Compute Library
 21.11
ClGemmLowpMatrixAReductionKernel Class Reference

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

#include <ClGemmLowpReductionKernel.h>

Collaboration diagram for ClGemmLowpMatrixAReductionKernel:
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Public Member Functions

void configure (const CLCompileContext &compile_context, const ITensorInfo *mtx_a, ITensorInfo *vector_sum_row, const GEMMLowpReductionKernelInfo &info) override
 Initialise the kernel's input and output. More...
 
void run_op (ITensorPack &tensors, 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 ()
 
 ARM_COMPUTE_DISALLOW_COPY_ALLOW_MOVE (IClGemmLowpReductionKernel)
 
- 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...
 
virtual void run (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...
 
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 *mtx_a, const ITensorInfo *vector_sum_row, const GEMMLowpReductionKernelInfo &info)
 Static function to check if given info will lead to a valid configuration. 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 row of Matrix A.

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 63 of file ClGemmLowpReductionKernel.h.

Member Function Documentation

◆ configure()

void configure ( const CLCompileContext compile_context,
const ITensorInfo mtx_a,
ITensorInfo vector_sum_row,
const GEMMLowpReductionKernelInfo info 
)
overridevirtual

Initialise the kernel's input and output.

Parameters
[in]compile_contextThe compile context to be used.
[in]mtx_aInput tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/QSYMM8.
[out]vector_sum_rowOutput row-vector of sums of all the entries in each row of mtx_a. 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 76 of file ClGemmLowpReductionKernel.cpp.

References CLBuildOptions::add_option(), 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::dot8_supported(), CLKernelLibrary::get(), 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(), kernel_name, GEMMLowpReductionKernelInfo::mul_by_scalar, arm_compute::S32, GEMMLowpReductionKernelInfo::scalar, and arm_compute::support::cpp11::to_string().

77 {
78  // Perform validate step
79  ARM_COMPUTE_ERROR_ON_NULLPTR(mtx_a, vector_sum_row);
80  ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_matrix_a_reduction(mtx_a, vector_sum_row));
81 
82  // Output auto initialization if not yet initialized
83  auto_init_if_empty(*vector_sum_row, TensorShape(mtx_a->dimension(1)), 1, DataType::S32);
84 
85  auto padding_info = get_padding_info({ mtx_a, vector_sum_row });
86 
87  // Set the arguments to pass at compile time
88  CLBuildOptions build_opts;
89  build_opts.add_option("-DCOLS_A=" + support::cpp11::to_string(mtx_a->dimension(0)));
90  build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(mtx_a->data_type()));
91  build_opts.add_option("-DACC_DATA_TYPE=" + get_cl_dot8_acc_type_from_data_type(mtx_a->data_type()));
92  build_opts.add_option_if(info.mul_by_scalar, "-DSCALAR=" + support::cpp11::to_string(info.scalar));
93 
94  const bool is_dot8_supported = dot8_supported(CLKernelLibrary::get().get_device());
95 
96  std::string kernel_name = "gemmlowp_matrix_a_reduction" + std::string(is_dot8_supported ? "_dot8" : "");
97 
98  // Create kernel
99  _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
100 
101  // Configure kernel window
102  // This kernel does not need padding
103  Window win = calculate_max_window(*vector_sum_row, Steps());
104  ICLKernel::configure_internal(win);
105 
106  _config_id = kernel_name;
107  _config_id += "_";
108  _config_id += support::cpp11::to_string(mtx_a->dimension(0));
109  _config_id += "_";
110  _config_id += support::cpp11::to_string(mtx_a->dimension(1));
111  _config_id += "_";
112  _config_id += support::cpp11::to_string(mtx_a->dimension(2));
113 
115 }
Window calculate_max_window(const ValidRegion &valid_region, const Steps &steps, bool skip_border, BorderSize border_size)
bool dot8_supported(const cl::Device &device)
Helper function to check whether the cl_arm_integer_dot_product_int8 extension is supported...
Definition: CLHelpers.cpp:241
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:175
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
static CLKernelLibrary & get()
Access the KernelLibrary singleton.
#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:391
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:533
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:518
#define ARM_COMPUTE_ERROR_ON_NULLPTR(...)
Definition: Validate.h:157
std::string kernel_name

◆ run_op()

void run_op ( ITensorPack tensors,
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]tensorsA vector containing the tensors to operato on.
[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 125 of file ClGemmLowpReductionKernel.cpp.

References arm_compute::ACL_DST, arm_compute::ACL_SRC, 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::DimX, Window::DimY, Window::DimZ, arm_compute::enqueue(), Window::first_slice_window_2D(), ITensorPack::get_const_tensor(), ITensorPack::get_tensor(), ICLKernel::lws_hint(), Window::set(), and IKernel::window().

126 {
129 
130  const auto src = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC));
131  auto dst = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_DST));
132 
134  Window slice_in = collapsed.first_slice_window_2D();
135  Window slice_out = collapsed.first_slice_window_2D();
136 
137  // Setup input slice. Its dimensions are increased in the cl kernel.
138  slice_in.set(Window::DimX, Window::Dimension(0, 0, 0));
139  slice_in.set(Window::DimY, Window::Dimension(0, 0, 0));
140  slice_in.set(Window::DimZ, Window::Dimension(0, 0, 0));
141 
142  do
143  {
144  unsigned int idx = 0;
145  add_3D_tensor_argument(idx, src, slice_in);
146  add_2D_tensor_argument(idx, dst, slice_out);
147  enqueue(queue, *this, slice_out, lws_hint());
148  }
149  while(collapsed.slide_window_slice_2D(slice_out));
150 }
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(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:318
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:214
SimpleTensor< float > src
Definition: DFT.cpp:155
static constexpr size_t DimX
Alias for dimension 0 also known as X dimension.
Definition: Window.h:43
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:915
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:190
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:201

◆ validate()

Status validate ( const ITensorInfo mtx_a,
const ITensorInfo vector_sum_row,
const GEMMLowpReductionKernelInfo info 
)
static

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

Similar to ClGemmLowpQuantizeDownInt32ScaleByFixedPointKernel::configure()

Returns
a status

Definition at line 117 of file ClGemmLowpReductionKernel.cpp.

References ARM_COMPUTE_RETURN_ON_ERROR, and ARM_COMPUTE_UNUSED.

Referenced by ClGemmLowpMatrixMultiplyCore::validate(), and CLQLSTMLayer::validate().

118 {
120  ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_matrix_a_reduction(mtx_a, vector_sum_row));
121 
122  return Status{};
123 }
#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: