLMeanStdDevNormalizationLayer::validate().

113 {
115  return Status{};
116 }
#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)

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