Compute Library
 19.08
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 209 of file CLGEMMMatrixMultiplyReshapedOnlyRHSKernel.cpp.

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

◆ 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: 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 215 of file CLGEMMMatrixMultiplyReshapedOnlyRHSKernel.cpp.

218 {
219  ARM_COMPUTE_ERROR_ON_NULLPTR(input0, input1, output);
220 
221  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));
222 
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  // Create build options
253  CLBuildOptions build_opts;
254  build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input0->info()->data_type()));
255  build_opts.add_option_if(!(helpers::float_ops::is_one(alpha)), "-DALPHA=" + float_to_string_with_full_precision(alpha));
256  build_opts.add_option_if(_input2 != nullptr, "-DBETA=" + float_to_string_with_full_precision(beta));
257  build_opts.add_option_if(helpers::float_ops::is_one(beta), "-DUNIT_BETA");
258  build_opts.add_option_if(_reinterpret_input_as_3d, "-DREINTERPRET_INPUT_AS_3D");
259  build_opts.add_option_if(_reinterpret_output_as_3d, "-DREINTERPRET_OUTPUT_AS_3D");
260  build_opts.add_option_if(gemm_info.broadcast_bias, "-DBROADCAST_BIAS");
261  build_opts.add_option_if(_reinterpret_input_as_3d || _reinterpret_output_as_3d, "-DHEIGHT_GEMM3D=" + support::cpp11::to_string(output->info()->dimension(1)));
262  build_opts.add_option_if(_reinterpret_input_as_3d || _reinterpret_output_as_3d, "-DDEPTH_GEMM3D=" + support::cpp11::to_string(output->info()->dimension(2)));
263  build_opts.add_option_if(!_slide_matrix_b, "-DMATRIX_B_DEPTH=" + support::cpp11::to_string(input1->info()->dimension(2)));
264  build_opts.add_option_if(rhs_info.interleave, "-DRHS_INTERLEAVE");
265  build_opts.add_option_if(_use_dummy_work_items, "-DDUMMY_WORK_ITEMS");
266  build_opts.add_option("-DM=" + support::cpp11::to_string(input0->info()->dimension(1)));
267  build_opts.add_option("-DN=" + support::cpp11::to_string(gemm_info.n));
268  build_opts.add_option("-DK=" + support::cpp11::to_string(gemm_info.k));
269  build_opts.add_option("-DM0=" + support::cpp11::to_string(lhs_info.m0));
270  build_opts.add_option("-DN0=" + support::cpp11::to_string(rhs_info.n0));
271  build_opts.add_option("-DK0=" + support::cpp11::to_string(rhs_info.k0));
272  build_opts.add_option("-DH0=" + support::cpp11::to_string(rhs_info.h0));
273  build_opts.add_option_if(gemm_info.activation_info.enabled(), "-DACTIVATION_TYPE=" + lower_string(string_from_activation_func(gemm_info.activation_info.activation())));
274  build_opts.add_option_if(gemm_info.activation_info.enabled(), "-DA_VAL=" + float_to_string_with_full_precision(gemm_info.activation_info.a()));
275  build_opts.add_option_if(gemm_info.activation_info.enabled(), "-DB_VAL=" + float_to_string_with_full_precision(gemm_info.activation_info.b()));
276 
277  std::string kernel_name("gemm_mm_reshaped_only_rhs_");
278  kernel_name += rhs_info.transpose ? "t" : "nt";
279 
280  // Create kernel
281  _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
282 
283  // Set config_id for enabling LWS tuning
284  _config_id = kernel_name;
285  _config_id += "_";
286  _config_id += (_add_bias ? "add_bias_" : "");
287  _config_id += (_broadcast_bias ? "broadcast_bias_" : "");
288  _config_id += (_reinterpret_input_as_3d ? "3di_" : "");
289  _config_id += (_reinterpret_output_as_3d ? "3do_" : "");
290  _config_id += (gemm_info.activation_info.enabled() ? "fused_activation_" : "");
291  _config_id += lower_string(string_from_data_type(input0->info()->data_type()));
292  _config_id += "_";
293  _config_id += support::cpp11::to_string(output->info()->dimension(1));
294  _config_id += "_";
295  _config_id += support::cpp11::to_string(output->info()->dimension(0));
296  _config_id += "_";
297  _config_id += support::cpp11::to_string(gemm_info.k);
298  _config_id += "_";
299  _config_id += support::cpp11::to_string(output->info()->dimension(2));
300  _config_id += "_";
301  _config_id += support::cpp11::to_string(lhs_info.m0);
302  _config_id += "_";
303  _config_id += support::cpp11::to_string(rhs_info.n0);
304  _config_id += "_";
305  _config_id += support::cpp11::to_string(rhs_info.k0);
306  _config_id += "_";
307  _config_id += support::cpp11::to_string(rhs_info.h0);
308  _config_id += "_";
309  _config_id += support::cpp11::to_string(rhs_info.interleave);
310 }
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
std::pair< Status, Window > validate_and_configure_window(ITensorInfo *input, ITensorInfo *weights, ITensorInfo *biases, ITensorInfo *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier, const Size2D &dilation)
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:268
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:170
static CLKernelLibrary & get()
Access the KernelLibrary singleton.
#define ARM_COMPUTE_ERROR_THROW_ON(status)
Definition: Error.h:327
std::string lower_string(const std::string &val)
Lower a given string.
Definition: Utils.cpp:327
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:1066
std::string get_cl_type_from_data_type(const DataType &dt)
Translates a tensor data type to the appropriate OpenCL type.
Definition: CLHelpers.cpp:35
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(), arm_compute::support::cpp11::to_string(), and arm_compute::validate_and_configure_window().

◆ 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 331 of file CLGEMMMatrixMultiplyReshapedOnlyRHSKernel.cpp.

332 {
335 
336  if(_input1->info()->num_dimensions() < 3)
337  {
338  // The stride_z for matrix B must be zero if we do not slice
339  ARM_COMPUTE_ERROR_ON(_input1->info()->strides_in_bytes()[3] != 0);
340  }
341 
343  Window slice_matrix_b = slice;
344 
345  slice_matrix_b.set(Window::DimX, Window::Dimension(0, 1, 1));
346  slice_matrix_b.set(Window::DimY, Window::Dimension(0, 1, 1));
347 
348  if(_reinterpret_input_as_3d)
349  {
350  // Pass bottom paddings to the kernel if the input has to be reinterpreted as 3D tensor
351  unsigned int idx0;
352  if(_add_bias)
353  {
354  idx0 = 4 * num_arguments_per_2D_tensor() + 4;
355  }
356  else
357  {
358  idx0 = 3 * num_arguments_per_2D_tensor() + 3;
359  }
360  const unsigned int total_cross_plane_pad = _input0->info()->padding().top + _input0->info()->padding().bottom;
361  _kernel.setArg<cl_uint>(idx0, static_cast<unsigned int>(total_cross_plane_pad));
362  }
363 
364  if(_reinterpret_output_as_3d)
365  {
366  // Pass bottom paddings to the kernel if the output has to be reinterpreted as 3D tensor
367  unsigned int idx0;
368  if(_add_bias)
369  {
370  idx0 = 4 * num_arguments_per_2D_tensor() + 4 + (_reinterpret_input_as_3d ? 1 : 0);
371  }
372  else
373  {
374  idx0 = 3 * num_arguments_per_2D_tensor() + 3 + (_reinterpret_input_as_3d ? 1 : 0);
375  }
376  const unsigned int total_cross_plane_pad = _output->info()->padding().top + _output->info()->padding().bottom;
377  _kernel.setArg<cl_uint>(idx0, static_cast<unsigned int>(total_cross_plane_pad));
378  }
379 
380  do
381  {
382  Window slice_b = slice;
383  // Don't slice matrix B along the z dimension if matrix B has just 2 dimensions and matrix A more than 2
384  // This scenario can happen when the matrix multiplication is used to perform a convolution operation
385  if(!_slide_matrix_b)
386  {
387  slice_b = slice_matrix_b;
388  }
389 
390  unsigned int idx = 0;
391  add_2D_tensor_argument(idx, _input0, slice);
392  add_2D_tensor_argument(idx, _input1, slice_b);
393  add_2D_tensor_argument_if((_add_bias), idx, _input2, slice);
394  add_2D_tensor_argument(idx, _output, slice);
395  _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_input0->info()->strides_in_bytes()[2]));
396  _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_input1->info()->strides_in_bytes()[2]));
397  if(_add_bias)
398  {
399  _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_input2->info()->strides_in_bytes()[2]));
400  }
401  _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_output->info()->strides_in_bytes()[2]));
402  enqueue(queue, *this, slice, lws_hint(), _use_dummy_work_items);
403  }
405 }
unsigned int top
top of the border
Definition: Types.h:339
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:337
unsigned int bottom
bottom of the border
Definition: Types.h:341
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:319
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:275
#define ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(f, s)
Definition: Validate.h:205
#define ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(k)
Definition: Validate.h:940
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: 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 312 of file CLGEMMMatrixMultiplyReshapedOnlyRHSKernel.cpp.

315 {
316  ElementsProcessed num_elements_processed{};
317  ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input0, input1, input2, output, alpha, beta, lhs_info, rhs_info, gemm_info));
319  input1->clone().get(),
320  input2 != nullptr ? input2->clone().get() : nullptr,
321  output->clone().get(),
322  lhs_info,
323  rhs_info,
324  gemm_info,
325  num_elements_processed)
326  .first);
327 
328  return Status{};
329 }
std::pair< Status, Window > validate_and_configure_window(ITensorInfo *input, ITensorInfo *weights, ITensorInfo *biases, ITensorInfo *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier, const Size2D &dilation)
#define ARM_COMPUTE_RETURN_ON_ERROR(status)
Checks if a status contains an error and returns it.
Definition: Error.h:193

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


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