Compute Library
 19.11
CLGEMMMatrixMultiplyReshapedKernel Class Reference

OpenCL kernel to multiply matrices when both the input matrices LHS (input0) and RHS (input1) have been reshaped. More...

#include <CLGEMMMatrixMultiplyReshapedKernel.h>

Collaboration diagram for CLGEMMMatrixMultiplyReshapedKernel:
[legend]

Public Member Functions

 CLGEMMMatrixMultiplyReshapedKernel ()
 Default Constructor. More...
 
 CLGEMMMatrixMultiplyReshapedKernel (const CLGEMMMatrixMultiplyReshapedKernel &)=delete
 Prevent instances of this class from being copied (As this class contains pointers) More...
 
CLGEMMMatrixMultiplyReshapedKerneloperator= (const CLGEMMMatrixMultiplyReshapedKernel &)=delete
 Prevent instances of this class from being copied (As this class contains pointers) More...
 
 CLGEMMMatrixMultiplyReshapedKernel (CLGEMMMatrixMultiplyReshapedKernel &&)=default
 Allow instances of this class to be moved. More...
 
CLGEMMMatrixMultiplyReshapedKerneloperator= (CLGEMMMatrixMultiplyReshapedKernel &&)=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 CLGEMMMatrixMultiplyReshapedKernel. 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 both the input matrices LHS (input0) and RHS (input1) have been reshaped.

Note
The input matrices input0 and input1 must be reshaped through CLGEMMReshapeLHSMatrixKernel and CLGEMMReshapeRHSMatrixKernel

Definition at line 39 of file CLGEMMMatrixMultiplyReshapedKernel.h.

Constructor & Destructor Documentation

◆ CLGEMMMatrixMultiplyReshapedKernel() [1/3]

Default Constructor.

Definition at line 209 of file CLGEMMMatrixMultiplyReshapedKernel.cpp.

210  : _input0(nullptr), _input1(nullptr), _input2(nullptr), _output(nullptr), _slide_matrix_b(true), _reinterpret_output_as_3d(false), _k(1), _use_dummy_work_items(false), _add_bias(false),
211  _broadcast_bias(false)
212 {
213 }

◆ CLGEMMMatrixMultiplyReshapedKernel() [2/3]

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

◆ CLGEMMMatrixMultiplyReshapedKernel() [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.

Note
The F16 computation also supports mixed precision through the gemm_info.fp_mixed_precision flag. Mixed precision combines different floating precisions during the computation, in particular, F32 for the accumulations and F16 for the multiplications. i.e. float c = (half)a * (half)b
Parameters
[in]input0Input tensor containing the LHS reshaped 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 for reshaping the input0 tensor. Only the following values are supported: lhs_info.m0: 2,3,4,5,6,7,8 lhs_info.k0: 2,3,4,8,16 lhs_info.transpose: false
[in]rhs_infoRHS matrix information used for reshaping the input1 tensor. Only the following values are supported: rhs_info.n0: 2,3,4,8,16 rhs_info.k0: 2,3,4,8,16 rhs_info.transpose: true
[in]gemm_infoGEMM information used to retrieve the original dimensions of the input matrices
Note
lhs_info.k0 must be equal to rhs_info.k0

Definition at line 215 of file CLGEMMMatrixMultiplyReshapedKernel.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_output_as_3d = gemm_info.depth_output_gemm3d != 0;
228  _k = gemm_info.k;
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  // Check if we need to slide the matrix B
234  const unsigned int num_dimensions_input0 = _input0->info()->num_dimensions();
235  _slide_matrix_b = (_input1->info()->num_dimensions() >= num_dimensions_input0);
236 
237  ElementsProcessed num_elements_processed{};
238 
239  // Configure kernel window
240  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);
241  ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
242  ICLKernel::configure_internal(win_config.second);
243 
244  const bool enable_mixed_precision = gemm_info.fp_mixed_precision;
245  const DataType data_type = input0->info()->data_type();
246 
247  // Create build options
248  CLBuildOptions build_opts;
250  build_opts.add_option_if(_input2 != nullptr, "-DBETA=" + float_to_string_with_full_precision(beta));
251  build_opts.add_option_if(helpers::float_ops::is_one(beta), "-DUNIT_BETA");
252  build_opts.add_option_if(_reinterpret_output_as_3d, "-DREINTERPRET_OUTPUT_AS_3D");
253  build_opts.add_option_if(_reinterpret_output_as_3d, "-DHEIGHT_GEMM3D=" + support::cpp11::to_string(output->info()->dimension(1)));
254  build_opts.add_option_if(_reinterpret_output_as_3d, "-DDEPTH_GEMM3D=" + support::cpp11::to_string(output->info()->dimension(2)));
255  build_opts.add_option_if(gemm_info.broadcast_bias, "-DBROADCAST_BIAS");
256  build_opts.add_option_if(!_slide_matrix_b, "-DMATRIX_B_DEPTH=" + support::cpp11::to_string(input1->info()->dimension(2)));
257  build_opts.add_option_if(lhs_info.interleave, "-DLHS_INTERLEAVE");
258  build_opts.add_option_if(rhs_info.interleave, "-DRHS_INTERLEAVE");
259  build_opts.add_option_if(lhs_info.transpose, "-DLHS_TRANSPOSE");
260  build_opts.add_option_if(_use_dummy_work_items, "-DDUMMY_WORK_ITEMS");
261  build_opts.add_option_if(gemm_info.activation_info.enabled(), "-DACTIVATION_TYPE=" + lower_string(string_from_activation_func(gemm_info.activation_info.activation())));
262  build_opts.add_option_if(gemm_info.activation_info.enabled(), "-DA_VAL=" + float_to_string_with_full_precision(gemm_info.activation_info.a()));
263  build_opts.add_option_if(gemm_info.activation_info.enabled(), "-DB_VAL=" + float_to_string_with_full_precision(gemm_info.activation_info.b()));
264  build_opts.add_option_if(enable_mixed_precision, "-DMIXED_PRECISION");
265  build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(data_type));
266  build_opts.add_option("-DDATA_TYPE_ACCUMULATOR=" + (enable_mixed_precision ? get_cl_type_from_data_type(DataType::F32) : get_cl_type_from_data_type(data_type)));
267  build_opts.add_option("-DM=" + support::cpp11::to_string(gemm_info.m));
268  build_opts.add_option("-DN=" + support::cpp11::to_string(gemm_info.n));
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(lhs_info.k0));
272  build_opts.add_option("-DV0=" + support::cpp11::to_string(lhs_info.v0));
273  build_opts.add_option("-DH0=" + support::cpp11::to_string(rhs_info.h0));
274 
275  std::string kernel_name("gemm_mm_reshaped_");
276  kernel_name += lhs_info.transpose ? "lhs_t_" : "lhs_nt_";
277  kernel_name += rhs_info.transpose ? "rhs_t" : "rhs_nt";
278 
279  // Create kernel
280  _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
281 
282  // Set config_id for enabling LWS tuning
283  _config_id = kernel_name;
284  _config_id += "_";
285  _config_id += (_add_bias ? "add_bias_" : "");
286  _config_id += (_broadcast_bias ? "broadcast_bias_" : "");
287  _config_id += (_reinterpret_output_as_3d ? "3do_" : "");
288  _config_id += (gemm_info.activation_info.enabled() ? "fused_activation_" : "");
289  _config_id += lower_string(string_from_data_type(input0->info()->data_type()));
290  _config_id += "_";
291  _config_id += (enable_mixed_precision ? "mixed_precision_" : "");
292  _config_id += support::cpp11::to_string(output->info()->dimension(1));
293  _config_id += "_";
294  _config_id += support::cpp11::to_string(output->info()->dimension(0));
295  _config_id += "_";
296  _config_id += support::cpp11::to_string(gemm_info.k);
297  _config_id += "_";
298  _config_id += support::cpp11::to_string(output->info()->dimension(2));
299  _config_id += "_";
300  _config_id += support::cpp11::to_string(lhs_info.m0);
301  _config_id += "_";
302  _config_id += support::cpp11::to_string(rhs_info.n0);
303  _config_id += "_";
304  _config_id += support::cpp11::to_string(lhs_info.k0);
305  _config_id += "_";
306  _config_id += support::cpp11::to_string(lhs_info.v0);
307  _config_id += "_";
308  _config_id += support::cpp11::to_string(rhs_info.h0);
309  _config_id += "_";
310  _config_id += support::cpp11::to_string(lhs_info.interleave);
311  _config_id += "_";
312  _config_id += support::cpp11::to_string(rhs_info.interleave);
313 }
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 broadcast_bias
Flag used to broadcase the bias addition.
virtual size_t dimension(size_t index) const =0
Return the size of the requested dimension.
const StringSet & options() const
Gets the current options list set.
unsigned int v0
Number of vertical blocks of size (m0xk0) stored on the same output row.
Definition: Types.h:1894
unsigned int depth_output_gemm3d
Depth of the output tensor in case is reinterpreted as 3D.
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.
virtual DataType data_type() const =0
Data type used for each element of the tensor.
1 channel, 1 F32 per channel
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
bool interleave
True if the v0 (m0xk0) blocks have to be interleaved in the output row.
Definition: Types.h:1896
void add_option(std::string option)
Adds option to the existing build option list.
bool transpose
True if the (m0xk0) block has to be transposed before been stored.
Definition: Types.h:1895
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.
void add_option_if(bool cond, std::string option)
Adds option if a given condition is true;.
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
unsigned int k
Number of LHS columns or RHS rows.
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
unsigned int k0
Number of partial accumulations performed by the matrix multiplication.
Definition: Types.h:1893
unsigned int m0
Number of rows processed by the matrix multiplication.
Definition: Types.h:1892
DataType
Available data types.
Definition: Types.h:74

References arm_compute::test::validation::alpha, ARM_COMPUTE_ERROR_ON_NULLPTR, ARM_COMPUTE_ERROR_THROW_ON, ITensor::info(), and arm_compute::helpers::float_ops::is_zero().

◆ 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 334 of file CLGEMMMatrixMultiplyReshapedKernel.cpp.

335 {
338 
339  if(_input1->info()->num_dimensions() < 3)
340  {
341  // The stride_z for matrix B must be zero if we do not slice
342  ARM_COMPUTE_ERROR_ON(_input1->info()->strides_in_bytes()[3] != 0);
343  }
344 
346  Window slice_matrix_b = slice;
347 
348  slice_matrix_b.set(Window::DimX, Window::Dimension(0, 1, 1));
349  slice_matrix_b.set(Window::DimY, Window::Dimension(0, 1, 1));
350 
351  if(_reinterpret_output_as_3d)
352  {
353  // Pass bottom paddings to the kernel if the output has to be reinterpreted as 3D tensor
354  unsigned int idx0;
355  if(_add_bias)
356  {
357  idx0 = 4 * num_arguments_per_2D_tensor() + 5;
358  }
359  else
360  {
361  idx0 = 3 * num_arguments_per_2D_tensor() + 4;
362  }
363  const unsigned int total_cross_plane_pad = _output->info()->padding().top + _output->info()->padding().bottom;
364  _kernel.setArg<cl_uint>(idx0, static_cast<unsigned int>(total_cross_plane_pad));
365  }
366 
367  do
368  {
369  Window slice_b = slice;
370  // Don't slice matrix B along the z dimension if matrix B has just 2 dimensions and matrix A more than 2
371  // This scenario can happen when the matrix multiplication is used to perform a convolution operation
372  if(!_slide_matrix_b)
373  {
374  slice_b = slice_matrix_b;
375  }
376 
377  unsigned int idx = 0;
378  add_2D_tensor_argument(idx, _input0, slice);
379  add_2D_tensor_argument(idx, _input1, slice_b);
380  add_2D_tensor_argument_if((_add_bias), idx, _input2, slice);
381  add_2D_tensor_argument(idx, _output, slice);
382  _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_k));
383  _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_input0->info()->strides_in_bytes()[2]));
384  _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_input1->info()->strides_in_bytes()[2]));
385  if(_add_bias)
386  {
387  _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_input2->info()->strides_in_bytes()[2]));
388  }
389  _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_output->info()->strides_in_bytes()[2]));
390  enqueue(queue, *this, slice, lws_hint(), _use_dummy_work_items);
391  }
393 }
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
Describe one of the image's dimensions with a start, end and step.
Definition: Window.h:75
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.
void set(size_t dimension, const Dimension &dim)
Set the values of a given dimension.
Definition: Window.inl:49
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
Describe a multidimensional execution window.
Definition: Window.h:39
#define ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(k)
Definition: Validate.h:941
SimpleTensor< T > slice(const SimpleTensor< T > &src, Coordinates starts, Coordinates ends)

References ARM_COMPUTE_ERROR_ON, ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW, ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL, Window::DimX, Window::DimY, Window::first_slice_window_3D(), ITensor::info(), ICLKernel::num_arguments_per_2D_tensor(), ITensorInfo::num_dimensions(), Window::set(), arm_compute::test::validation::reference::slice(), ITensorInfo::strides_in_bytes(), 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 CLGEMMMatrixMultiplyReshapedKernel.

Parameters
[in]input0Input tensor containing the LHS reshaped 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 info containing the bias matrix. Data type supported: same as input0.
[in]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 for reshaping the input0 tensor. Only the following values are supported: lhs_info.m0: 2,3,4,5,6,7,8 lhs_info.k0: 2,3,4,8,16 lhs_info.transpose: false
[in]rhs_infoRHS matrix information used for reshaping the input1 tensor. Only the following values are supported: rhs_info.n0: 2,3,4,8,16 rhs_info.k0: 2,3,4,8,16 rhs_info.transpose: true
[in]gemm_infoGEMM information used to retrieve the original dimensions of the input matrices
Note
lhs_info.k0 must be equal to rhs_info.k0
Returns
a status

Definition at line 315 of file CLGEMMMatrixMultiplyReshapedKernel.cpp.

318 {
319  ElementsProcessed num_elements_processed{};
320  ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input0, input1, input2, output, alpha, beta, lhs_info, rhs_info, gemm_info));
321  ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input0->clone().get(),
322  input1->clone().get(),
323  input2 != nullptr ? input2->clone().get() : nullptr,
324  output->clone().get(),
325  lhs_info,
326  rhs_info,
327  gemm_info,
328  num_elements_processed)
329  .first);
330 
331  return Status{};
332 }
#define ARM_COMPUTE_RETURN_ON_ERROR(status)
Checks if a status contains an error and returns it.
Definition: Error.h:204
Status class.
Definition: Error.h:52
virtual std::unique_ptr< T > clone() const =0
Provide a clone of the current object of class T.

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: