Compute Library
 19.11
CLGEMMMatrixMultiplyReshapedOnlyRHSKernel Class Reference

OpenCL kernel to multiply matrices when only the input matrix RHS (input1) has been reshaped. More...

#include <CLGEMMMatrixMultiplyReshapedOnlyRHSKernel.h>

Collaboration diagram for CLGEMMMatrixMultiplyReshapedOnlyRHSKernel:
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Public Member Functions

 CLGEMMMatrixMultiplyReshapedOnlyRHSKernel ()
 Default Constructor. More...
 
 CLGEMMMatrixMultiplyReshapedOnlyRHSKernel (const CLGEMMMatrixMultiplyReshapedOnlyRHSKernel &)=delete
 Prevent instances of this class from being copied (As this class contains pointers) More...
 
CLGEMMMatrixMultiplyReshapedOnlyRHSKerneloperator= (const CLGEMMMatrixMultiplyReshapedOnlyRHSKernel &)=delete
 Prevent instances of this class from being copied (As this class contains pointers) More...
 
 CLGEMMMatrixMultiplyReshapedOnlyRHSKernel (CLGEMMMatrixMultiplyReshapedOnlyRHSKernel &&)=default
 Allow instances of this class to be moved. More...
 
CLGEMMMatrixMultiplyReshapedOnlyRHSKerneloperator= (CLGEMMMatrixMultiplyReshapedOnlyRHSKernel &&)=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 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...
 
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...
 
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<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...
 
template<unsigned int dimension_size>
void add_tensor_argument (unsigned &idx, const ICLTensor *tensor, const Window &window)
 
- 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 CLGEMMMatrixMultiplyReshapedOnlyRHSKernel. 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 only the input matrix RHS (input1) has been reshaped.

Note
The input matrix input1 must be reshaped through CLGEMMReshapeRHSMatrixKernel

Definition at line 39 of file CLGEMMMatrixMultiplyReshapedOnlyRHSKernel.h.

Constructor & Destructor Documentation

◆ CLGEMMMatrixMultiplyReshapedOnlyRHSKernel() [1/3]

Default Constructor.

Definition at line 210 of file CLGEMMMatrixMultiplyReshapedOnlyRHSKernel.cpp.

211  : _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),
212  _add_bias(false), _broadcast_bias(false)
213 {
214 }

◆ CLGEMMMatrixMultiplyReshapedOnlyRHSKernel() [2/3]

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

◆ CLGEMMMatrixMultiplyReshapedOnlyRHSKernel() [3/3]

Allow instances of this class to be moved.

Member Function Documentation

◆ configure()

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 containing the LHS matrix. Data type supported: F16/F32. The number of dimensions for the LHS matrix must be less or equal than 4.
[in]input1Input tensor containing the RHS reshaped 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 to store the result of matrix multiplication. 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 to be processed by each thread. Only the following values are supported: lhs_info.m0: 1,2,3,4,5,6,7,8
[in]rhs_infoRHS matrix information used for reshaping the input1 tensor. Only the following values are supported: rhs_info.k0: 2,3,4,8,16 rhs_info.n0: 2,3,4,8,16 rhs_info.transpose: true,false
[in]gemm_infoGEMM information used to retrieve the original dimensions of the input matrices

Definition at line 216 of file CLGEMMMatrixMultiplyReshapedOnlyRHSKernel.cpp.

219 {
220  ARM_COMPUTE_ERROR_ON_NULLPTR(input0, input1, output);
221 
222  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));
223 
224  _input0 = input0;
225  _input1 = input1;
226  _input2 = helpers::float_ops::is_zero(beta) ? nullptr : input2;
227  _output = output;
228  _reinterpret_input_as_3d = gemm_info.reinterpret_input_as_3d;
229  _reinterpret_output_as_3d = gemm_info.depth_output_gemm3d != 0;
230  _use_dummy_work_items = preferred_dummy_work_items_support(CLKernelLibrary::get().get_device());
231  _add_bias = _input2 != nullptr;
232  _broadcast_bias = gemm_info.broadcast_bias;
233 
234  // In case both input and output have to be reinterpreted as 3D tensors,
235  // force reinterpret_input_as_3d and reinterpret_output_as_3d to be false.
236  if(_reinterpret_input_as_3d == _reinterpret_output_as_3d)
237  {
238  _reinterpret_input_as_3d = false;
239  _reinterpret_output_as_3d = false;
240  }
241 
242  // Check if we need to slide the matrix B
243  const unsigned int num_dimensions_input0 = _input0->info()->num_dimensions();
244  _slide_matrix_b = (_input1->info()->num_dimensions() >= num_dimensions_input0);
245 
246  ElementsProcessed num_elements_processed{};
247 
248  // Configure kernel window
249  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);
250  ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
251  ICLKernel::configure_internal(win_config.second);
252 
253  // If _reinterpret_input_as_3d = _reinterpret_output_as_3d = true,
254  // we will dispatch a batched-GEMM to reduce the complexity of the address calculation within the OpenCL kernel.
255  // This means that the actual m used by the kernel is given by output->info()->dimension(1) and not by gemm_info.m
256  const unsigned int internal_m = _reinterpret_output_as_3d ? gemm_info.m : output->info()->dimension(1);
257 
258  const unsigned int h_gemm_3d = _reinterpret_output_as_3d ? output->info()->dimension(1) : input0->info()->dimension(1);
259  const unsigned int d_gemm_3d = _reinterpret_output_as_3d ? output->info()->dimension(2) : input0->info()->dimension(2);
260 
261  // Create build options
262  CLBuildOptions build_opts;
263  build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input0->info()->data_type()));
264  build_opts.add_option_if(!(helpers::float_ops::is_one(alpha)), "-DALPHA=" + float_to_string_with_full_precision(alpha));
265  build_opts.add_option_if(_input2 != nullptr, "-DBETA=" + float_to_string_with_full_precision(beta));
266  build_opts.add_option_if(helpers::float_ops::is_one(beta), "-DUNIT_BETA");
267  build_opts.add_option_if(_reinterpret_input_as_3d, "-DREINTERPRET_INPUT_AS_3D");
268  build_opts.add_option_if(_reinterpret_output_as_3d, "-DREINTERPRET_OUTPUT_AS_3D");
269  build_opts.add_option_if(gemm_info.broadcast_bias, "-DBROADCAST_BIAS");
270  build_opts.add_option_if(_reinterpret_input_as_3d || _reinterpret_output_as_3d, "-DHEIGHT_GEMM3D=" + support::cpp11::to_string(h_gemm_3d));
271  build_opts.add_option_if(_reinterpret_input_as_3d || _reinterpret_output_as_3d, "-DDEPTH_GEMM3D=" + support::cpp11::to_string(d_gemm_3d));
272  build_opts.add_option_if(!_slide_matrix_b, "-DMATRIX_B_DEPTH=" + support::cpp11::to_string(input1->info()->dimension(2)));
273  build_opts.add_option_if(rhs_info.interleave, "-DRHS_INTERLEAVE");
274  build_opts.add_option_if(_use_dummy_work_items, "-DDUMMY_WORK_ITEMS");
275  build_opts.add_option("-DM=" + support::cpp11::to_string(internal_m));
276  build_opts.add_option("-DN=" + support::cpp11::to_string(gemm_info.n));
277  build_opts.add_option("-DK=" + support::cpp11::to_string(gemm_info.k));
278  build_opts.add_option("-DM0=" + support::cpp11::to_string(lhs_info.m0));
279  build_opts.add_option("-DN0=" + support::cpp11::to_string(rhs_info.n0));
280  build_opts.add_option("-DK0=" + support::cpp11::to_string(rhs_info.k0));
281  build_opts.add_option("-DH0=" + support::cpp11::to_string(rhs_info.h0));
282  build_opts.add_option_if(gemm_info.activation_info.enabled(), "-DACTIVATION_TYPE=" + lower_string(string_from_activation_func(gemm_info.activation_info.activation())));
283  build_opts.add_option_if(gemm_info.activation_info.enabled(), "-DA_VAL=" + float_to_string_with_full_precision(gemm_info.activation_info.a()));
284  build_opts.add_option_if(gemm_info.activation_info.enabled(), "-DB_VAL=" + float_to_string_with_full_precision(gemm_info.activation_info.b()));
285 
286  std::string kernel_name("gemm_mm_reshaped_only_rhs_");
287  kernel_name += rhs_info.transpose ? "t" : "nt";
288 
289  // Create kernel
290  _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
291 
292  // Set config_id for enabling LWS tuning
293  _config_id = kernel_name;
294  _config_id += "_";
295  _config_id += (_add_bias ? "add_bias_" : "");
296  _config_id += (_broadcast_bias ? "broadcast_bias_" : "");
297  _config_id += (_reinterpret_input_as_3d ? "3di_" : "");
298  _config_id += (_reinterpret_output_as_3d ? "3do_" : "");
299  _config_id += (gemm_info.activation_info.enabled() ? "fused_activation_" : "");
300  _config_id += lower_string(string_from_data_type(input0->info()->data_type()));
301  _config_id += "_";
302  _config_id += support::cpp11::to_string(output->info()->dimension(1));
303  _config_id += "_";
304  _config_id += support::cpp11::to_string(output->info()->dimension(0));
305  _config_id += "_";
306  _config_id += support::cpp11::to_string(gemm_info.k);
307  _config_id += "_";
308  _config_id += support::cpp11::to_string(output->info()->dimension(2));
309  _config_id += "_";
310  _config_id += support::cpp11::to_string(lhs_info.m0);
311  _config_id += "_";
312  _config_id += support::cpp11::to_string(rhs_info.n0);
313  _config_id += "_";
314  _config_id += support::cpp11::to_string(rhs_info.k0);
315  _config_id += "_";
316  _config_id += support::cpp11::to_string(rhs_info.h0);
317  _config_id += "_";
318  _config_id += support::cpp11::to_string(rhs_info.interleave);
319 }
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:325
std::string to_string(T &&value)
Convert integer and float values to string.
const std::string & string_from_activation_func(ActivationLayerInfo::ActivationFunction act)
Translates a given activation function to a string.
Definition: Utils.cpp:172
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:333
const std::string & string_from_data_type(DataType dt)
Convert a data type identity into a string.
Definition: Utils.cpp:144
std::string float_to_string_with_full_precision(float val)
Create a string with the float in full precision.
Definition: Utils.h:1099
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's metadata.
std::unique_ptr< Kernel > create_kernel()
Helper function to create and return a unique_ptr pointed to a CL/GLES kernel object.
Definition: Helpers.h:86
#define ARM_COMPUTE_ERROR_ON_NULLPTR(...)
Definition: Validate.h:161
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

References CLBuildOptions::add_option(), CLBuildOptions::add_option_if(), arm_compute::test::validation::alpha, 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(), ITensor::info(), arm_compute::helpers::float_ops::is_one(), arm_compute::helpers::float_ops::is_zero(), 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(), and arm_compute::support::cpp11::to_string().

◆ 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.

Implements ICLKernel.

Definition at line 340 of file CLGEMMMatrixMultiplyReshapedOnlyRHSKernel.cpp.

341 {
344 
345  if(_input1->info()->num_dimensions() < 3)
346  {
347  // The stride_z for matrix B must be zero if we do not slice
348  ARM_COMPUTE_ERROR_ON(_input1->info()->strides_in_bytes()[3] != 0);
349  }
350 
352  Window slice_matrix_b = slice;
353 
354  slice_matrix_b.set(Window::DimX, Window::Dimension(0, 1, 1));
355  slice_matrix_b.set(Window::DimY, Window::Dimension(0, 1, 1));
356 
357  if(_reinterpret_input_as_3d)
358  {
359  // Pass bottom paddings to the kernel if the input has to be reinterpreted as 3D tensor
360  unsigned int idx0;
361  if(_add_bias)
362  {
363  idx0 = 4 * num_arguments_per_2D_tensor() + 4;
364  }
365  else
366  {
367  idx0 = 3 * num_arguments_per_2D_tensor() + 3;
368  }
369  const unsigned int total_cross_plane_pad = _input0->info()->padding().top + _input0->info()->padding().bottom;
370  _kernel.setArg<cl_uint>(idx0, static_cast<unsigned int>(total_cross_plane_pad));
371  }
372 
373  if(_reinterpret_output_as_3d)
374  {
375  // Pass bottom paddings to the kernel if the output has to be reinterpreted as 3D tensor
376  unsigned int idx0;
377  if(_add_bias)
378  {
379  idx0 = 4 * num_arguments_per_2D_tensor() + 4 + (_reinterpret_input_as_3d ? 1 : 0);
380  }
381  else
382  {
383  idx0 = 3 * num_arguments_per_2D_tensor() + 3 + (_reinterpret_input_as_3d ? 1 : 0);
384  }
385  const unsigned int total_cross_plane_pad = _output->info()->padding().top + _output->info()->padding().bottom;
386  _kernel.setArg<cl_uint>(idx0, static_cast<unsigned int>(total_cross_plane_pad));
387  }
388 
389  do
390  {
391  Window slice_b = slice;
392  // Don't slice matrix B along the z dimension if matrix B has just 2 dimensions and matrix A more than 2
393  // This scenario can happen when the matrix multiplication is used to perform a convolution operation
394  if(!_slide_matrix_b)
395  {
396  slice_b = slice_matrix_b;
397  }
398 
399  unsigned int idx = 0;
400  add_2D_tensor_argument(idx, _input0, slice);
401  add_2D_tensor_argument(idx, _input1, slice_b);
402  add_2D_tensor_argument_if((_add_bias), idx, _input2, slice);
403  add_2D_tensor_argument(idx, _output, slice);
404  _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_input0->info()->strides_in_bytes()[2]));
405  _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_input1->info()->strides_in_bytes()[2]));
406  if(_add_bias)
407  {
408  _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_input2->info()->strides_in_bytes()[2]));
409  }
410  _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_output->info()->strides_in_bytes()[2]));
411  enqueue(queue, *this, slice, lws_hint(), _use_dummy_work_items);
412  }
414 }
unsigned int top
top of the border
Definition: Types.h:348
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 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 ...
Definition: ICLKernel.h:145
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:39
cl::NDRange lws_hint() const
Return the Local-Workgroup-Size hint.
Definition: ICLKernel.h:247
#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:350
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'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:192
bool slide_window_slice_3D(Window &slice) const
Slide the passed 3D window slice.
Definition: Window.h:333
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's parameters to the object's kernel's arguments starting from the index idx.
Definition: ICLKernel.h:134
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:289
#define ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(f, s)
Definition: Validate.h:205
#define ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(k)
Definition: Validate.h:941
SimpleTensor< T > slice(const SimpleTensor< T > &src, Coordinates starts, Coordinates ends)

References ICLKernel::add_2D_tensor_argument(), ICLKernel::add_2D_tensor_argument_if(), 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().

◆ 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 CLGEMMMatrixMultiplyReshapedOnlyRHSKernel.

Parameters
[in]input0Input tensor info for the LHS matrix. Data type supported: F16/F32. The number of dimensions for the LHS matrix must be less or equal than 4.
[in]input1Input tensor info for the RHS reshaped 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 to be processed by each thread. Only the following values are supported: lhs_info.m0: 1,2,3,4,5,6,7,8
[in]rhs_infoRHS matrix information used for reshaping the input1 tensor. Only the following values are supported: rhs_info.k0: 2,3,4,8,16 rhs_info.n0: 2,3,4,8,16 rhs_info.transpose: true,false
[in]gemm_infoGEMM information used to retrieve the original dimensions of the input matrices
Returns
a status

Definition at line 321 of file CLGEMMMatrixMultiplyReshapedOnlyRHSKernel.cpp.

324 {
325  ElementsProcessed num_elements_processed{};
326  ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input0, input1, input2, output, alpha, beta, lhs_info, rhs_info, gemm_info));
327  ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input0->clone().get(),
328  input1->clone().get(),
329  input2 != nullptr ? input2->clone().get() : nullptr,
330  output->clone().get(),
331  lhs_info,
332  rhs_info,
333  gemm_info,
334  num_elements_processed)
335  .first);
336 
337  return Status{};
338 }
#define ARM_COMPUTE_RETURN_ON_ERROR(status)
Checks if a status contains an error and returns it.
Definition: Error.h:204

References arm_compute::test::validation::alpha, ARM_COMPUTE_RETURN_ON_ERROR, and ICloneable< T >::clone().


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