Compute Library
 21.02
CLGEMMLowpMatrixBReductionKernel Class Reference

OpenCL kernel used to compute the row-vectors of sums of all the entries in each column of Matrix B. More...

#include <CLGEMMLowpReductionKernel.h>

Collaboration diagram for CLGEMMLowpMatrixBReductionKernel:
[legend]

Public Member Functions

void configure (const ICLTensor *mtx_b, ICLTensor *vector_sum_col, const GEMMLowpReductionKernelInfo &info) override
 Initialise the kernel's input and output. More...
 
void configure (const CLCompileContext &compile_context, const ICLTensor *mtx_b, ICLTensor *vector_sum_col, const GEMMLowpReductionKernelInfo &info) override
 Initialise the kernel's input and output. 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 ICLGEMMLowpReductionKernel
 ICLGEMMLowpReductionKernel ()
 Constructor. More...
 
 ICLGEMMLowpReductionKernel (const ICLGEMMLowpReductionKernel &)=delete
 Prevent instances of this class from being copied (As this class contains pointers) More...
 
ICLGEMMLowpReductionKerneloperator= (const ICLGEMMLowpReductionKernel &)=delete
 Prevent instances of this class from being copied (As this class contains pointers) More...
 
 ICLGEMMLowpReductionKernel (ICLGEMMLowpReductionKernel &&)=default
 Allow instances of this class to be moved. More...
 
ICLGEMMLowpReductionKerneloperator= (ICLGEMMLowpReductionKernel &&)=default
 Allow instances of this class to be moved. 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 *mtx_b, const ITensorInfo *vector_sum_col, const GEMMLowpReductionKernelInfo &info)
 Static function to check if given info will lead to a valid configuration of CLGEMMLowpMatrixBReductionKernel. 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

OpenCL kernel used to compute the row-vectors of sums of all the entries in each column of Matrix B.

Note
This stage is needed to handle the offset of matrix product https://github.com/google/gemmlowp/blob/master/doc/low-precision.md

Definition at line 132 of file CLGEMMLowpReductionKernel.h.

Member Function Documentation

◆ configure() [1/2]

void configure ( const ICLTensor mtx_b,
ICLTensor vector_sum_col,
const GEMMLowpReductionKernelInfo info 
)
overridevirtual

Initialise the kernel's input and output.

Parameters
[in]mtx_bInput tensor. Data type supported: Data type supported: QASYMM8/QASYMM8_SIGNED/QSYMM8/QSYMM8_PER_CHANNEL.
[out]vector_sum_colOutput row-vector of sums of all the entries in each column of mtx_b. Data type supported: S32
[in]infoKernel metadata:
  • k Number of matrix columns/rows depending on the type of reduction.
  • is_reshaped True if the matrix has been reshaped.
  • scalar Scalar value to multiply each reduced column/row by.
  • mul_byscalar True if each reduced column/row must be multiplied by a scalar value.

Implements ICLGEMMLowpReductionKernel.

Definition at line 151 of file CLGEMMLowpReductionKernel.cpp.

References ICLGEMMLowpReductionKernel::configure(), and CLKernelLibrary::get().

152 {
153  configure(CLKernelLibrary::get().get_compile_context(), mtx_b, vector_sum_col, info);
154 }
void configure(const ICLTensor *mtx_b, ICLTensor *vector_sum_col, const GEMMLowpReductionKernelInfo &info) override
Initialise the kernel&#39;s input and output.
static CLKernelLibrary & get()
Access the KernelLibrary singleton.
ScaleKernelInfo info(interpolation_policy, default_border_mode, PixelValue(), sampling_policy, false)

◆ configure() [2/2]

void configure ( const CLCompileContext compile_context,
const ICLTensor mtx_b,
ICLTensor vector_sum_col,
const GEMMLowpReductionKernelInfo info 
)
overridevirtual

Initialise the kernel's input and output.

Parameters
[in]compile_contextThe compile context to be used.
[in]mtx_bInput tensor. Data type supported: Data type supported: QASYMM8/QASYMM8_SIGNED/QSYMM8/QSYMM8_PER_CHANNEL.
[out]vector_sum_colOutput row-vector of sums of all the entries in each column of mtx_b. Data type supported: S32
[in]infoKernel metadata:
  • k Number of matrix columns/rows depending on the type of reduction.
  • is_reshaped True if the matrix has been reshaped.
  • scalar Scalar value to multiply each reduced column/row by.
  • mul_byscalar True if each reduced column/row must be multiplied by a scalar value.

Implements ICLGEMMLowpReductionKernel.

Definition at line 156 of file CLGEMMLowpReductionKernel.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::create_kernel(), ITensorInfo::data_type(), ITensorInfo::dimension(), arm_compute::get_cl_dot8_acc_type_from_data_type(), arm_compute::get_cl_type_from_data_type(), arm_compute::get_padding_info(), arm_compute::has_padding_changed(), ITensor::info(), GEMMLowpReductionKernelInfo::mul_by_scalar, num_elems_processed_per_iteration, arm_compute::S32, GEMMLowpReductionKernelInfo::scalar, and arm_compute::support::cpp11::to_string().

157 {
158  ARM_COMPUTE_ERROR_ON_NULLPTR(mtx_b, vector_sum_col);
159  ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_matrix_b_reduction(mtx_b->info(), vector_sum_col->info()));
160 
161  _input = mtx_b;
162  _output = vector_sum_col;
163 
164  // Output auto initialization if not yet initialized
165  auto_init_if_empty(*_output->info(), TensorShape(mtx_b->info()->dimension(0)), 1, DataType::S32);
166 
167  auto padding_info = get_padding_info({ mtx_b, vector_sum_col });
168 
169  const unsigned int num_elems_processed_per_iteration = adjust_vec_size(16, mtx_b->info()->dimension(0));
170 
171  // Set the arguments to pass at compile time
172  CLBuildOptions build_opts;
173  build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration));
174  build_opts.add_option("-DVEC_SIZE_LEFTOVER=" + support::cpp11::to_string(mtx_b->info()->dimension(0) % num_elems_processed_per_iteration));
175  build_opts.add_option("-DCOLS_B=" + support::cpp11::to_string(mtx_b->info()->dimension(0)));
176  build_opts.add_option("-DROWS_B=" + support::cpp11::to_string(mtx_b->info()->dimension(1)));
177  build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(mtx_b->info()->data_type()));
178  build_opts.add_option("-DACC_DATA_TYPE=" + get_cl_dot8_acc_type_from_data_type(mtx_b->info()->data_type()));
179  build_opts.add_option_if(info.mul_by_scalar, "-DSCALAR=" + support::cpp11::to_string(info.scalar));
180 
181  // Create kernel
182  _kernel = create_kernel(compile_context, "gemmlowp_matrix_b_reduction", build_opts.options());
183 
184  // Configure kernel window
185  Window win = calculate_max_window(*_output->info(), Steps(num_elems_processed_per_iteration));
186  ICLKernel::configure_internal(win);
187 
189 }
Window calculate_max_window(const ValidRegion &valid_region, const Steps &steps, bool skip_border, BorderSize border_size)
std::string get_cl_dot8_acc_type_from_data_type(const DataType &dt)
Translates a tensor data type to the appropriate OpenCL dot8 accumulator type.
Definition: CLHelpers.cpp:173
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
1 channel, 1 S32 per channel
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
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
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:528
ScaleKernelInfo info(interpolation_policy, default_border_mode, PixelValue(), sampling_policy, false)
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:513
unsigned int num_elems_processed_per_iteration
#define ARM_COMPUTE_ERROR_ON_NULLPTR(...)
Definition: Validate.h:161
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:1358

◆ 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 199 of file CLGEMMLowpReductionKernel.cpp.

References ICLKernel::add_2D_tensor_argument(), ICLKernel::add_3D_tensor_argument(), ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW, ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL, Window::collapse_if_possible(), Window::DimY, Window::DimZ, arm_compute::enqueue(), Window::first_slice_window_2D(), ICLKernel::lws_hint(), Window::set(), Window::slide_window_slice_2D(), and IKernel::window().

200 {
203 
205 
206  Window slice_out = collapsed.first_slice_window_2D();
207  Window slice_in = slice_out;
208 
209  slice_in.set(Window::DimY, Window::Dimension(0, 0, 0));
210  slice_in.set(Window::DimZ, Window::Dimension(0, 0, 0));
211 
212  do
213  {
214  unsigned int idx = 0;
215  add_3D_tensor_argument(idx, _input, slice_in);
216  add_2D_tensor_argument(idx, _output, slice_out);
217  enqueue(queue, *this, slice_out, lws_hint());
218  }
219  while(collapsed.slide_window_slice_2D(slice_out));
220 }
Window first_slice_window_2D() const
First 2D slice of the window.
Definition: Window.h:283
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
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
void set(size_t dimension, const Dimension &dim)
Set the values of a given dimension.
Definition: Window.inl:49
#define ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(k)
Definition: Validate.h:941
static constexpr size_t DimY
Alias for dimension 1 also known as Y dimension.
Definition: Window.h:45
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:148
static constexpr size_t DimZ
Alias for dimension 2 also known as Z dimension.
Definition: Window.h:47
#define ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(f, s)
Definition: Validate.h:205

◆ validate()

Status validate ( const ITensorInfo mtx_b,
const ITensorInfo vector_sum_col,
const GEMMLowpReductionKernelInfo info 
)
static

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

Parameters
[in]mtx_bInput tensor. Data type supported: Data type supported: QASYMM8/QASYMM8_SIGNED/QSYMM8/QSYMM8_PER_CHANNEL.
[in]vector_sum_colOutput row-vector of sums of all the entries in each column of mtx_b. Data type supported: S32
[in]infoKernel metadata:
  • k Number of matrix columns/rows depending on the type of reduction.
  • is_reshaped True if the matrix has been reshaped.
  • scalar Scalar value to multiply each reduced column/row by.
  • mul_byscalar True if each reduced column/row must be multiplied by a scalar value.
Returns
a status

Definition at line 191 of file CLGEMMLowpReductionKernel.cpp.

References ARM_COMPUTE_RETURN_ON_ERROR, and ARM_COMPUTE_UNUSED.

Referenced by CLGEMMLowpMatrixMultiplyCore::validate().

192 {
194  ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_matrix_b_reduction(mtx_b, vector_sum_col));
195 
196  return Status{};
197 }
#define ARM_COMPUTE_RETURN_ON_ERROR(status)
Checks if a status contains an error and returns it.
Definition: Error.h:204
#define ARM_COMPUTE_UNUSED(...)
To avoid unused variables warnings.
Definition: Error.h:152
ScaleKernelInfo info(interpolation_policy, default_border_mode, PixelValue(), sampling_policy, false)

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