Compute Library
 21.02
CLGEMMMatrixMultiplyNativeKernel Class Reference

OpenCL kernel to multiply matrices when neither of the input matrices have been reshaped. More...

#include <CLGEMMMatrixMultiplyNativeKernel.h>

Collaboration diagram for CLGEMMMatrixMultiplyNativeKernel:
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Public Member Functions

 CLGEMMMatrixMultiplyNativeKernel ()
 Default Constructor. More...
 
 CLGEMMMatrixMultiplyNativeKernel (const CLGEMMMatrixMultiplyNativeKernel &)=delete
 Prevent instances of this class from being copied (As this class contains pointers) More...
 
CLGEMMMatrixMultiplyNativeKerneloperator= (const CLGEMMMatrixMultiplyNativeKernel &)=delete
 Prevent instances of this class from being copied (As this class contains pointers) More...
 
 CLGEMMMatrixMultiplyNativeKernel (CLGEMMMatrixMultiplyNativeKernel &&)=default
 Allow instances of this class to be moved. More...
 
CLGEMMMatrixMultiplyNativeKerneloperator= (CLGEMMMatrixMultiplyNativeKernel &&)=default
 Allow instances of this class to be moved. More...
 
void configure (const ICLTensor *input0, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, float alpha, float beta, const GEMMLHSMatrixInfo &lhs_info, const GEMMRHSMatrixInfo &rhs_info, const GEMMKernelInfo &gemm_info)
 Initialise the kernel's input and output. More...
 
void configure (const CLCompileContext &compile_context, const ICLTensor *input0, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, float alpha, float beta, const GEMMLHSMatrixInfo &lhs_info, const GEMMRHSMatrixInfo &rhs_info, const GEMMKernelInfo &gemm_info)
 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 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 *input0, const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, float alpha, float beta, const GEMMLHSMatrixInfo &lhs_info, const GEMMRHSMatrixInfo &rhs_info, const GEMMKernelInfo &gemm_info)
 Static function to check if given info will lead to a valid configuration of CLGEMMMatrixMultiplyNativeKernel. 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 to multiply matrices when neither of the input matrices have been reshaped.

Definition at line 36 of file CLGEMMMatrixMultiplyNativeKernel.h.

Constructor & Destructor Documentation

◆ CLGEMMMatrixMultiplyNativeKernel() [1/3]

Default Constructor.

Definition at line 200 of file CLGEMMMatrixMultiplyNativeKernel.cpp.

201  : _input0(nullptr), _input1(nullptr), _input2(nullptr), _output(nullptr), _slide_matrix_b(true), _reinterpret_input_as_3d(false), _reinterpret_output_as_3d(false), _use_dummy_work_items(false),
202  _add_bias(false), _broadcast_bias(false)
203 {
204 }

◆ CLGEMMMatrixMultiplyNativeKernel() [2/3]

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

◆ CLGEMMMatrixMultiplyNativeKernel() [3/3]

Allow instances of this class to be moved.

Member Function Documentation

◆ configure() [1/2]

void configure ( const ICLTensor input0,
const ICLTensor input1,
const ICLTensor input2,
ICLTensor output,
float  alpha,
float  beta,
const GEMMLHSMatrixInfo lhs_info,
const GEMMRHSMatrixInfo rhs_info,
const GEMMKernelInfo gemm_info 
)

Initialise the kernel's input and output.

Parameters
[in]input0Input tensor for the LHS matrix. Data type supported: F32. The number of dimensions for the LHS matrix must be less or equal than 4.
[in]input1Input tensor for the RHS matrix. Data type supported: same as input0. The number of dimensions for the RHS matrix must be less or equal than 3.
[in]input2Input tensor containing the bias matrix. Data type supported: same as input0.
[out]outputOutput tensor info. Data type supported: same as input0
[in]alphaWeight of the matrix product
[in]betaWeight of the matrix bias
[in]lhs_infoLHS matrix information used to retrieve the number of rows and accumulations to be processed by each thread. Only the following values are supported: lhs_info.m0: 1,2,3,4,5,6,7,8 lhs_info.k0: 2,3,4,8,16
[in]rhs_infoRHS matrix information used to retrieve the number of columns and accumulations to be processed by each thread. Only the following values are supported: rhs_info.n0: 2,3,4,8,16 rhs_info.k0: same of lhs_info.k0
[in]gemm_infoGEMM information used to retrieve the original dimensions of the input matrices

Definition at line 206 of file CLGEMMMatrixMultiplyNativeKernel.cpp.

References CLKernelLibrary::get().

209 {
210  configure(CLKernelLibrary::get().get_compile_context(), input0, input1, input2, output, alpha, beta, lhs_info, rhs_info, gemm_info);
211 }
static CLKernelLibrary & get()
Access the KernelLibrary singleton.
void configure(const ICLTensor *input0, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, float alpha, float beta, const GEMMLHSMatrixInfo &lhs_info, const GEMMRHSMatrixInfo &rhs_info, const GEMMKernelInfo &gemm_info)
Initialise the kernel&#39;s input and output.

◆ configure() [2/2]

void configure ( const CLCompileContext compile_context,
const ICLTensor input0,
const ICLTensor input1,
const ICLTensor input2,
ICLTensor output,
float  alpha,
float  beta,
const GEMMLHSMatrixInfo lhs_info,
const GEMMRHSMatrixInfo rhs_info,
const GEMMKernelInfo gemm_info 
)

Initialise the kernel's input and output.

Parameters
[in]compile_contextThe compile context to be used.
[in]input0Input tensor for the LHS matrix. Data type supported: F32. The number of dimensions for the LHS matrix must be less or equal than 4.
[in]input1Input tensor for the RHS matrix. Data type supported: same as input0. The number of dimensions for the RHS matrix must be less or equal than 3.
[in]input2Input tensor containing the bias matrix. Data type supported: same as input0.
[out]outputOutput tensor info. Data type supported: same as input0
[in]alphaWeight of the matrix product
[in]betaWeight of the matrix bias
[in]lhs_infoLHS matrix information used to retrieve the number of rows and accumulations to be processed by each thread. Only the following values are supported: lhs_info.m0: 1,2,3,4,5,6,7,8 lhs_info.k0: 2,3,4,8,16
[in]rhs_infoRHS matrix information used to retrieve the number of columns and accumulations to be processed by each thread. Only the following values are supported: rhs_info.n0: 2,3,4,8,16 rhs_info.k0: same of lhs_info.k0
[in]gemm_infoGEMM information used to retrieve the original dimensions of the input matrices

Definition at line 213 of file CLGEMMMatrixMultiplyNativeKernel.cpp.

References CLBuildOptions::add_option(), CLBuildOptions::add_option_if(), ARM_COMPUTE_ERROR_ON, ARM_COMPUTE_ERROR_ON_NULLPTR, ARM_COMPUTE_ERROR_THROW_ON, GEMMKernelInfo::broadcast_bias, arm_compute::create_kernel(), ITensorInfo::data_type(), GEMMKernelInfo::depth_output_gemm3d, ITensorInfo::dimension(), arm_compute::float_to_string_with_full_precision(), CLKernelLibrary::get(), arm_compute::get_cl_type_from_data_type(), arm_compute::get_padding_info(), arm_compute::has_padding_changed(), ITensor::info(), arm_compute::helpers::float_ops::is_one(), arm_compute::helpers::float_ops::is_zero(), kernel_name, arm_compute::lower_string(), ITensorInfo::num_dimensions(), CLBuildOptions::options(), arm_compute::preferred_dummy_work_items_support(), GEMMKernelInfo::reinterpret_input_as_3d, arm_compute::string_from_activation_func(), arm_compute::string_from_data_type(), arm_compute::support::cpp11::to_string(), and arm_compute::validate_arguments().

217 {
218  ARM_COMPUTE_ERROR_ON_NULLPTR(input0, input1, output);
219 
220  ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input0->info(), input1->info(), (input2 != nullptr ? input2->info() : nullptr), output->info(), alpha, beta, lhs_info, rhs_info, gemm_info));
221 
222  auto padding_info = get_padding_info({ input0, output });
223  _input0 = input0;
224  _input1 = input1;
225  _input2 = helpers::float_ops::is_zero(beta) ? nullptr : input2;
226  _output = output;
227  _reinterpret_input_as_3d = gemm_info.reinterpret_input_as_3d;
228  _reinterpret_output_as_3d = gemm_info.depth_output_gemm3d != 0;
229  _use_dummy_work_items = preferred_dummy_work_items_support(CLKernelLibrary::get().get_device());
230  _add_bias = _input2 != nullptr;
231  _broadcast_bias = gemm_info.broadcast_bias;
232 
233  // In case both input and output have to be reinterpreted as 3D tensors,
234  // force reinterpret_input_as_3d and reinterpret_output_as_3d to be false.
235  if(_reinterpret_input_as_3d == _reinterpret_output_as_3d)
236  {
237  _reinterpret_input_as_3d = false;
238  _reinterpret_output_as_3d = false;
239  }
240 
241  // Check if we need to slide the matrix B
242  const unsigned int num_dimensions_input0 = _input0->info()->num_dimensions();
243  _slide_matrix_b = (_input1->info()->num_dimensions() >= num_dimensions_input0);
244 
245  ElementsProcessed num_elements_processed{};
246 
247  // Configure kernel window
248  auto win_config = validate_and_configure_window(input0->info(), input1->info(), input2 != nullptr ? input2->info() : nullptr, output->info(), lhs_info, rhs_info, gemm_info, num_elements_processed);
249  ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
250  ICLKernel::configure_internal(win_config.second);
251 
252  // If _reinterpret_input_as_3d = _reinterpret_output_as_3d = true,
253  // we will dispatch a batched-GEMM to reduce the complexity of the address calculation within the OpenCL kernel.
254  // This means that the actual m used by the kernel is given by output->info()->dimension(1) and not by gemm_info.m
255  const unsigned int internal_m = _reinterpret_output_as_3d ? gemm_info.m : output->info()->dimension(1);
256 
257  const unsigned int h_gemm_3d = _reinterpret_output_as_3d ? output->info()->dimension(1) : input0->info()->dimension(1);
258  const unsigned int d_gemm_3d = _reinterpret_output_as_3d ? output->info()->dimension(2) : input0->info()->dimension(2);
259 
260  // Calculate partial (store instead of load) M0 and partial N0 for the partial blocks at the end of a row/column if any. This is to avoid padding.
261  const unsigned int partial_store_m0 = internal_m % lhs_info.m0;
262  const unsigned int partial_store_n0 = gemm_info.n % rhs_info.n0;
263 
264  // Shrink M0 to be always <= M (internal_m) to prevent out-of-bounds reads.
265  // NOTE: This might have implications on heuristics and performance
266  const unsigned int internal_m0 = std::min(internal_m, lhs_info.m0);
267 
268  // Create build options
269  CLBuildOptions build_opts;
270  build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input0->info()->data_type()));
271  build_opts.add_option_if(!(helpers::float_ops::is_one(alpha)), "-DALPHA=" + float_to_string_with_full_precision(alpha));
272  build_opts.add_option_if(_input2 != nullptr, "-DBETA=" + float_to_string_with_full_precision(beta));
273  build_opts.add_option_if(helpers::float_ops::is_one(beta), "-DUNIT_BETA");
274  build_opts.add_option_if(gemm_info.broadcast_bias, "-DBROADCAST_BIAS");
275  build_opts.add_option_if(_reinterpret_input_as_3d, "-DREINTERPRET_INPUT_AS_3D");
276  build_opts.add_option_if(_reinterpret_output_as_3d, "-DREINTERPRET_OUTPUT_AS_3D");
277  build_opts.add_option_if(_reinterpret_input_as_3d || _reinterpret_output_as_3d, "-DHEIGHT_GEMM3D=" + support::cpp11::to_string(h_gemm_3d));
278  build_opts.add_option_if(_reinterpret_input_as_3d || _reinterpret_output_as_3d, "-DDEPTH_GEMM3D=" + support::cpp11::to_string(d_gemm_3d));
279  build_opts.add_option_if(!_slide_matrix_b, "-DMATRIX_B_DEPTH=" + support::cpp11::to_string(input1->info()->dimension(2)));
280  build_opts.add_option_if(_use_dummy_work_items, "-DDUMMY_WORK_ITEMS");
281  build_opts.add_option("-DM=" + support::cpp11::to_string(internal_m));
282  build_opts.add_option("-DN=" + support::cpp11::to_string(gemm_info.n));
283  build_opts.add_option("-DK=" + support::cpp11::to_string(gemm_info.k));
284  build_opts.add_option("-DM0=" + support::cpp11::to_string(internal_m0));
285  build_opts.add_option("-DN0=" + support::cpp11::to_string(rhs_info.n0));
286  build_opts.add_option("-DK0=" + support::cpp11::to_string(rhs_info.k0));
287  build_opts.add_option("-DPARTIAL_STORE_M0=" + support::cpp11::to_string(partial_store_m0));
288  build_opts.add_option("-DPARTIAL_STORE_N0=" + support::cpp11::to_string(partial_store_n0));
289  build_opts.add_option_if(gemm_info.activation_info.enabled(), "-DACTIVATION_TYPE=" + lower_string(string_from_activation_func(gemm_info.activation_info.activation())));
290  build_opts.add_option_if(gemm_info.activation_info.enabled(), "-DA_VAL=" + float_to_string_with_full_precision(gemm_info.activation_info.a()));
291  build_opts.add_option_if(gemm_info.activation_info.enabled(), "-DB_VAL=" + float_to_string_with_full_precision(gemm_info.activation_info.b()));
292 
293  std::string kernel_name("gemm_mm_native");
294 
295  // Create kernel
296  _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
297 
298  // Set config_id for enabling LWS tuning
299  _config_id = kernel_name;
300  _config_id += "_";
301  _config_id += (_add_bias ? "add_bias_" : "");
302  _config_id += (_broadcast_bias ? "broadcast_bias_" : "");
303  _config_id += (_reinterpret_input_as_3d ? "3di_" : "");
304  _config_id += (_reinterpret_output_as_3d ? "3do_" : "");
305  _config_id += (gemm_info.activation_info.enabled() ? "fused_activation_" : "");
306  _config_id += lower_string(string_from_data_type(input0->info()->data_type()));
307  _config_id += "_";
308  _config_id += support::cpp11::to_string(output->info()->dimension(1));
309  _config_id += "_";
310  _config_id += support::cpp11::to_string(output->info()->dimension(0));
311  _config_id += "_";
312  _config_id += support::cpp11::to_string(gemm_info.k);
313  _config_id += "_";
314  _config_id += support::cpp11::to_string(output->info()->dimension(2));
315  _config_id += "_";
316  _config_id += support::cpp11::to_string(lhs_info.m0);
317  _config_id += "_";
318  _config_id += support::cpp11::to_string(rhs_info.n0);
319  _config_id += "_";
320  _config_id += support::cpp11::to_string(rhs_info.k0);
321 
323 }
virtual size_t num_dimensions() const =0
The number of dimensions of the tensor (rank)
bool is_one(float a, float epsilon=0.00001f)
Checks if the input floating point number is 1.0f checking if the difference is within a range define...
Definition: float_ops.h:97
bool preferred_dummy_work_items_support(const cl::Device &device)
Helper function to check if "dummy work-items" are preferred to have a power of two NDRange In case d...
Definition: CLHelpers.cpp:361
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
const std::string & string_from_activation_func(ActivationLayerInfo::ActivationFunction act)
Translates a given activation function to a string.
Definition: Utils.cpp:163
static CLKernelLibrary & get()
Access the KernelLibrary singleton.
#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:350
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
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:1262
std::string kernel_name
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
virtual ITensorInfo * info() const =0
Interface to be implemented by the child class to return the tensor&#39;s metadata.
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
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
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, const GEMMLowpOutputStageInfo *output_stage)
bool is_zero(float a, float epsilon=0.00001f)
Checks if the input floating point number is 0.0f checking if the difference is within a range define...
Definition: float_ops.h:109
#define ARM_COMPUTE_ERROR_ON_NULLPTR(...)
Definition: Validate.h:161

◆ 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 344 of file CLGEMMMatrixMultiplyNativeKernel.cpp.

References ICLKernel::add_2D_tensor_argument(), ARM_COMPUTE_ERROR_ON, ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW, ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL, BorderSize::bottom, Window::DimX, Window::DimY, arm_compute::enqueue(), Window::first_slice_window_3D(), ITensor::info(), ICLKernel::lws_hint(), ICLKernel::num_arguments_per_2D_tensor(), ITensorInfo::num_dimensions(), ITensorInfo::padding(), Window::set(), arm_compute::test::validation::reference::slice(), Window::slide_window_slice_3D(), ITensorInfo::strides_in_bytes(), BorderSize::top, and IKernel::window().

345 {
348 
349  if(_input1->info()->num_dimensions() < 3)
350  {
351  // The stride_z for matrix B must be zero if we do not slice
352  ARM_COMPUTE_ERROR_ON(_input1->info()->strides_in_bytes()[3] != 0);
353  }
354 
356  Window slice_matrix_b = slice;
357 
358  slice_matrix_b.set(Window::DimX, Window::Dimension(0, 1, 1));
359  slice_matrix_b.set(Window::DimY, Window::Dimension(0, 1, 1));
360 
361  if(_reinterpret_input_as_3d)
362  {
363  // Pass bottom paddings to the kernel if the input has to be reinterpreted as 3D tensor
364  unsigned int idx0;
365  if(_add_bias)
366  {
367  idx0 = 4 * num_arguments_per_2D_tensor() + 4;
368  }
369  else
370  {
371  idx0 = 3 * num_arguments_per_2D_tensor() + 3;
372  }
373  const unsigned int total_cross_plane_pad = _input0->info()->padding().top + _input0->info()->padding().bottom;
374  _kernel.setArg<cl_uint>(idx0, static_cast<unsigned int>(total_cross_plane_pad));
375  }
376 
377  if(_reinterpret_output_as_3d)
378  {
379  // Pass bottom paddings to the kernel if the output has to be reinterpreted as 3D tensor
380  unsigned int idx0;
381  if(_add_bias)
382  {
383  idx0 = 4 * num_arguments_per_2D_tensor() + 4 + (_reinterpret_input_as_3d ? 1 : 0);
384  }
385  else
386  {
387  idx0 = 3 * num_arguments_per_2D_tensor() + 3 + (_reinterpret_input_as_3d ? 1 : 0);
388  }
389  const unsigned int total_cross_plane_pad = _output->info()->padding().top + _output->info()->padding().bottom;
390  _kernel.setArg<cl_uint>(idx0, static_cast<unsigned int>(total_cross_plane_pad));
391  }
392 
393  do
394  {
395  Window slice_b = slice;
396  // Don't slice matrix B along the z dimension if matrix B has just 2 dimensions and matrix A more than 2
397  // This scenario can happen when the matrix multiplication is used to perform a convolution operation
398  if(!_slide_matrix_b)
399  {
400  slice_b = slice_matrix_b;
401  }
402 
403  unsigned int idx = 0;
404  add_2D_tensor_argument(idx, _input0, slice);
405  add_2D_tensor_argument(idx, _input1, slice_b);
406  if(_add_bias)
407  {
408  add_2D_tensor_argument(idx, _input2, slice);
409  }
410  add_2D_tensor_argument(idx, _output, slice);
411  _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_input0->info()->strides_in_bytes()[2]));
412  _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_input1->info()->strides_in_bytes()[2]));
413  if(_add_bias)
414  {
415  _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_input2->info()->strides_in_bytes()[2]));
416  }
417  _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_output->info()->strides_in_bytes()[2]));
418  enqueue(queue, *this, slice, lws_hint(), _use_dummy_work_items);
419  }
420  while(window.slide_window_slice_3D(slice));
421 }
unsigned int top
top of the border
Definition: Types.h:375
virtual size_t num_dimensions() const =0
The number of dimensions of the tensor (rank)
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
#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
unsigned int bottom
bottom of the border
Definition: Types.h:377
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.
virtual PaddingSize padding() const =0
Padding of tensor.
static constexpr unsigned int num_arguments_per_2D_tensor()
Returns the number of arguments enqueued per 2D tensor object.
Definition: ICLKernel.h:206
bool slide_window_slice_3D(Window &slice) const
Slide the passed 3D window slice.
Definition: Window.h:335
#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
virtual const Strides & strides_in_bytes() const =0
The strides in bytes for accessing each dimension of the tensor.
Window first_slice_window_3D() const
First 3D slice of the window.
Definition: Window.h:291
#define ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(f, s)
Definition: Validate.h:205
SimpleTensor< T > slice(const SimpleTensor< T > &src, Coordinates starts, Coordinates ends)

◆ validate()

Status validate ( const ITensorInfo input0,
const ITensorInfo input1,
const ITensorInfo input2,
const ITensorInfo output,
float  alpha,
float  beta,
const GEMMLHSMatrixInfo lhs_info,
const GEMMRHSMatrixInfo rhs_info,
const GEMMKernelInfo gemm_info 
)
static

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

Parameters
[in]input0Input tensor info for the LHS matrix. Data type supported: F32. The number of dimensions for the LHS matrix must be less or equal than 4.
[in]input1Input tensor info for the RHS matrix. Data type supported: same as input0. The number of dimensions for the RHS matrix must be less or equal than 3.
[in]input2Input tensor info containing the bias matrix. Data type supported: same as input0.
[in]outputOutput tensor info. Data type supported: same as input0
[in]alphaWeight of the matrix product
[in]betaWeight of the matrix bias
[in]lhs_infoLHS matrix information used to retrieve the number of rows and accumulations to be processed by each thread. Only the following values are supported: lhs_info.m0: 1,2,3,4,5,6,7,8 lhs_info.k0: 2,3,4,8,16
[in]rhs_infoRHS matrix information used to retrieve the number of columns and accumulations to be processed by each thread. Only the following values are supported: rhs_info.n0: 2,3,4,8,16 rhs_info.k0: same of lhs_info.k0
[in]gemm_infoGEMM information used to retrieve the original dimensions of the input matrices
Returns
a status

Definition at line 325 of file CLGEMMMatrixMultiplyNativeKernel.cpp.

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

328 {
329  ElementsProcessed num_elements_processed{};
330  ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input0, input1, input2, output, alpha, beta, lhs_info, rhs_info, gemm_info));
331  ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input0->clone().get(),
332  input1->clone().get(),
333  input2 != nullptr ? input2->clone().get() : nullptr,
334  output->clone().get(),
335  lhs_info,
336  rhs_info,
337  gemm_info,
338  num_elements_processed)
339  .first);
340 
341  return Status{};
342 }
#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 *input, const ITensorInfo *bias, const ITensorInfo *output, const GEMMLowpOutputStageInfo *output_stage)

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