Compute Library
 23.11
Public Member Functions | Static Public Member Functions
CLComputeMeanVariance Class Reference

Interface for compute Mean and Variance per channel. More...

#include <CLInstanceNormalizationLayerKernel.h>

Collaboration diagram for CLComputeMeanVariance:
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Public Member Functions

 CLComputeMeanVariance ()
 Constructor. More...
 
 CLComputeMeanVariance (const CLComputeMeanVariance &)=delete
 Prevent instances of this class from being copied (As this class contains pointers) More...
 
CLComputeMeanVariance & operator= (const CLComputeMeanVariance &)=delete
 Prevent instances of this class from being copied (As this class contains pointers) More...
 
 CLComputeMeanVariance (CLComputeMeanVariance &&)=default
 Default Move Constructor. More...
 
CLComputeMeanVariance & operator= (CLComputeMeanVariance &&)=default
 Default move assignment operator. More...
 
 ~CLComputeMeanVariance ()=default
 Default destructor. More...
 
void configure (const CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output, bool use_mixed_precision)
 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...
 
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...
 
cl::NDRange get_cached_gws () const
 Get the cached gws used to enqueue this kernel. More...
 
void cache_gws (const cl::NDRange &gws)
 Cache the latest gws used to enqueue this kernel. 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 Window & window () 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)
 Static function to check if given info will lead to a valid configuration of CLInstanceNormalizationLayer. More...
 
- Static Public Member Functions inherited from ICLKernel
constexpr static unsigned int num_arguments_per_3d_tensor_nhw ()
 Returns the number of arguments enqueued per NHW 3D Tensor object. More...
 
constexpr static unsigned int num_arguments_per_4d_tensor_nhwc ()
 Returns the number of arguments enqueued per NHWC 4D Tensor object. More...
 
constexpr static unsigned int num_arguments_per_1D_array ()
 Returns the number of arguments enqueued per 1D array object. More...
 
constexpr static unsigned int num_arguments_per_1D_tensor ()
 Returns the number of arguments enqueued per 1D tensor object. More...
 
constexpr static unsigned int num_arguments_per_2D_tensor ()
 Returns the number of arguments enqueued per 2D tensor object. More...
 
constexpr static unsigned int num_arguments_per_3D_tensor ()
 Returns the number of arguments enqueued per 3D tensor object. More...
 
constexpr static 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, bool use_dummy_work_items)
 Get the global work size given an execution window. More...
 

Detailed Description

Interface for compute Mean and Variance per channel.

Definition at line 90 of file CLInstanceNormalizationLayerKernel.h.

Constructor & Destructor Documentation

◆ CLComputeMeanVariance() [1/3]

CLComputeMeanVariance ( )

Constructor.

Definition at line 78 of file CLInstanceNormalizationLayerKernel.cpp.

78  : _input(nullptr), _output(nullptr)
79 {
80  _type = CLKernelType::ELEMENTWISE;
81 }

References arm_compute::ELEMENTWISE.

◆ CLComputeMeanVariance() [2/3]

CLComputeMeanVariance ( const CLComputeMeanVariance &  )
delete

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

◆ CLComputeMeanVariance() [3/3]

CLComputeMeanVariance ( CLComputeMeanVariance &&  )
default

Default Move Constructor.

◆ ~CLComputeMeanVariance()

~CLComputeMeanVariance ( )
default

Default destructor.

Member Function Documentation

◆ configure()

void configure ( const CLCompileContext &  compile_context,
ICLTensor *  input,
ICLTensor *  output,
bool  use_mixed_precision 
)

Set the input and output tensors.

Parameters
[in]compile_contextThe compile context to be used.
[in,out]inputSource tensor. Data types supported: F16/F32. Data layout supported: NCHW, NHWC In case of output tensor = nullptr this tensor will store the result of the normalization.
[out]outputDestination tensor. Data types and data layouts supported: same as input.
[in]use_mixed_precisionUse mixed precision in case of FP16 execution

Definition at line 83 of file CLInstanceNormalizationLayerKernel.cpp.

87 {
88  ARM_COMPUTE_ERROR_ON_NULLPTR(input);
89  auto padding_info = get_padding_info({input, output});
90 
91  _input = input;
92  _output = output == nullptr ? input : output;
93 
94  ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_meanvar(_input->info(), _output->info()));
95  const unsigned int num_elems_processed_per_iteration = 16 / input->info()->element_size();
96 
97  CLBuildOptions build_opts;
98  build_opts.add_option("-DINTERNAL_DATA_TYPE=" +
99  (use_mixed_precision ? "float" : get_cl_type_from_data_type(input->info()->data_type())));
100  build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()));
101  build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration));
102  build_opts.add_option("-DDIM_X=" + support::cpp11::to_string(input->info()->dimension(0)));
103  build_opts.add_option("-DDIM_Y=" + support::cpp11::to_string(input->info()->dimension(1)));
104  build_opts.add_option("-DDIM_Z=" + support::cpp11::to_string(input->info()->dimension(2)));
105  build_opts.add_option_if(_input->info()->data_layout() == DataLayout::NHWC, "-DNHWC");
106  // Create kernel
107  _kernel = create_kernel(compile_context, "compute_mean_var", build_opts.options());
108 
109  // We handle the planes manually
110  Window win = calculate_max_window(*(input->info()), Steps(1));
111  const auto data_layout = input->info()->data_layout();
112  const unsigned int channel_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL);
113  const unsigned int batches_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::BATCHES);
114  const unsigned int input_channel = input->info()->dimension(channel_idx);
115  const unsigned int input_batches = input->info()->dimension(batches_idx);
116  const TensorShape out_shape(input_channel, 2u, input_batches);
117 
118  // Output auto initialization if not yet initialized
119  if (use_mixed_precision)
120  {
121  auto_init_if_empty(*_output->info(), out_shape, 1, DataType::F32);
122  }
123  else
124  {
125  auto_init_if_empty(*_output->info(), out_shape, 1, input->info()->data_type());
126  }
127  ICLKernel::configure_internal(win);
128  ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info));
129 }

References CLBuildOptions::add_option(), CLBuildOptions::add_option_if(), ARM_COMPUTE_ERROR_ON, ARM_COMPUTE_ERROR_ON_NULLPTR, ARM_COMPUTE_ERROR_THROW_ON, arm_compute::auto_init_if_empty(), arm_compute::BATCHES, arm_compute::calculate_max_window(), arm_compute::CHANNEL, arm_compute::cpu::channel_idx, arm_compute::create_kernel(), arm_compute::cpu::data_layout, arm_compute::F32, 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::NHWC, num_elems_processed_per_iteration, CLBuildOptions::options(), and arm_compute::support::cpp11::to_string().

◆ operator=() [1/2]

CLComputeMeanVariance& operator= ( CLComputeMeanVariance &&  )
default

Default move assignment operator.

◆ operator=() [2/2]

CLComputeMeanVariance& operator= ( const CLComputeMeanVariance &  )
delete

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

◆ 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 137 of file CLInstanceNormalizationLayerKernel.cpp.

138 {
139  ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
140  ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);
141 
142  Window collapsed_window = window.collapse(window, Window::DimZ);
143 
144  // We will process the planes together
145  if (_input->info()->data_layout() == DataLayout::NCHW)
146  {
147  collapsed_window.set(Window::DimX, Window::Dimension(0, 1, 1));
148  collapsed_window.set(Window::DimY, Window::Dimension(0, 1, 1));
149  }
150  else
151  {
152  collapsed_window.set(Window::DimZ, Window::Dimension(0, 1, 1));
153  collapsed_window.set(Window::DimY, Window::Dimension(0, _input->info()->dimension(3), 1));
154  }
155  unsigned int idx = 0;
156  add_4D_tensor_argument(idx, _input, collapsed_window);
157  add_3D_tensor_argument(idx, _output, collapsed_window);
158 
159  enqueue(queue, *this, collapsed_window, lws_hint());
160 }

References ICLKernel::add_3D_tensor_argument(), ICLKernel::add_4D_tensor_argument(), ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW, ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL, Window::collapse(), ITensorInfo::data_layout(), ITensorInfo::dimension(), Window::DimX, Window::DimY, Window::DimZ, arm_compute::enqueue(), ITensor::info(), ICLKernel::lws_hint(), arm_compute::NCHW, Window::set(), and IKernel::window().

◆ validate()

Status validate ( const ITensorInfo *  input,
const ITensorInfo *  output 
)
static

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

Parameters
[in]inputSource tensor info. Data types supported: F16/F32. Data layout supported: NHWC, NCHW
[in]outputDestination tensor info. Data types and data layouts supported: same as input.
Returns
a status

Definition at line 131 of file CLInstanceNormalizationLayerKernel.cpp.

132 {
133  ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_meanvar(input, output));
134  return Status{};
135 }

References ARM_COMPUTE_RETURN_ON_ERROR, and arm_compute::test::validation::input.

The documentation for this class was generated from the following files:
arm_compute::DataLayout::NCHW
@ NCHW
Num samples, channels, height, width.
arm_compute::support::cpp11::to_string
std::string to_string(T &&value)
Convert integer and float values to string.
Definition: StringSupport.h:168
arm_compute::ITensorInfo::data_layout
virtual DataLayout data_layout() const =0
Get the data layout of the tensor.
arm_compute::DataLayoutDimension::CHANNEL
@ CHANNEL
channel
arm_compute::calculate_max_window
Window calculate_max_window(const ValidRegion &valid_region, const Steps &steps, bool skip_border, BorderSize border_size)
Definition: WindowHelpers.cpp:29
arm_compute::DataLayout::NHWC
@ NHWC
Num samples, height, width, channels.
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL
#define ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(k)
Definition: Validate.h:1079
arm_compute::Window::DimX
static constexpr size_t DimX
Alias for dimension 0 also known as X dimension.
Definition: Window.h:43
arm_compute::cpu::data_layout
constexpr auto data_layout
Definition: impl.h:36
ARM_COMPUTE_RETURN_ON_ERROR
#define ARM_COMPUTE_RETURN_ON_ERROR(status)
Checks if a status contains an error and returns it.
Definition: Error.h:205
arm_compute::ITensorInfo::dimension
virtual size_t dimension(size_t index) const =0
Return the size of the requested dimension.
ARM_COMPUTE_ERROR_ON_NULLPTR
#define ARM_COMPUTE_ERROR_ON_NULLPTR(...)
Definition: Validate.h:159
arm_compute::ITensor::info
virtual ITensorInfo * info() const =0
Interface to be implemented by the child class to return the tensor's metadata.
ARM_COMPUTE_ERROR_ON
#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
ARM_COMPUTE_ERROR_THROW_ON
#define ARM_COMPUTE_ERROR_THROW_ON(status)
Definition: Error.h:455
arm_compute::Window::collapse
Window collapse(const Window &full_window, size_t first, size_t last=Coordinates::num_max_dimensions) const
Collapse the dimensions between first and last.
Definition: Window.inl:125
arm_compute::auto_init_if_empty
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: AutoConfiguration.h:43
arm_compute::create_kernel
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:409
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW
#define ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(f, s)
Definition: Validate.h:203
arm_compute::ICLKernel::add_4D_tensor_argument
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.
Definition: ICLKernel.h:244
arm_compute::Window::set
void set(size_t dimension, const Dimension &dim)
Set the values of a given dimension.
Definition: Window.inl:53
arm_compute::Window::DimY
static constexpr size_t DimY
Alias for dimension 1 also known as Y dimension.
Definition: Window.h:45
arm_compute::IKernel::window
const Window & window() const
The maximum window the kernel can be executed on.
Definition: IKernel.cpp:28
arm_compute::get_cl_type_from_data_type
std::string get_cl_type_from_data_type(const DataType &dt)
Translates a tensor data type to the appropriate OpenCL type.
Definition: CLHelpers.cpp:41
arm_compute::ICLKernel::add_3D_tensor_argument
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:234
arm_compute::get_data_layout_dimension_index
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:201
arm_compute::ELEMENTWISE
@ ELEMENTWISE
Elementwise CL kernel type.
Definition: CLTypes.h:83
arm_compute::has_padding_changed
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:491
arm_compute::Window::DimZ
static constexpr size_t DimZ
Alias for dimension 2 also known as Z dimension.
Definition: Window.h:47
arm_compute::ICLKernel::lws_hint
cl::NDRange lws_hint() const
Return the Local-Workgroup-Size hint.
Definition: ICLKernel.h:383
arm_compute::cpu::channel_idx
const size_t channel_idx
Definition: impl.h:39
arm_compute::DataLayoutDimension::BATCHES
@ BATCHES
batches
arm_compute::DataType::F32
@ F32
32-bit floating-point number
num_elems_processed_per_iteration
unsigned int num_elems_processed_per_iteration
Definition: ClIm2ColKernel.cpp:60
arm_compute::get_padding_info
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:476
arm_compute::test::validation::input
auto input
Definition: LSTMLayerQuantized.cpp:486
arm_compute::enqueue
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:33