Compute Library
 22.05
ClIm2ColKernel Class Reference

Interface for the im2col reshape kernel. More...

#include <ClIm2ColKernel.h>

Collaboration diagram for ClIm2ColKernel:
[legend]

Public Member Functions

 ClIm2ColKernel ()
 Default constructor. More...
 
 ARM_COMPUTE_DISALLOW_COPY_ALLOW_MOVE (ClIm2ColKernel)
 
void configure (const ClCompileContext &compile_context, ITensorInfo *src, ITensorInfo *dst, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, const Size2D &dilation=Size2D(1U, 1U), unsigned int num_groups=1)
 Set the input and output of the kernel. More...
 
void run_op (ITensorPack &tensors, const Window &window, cl::CommandQueue &queue) override
 Enqueue the OpenCL kernel to process the given window on the passed OpenCL command queue. More...
 
- Public Member Functions inherited from ICLKernel
 ICLKernel ()
 Constructor. More...
 
cl::Kernel & kernel ()
 Returns a reference to the OpenCL kernel of this object. More...
 
CLKernelType type () const
 Returns the CL kernel type. More...
 
template<typename T >
void add_1D_array_argument (unsigned int &idx, const ICLArray< T > *array, const Strides &strides, unsigned int num_dimensions, const Window &window)
 Add the passed 1D array's parameters to the object's kernel's arguments starting from the index idx. More...
 
void add_1D_tensor_argument (unsigned int &idx, const ICLTensor *tensor, const Window &window)
 Add the passed 1D tensor's parameters to the object's kernel's arguments starting from the index idx. More...
 
void add_1D_tensor_argument_if (bool cond, unsigned int &idx, const ICLTensor *tensor, const Window &window)
 Add the passed 1D tensor's parameters to the object's kernel's arguments starting from the index idx if the condition is true. More...
 
void add_2D_tensor_argument (unsigned int &idx, const ICLTensor *tensor, const Window &window)
 Add the passed 2D tensor's parameters to the object's kernel's arguments starting from the index idx. More...
 
void add_2D_tensor_argument_if (bool cond, unsigned int &idx, const ICLTensor *tensor, const Window &window)
 Add the passed 2D tensor's parameters to the object's kernel's arguments starting from the index idx if the condition is true. More...
 
void add_3D_tensor_argument (unsigned int &idx, const ICLTensor *tensor, const Window &window)
 Add the passed 3D tensor's parameters to the object's kernel's arguments starting from the index idx. More...
 
void add_4D_tensor_argument (unsigned int &idx, const ICLTensor *tensor, const Window &window)
 Add the passed 4D tensor's parameters to the object's kernel's arguments starting from the index idx. More...
 
void add_5D_tensor_argument (unsigned int &idx, const ICLTensor *tensor, const Window &window)
 Add the passed 5D tensor's parameters to the object's kernel's arguments starting from the index idx. More...
 
void add_3d_tensor_nhw_argument (unsigned int &idx, const ICLTensor *tensor)
 Add the passed NHW 3D tensor's parameters to the object's kernel's arguments by passing strides, dimensions and the offset to the first valid element in bytes. More...
 
void add_4d_tensor_nhwc_argument (unsigned int &idx, const ICLTensor *tensor)
 Add the passed NHWC 4D tensor's parameters to the object's kernel's arguments by passing strides, dimensions and the offset to the first valid element in bytes. More...
 
virtual void run (const Window &window, cl::CommandQueue &queue)
 Enqueue the OpenCL kernel to process the given window on the passed OpenCL command queue. More...
 
virtual void run_composite_op (ITensorPack &tensors, const Window &window, cl::CommandQueue &queue, const experimental::dynamic_fusion::ClExecutionDescriptor &exec_desc)
 The execution is carried out through run_op method. But the run_op method needs to be extended to include ClExecutionDescriptor as now LWS GWS tuning will be separated from the IKernel. More...
 
template<typename T >
void add_argument (unsigned int &idx, T value)
 Add the passed parameters to the object's kernel's arguments starting from the index idx. More...
 
void set_lws_hint (const cl::NDRange &lws_hint)
 Set the Local-Workgroup-Size hint. More...
 
cl::NDRange lws_hint () const
 Return the Local-Workgroup-Size hint. More...
 
void set_wbsm_hint (const cl_int &wbsm_hint)
 Set the workgroup batch size modifier hint. More...
 
cl_int wbsm_hint () const
 Return the workgroup batch size modifier hint. More...
 
const std::string & config_id () const
 Get the configuration ID. More...
 
void set_target (GPUTarget target)
 Set the targeted GPU architecture. More...
 
void set_target (cl::Device &device)
 Set the targeted GPU architecture according to the CL device. More...
 
GPUTarget get_target () const
 Get the targeted GPU architecture. More...
 
size_t get_max_workgroup_size ()
 Get the maximum workgroup size for the device the CLKernelLibrary uses. More...
 
template<unsigned int dimension_size>
void add_tensor_argument (unsigned &idx, const ICLTensor *tensor, const Window &window)
 
template<typename T , unsigned int dimension_size>
void add_array_argument (unsigned &idx, const ICLArray< T > *array, const Strides &strides, unsigned int num_dimensions, const Window &window)
 Add the passed array's parameters to the object's kernel's arguments starting from the index idx. More...
 
- Public Member Functions inherited from IKernel
 IKernel ()
 Constructor. More...
 
virtual ~IKernel ()=default
 Destructor. More...
 
virtual bool is_parallelisable () const
 Indicates whether or not the kernel is parallelisable. More...
 
virtual BorderSize border_size () const
 The size of the border for that kernel. More...
 
const Windowwindow () const
 The maximum window the kernel can be executed on. More...
 
bool is_window_configured () const
 Function to check if the embedded window of this kernel has been configured. More...
 

Static Public Member Functions

static Status validate (const ITensorInfo *input, const ITensorInfo *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, const Size2D &dilation=Size2D(1U, 1U), unsigned int num_groups=1)
 Static function to check if given info will lead to a valid configuration. More...
 
- Static Public Member Functions inherited from ICLKernel
static constexpr unsigned int num_arguments_per_3d_tensor_nhw ()
 Returns the number of arguments enqueued per NHW 3D Tensor object. More...
 
static constexpr unsigned int num_arguments_per_4d_tensor_nhwc ()
 Returns the number of arguments enqueued per NHWC 4D Tensor object. More...
 
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...
 

Data Fields

DataLayout _data_layout
 
std::pair< unsigned int, unsigned int > _convolved_dims
 
unsigned int _num_elems_processed_per_iteration
 
Size2D _kernel_dims
 
PadStrideInfo _conv_info
 
unsigned int _num_groups
 

Detailed Description

Interface for the im2col reshape kernel.

Rearranges image blocks into columns. It is used to strip out each convolution block to a single column. It is used to transform a convolution to a plain matrix multiplication.

For example taking into account the image below and assuming 3x3 image blocks with stride of 1 we have:

\[ \left( \begin{array}{cccc} a00 & a01 & a02 & a03 \\ a10 & a11 & a12 & a13 \\ a20 & a21 & a22 & a23 \\ a30 & a31 & a32 & a33 \\ \end{array} \right) = \left( \begin{array}{ccccccccc} a00 & a01 & a02 & a10 & a11 & a12 & a20 & a21 & a22 \\ a01 & a02 & a03 & a11 & a12 & a13 & a21 & a22 & a23 \\ a10 & a11 & a12 & a20 & a21 & a22 & a30 & a31 & a32 \\ a11 & a12 & a13 & a21 & a22 & a23 & a31 & a32 & a33 \\ \end{array} \right) \]

Definition at line 61 of file ClIm2ColKernel.h.

Constructor & Destructor Documentation

◆ ClIm2ColKernel()

Member Function Documentation

◆ ARM_COMPUTE_DISALLOW_COPY_ALLOW_MOVE()

ARM_COMPUTE_DISALLOW_COPY_ALLOW_MOVE ( ClIm2ColKernel  )

◆ configure()

void configure ( const ClCompileContext compile_context,
ITensorInfo src,
ITensorInfo dst,
const Size2D kernel_dims,
const PadStrideInfo conv_info,
bool  has_bias,
const Size2D dilation = Size2D(1U, 1U),
unsigned int  num_groups = 1 
)

Set the input and output of the kernel.

Parameters
[in]compile_contextThe compile context to be used.
[in]srcThe input tensor info to convert. 3 lower dimensions represent a single input [width, height, IFM], while every optional dimension from 4 and above represent a batch of inputs. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32
[out]dstThe output tensor info. First 2 lower dimensions represent a transform of each 3D input, while every dimension above represents a batch. Data types supported: Same as input
[in]kernel_dimsThe kernel dimensions (width and height).
[in]conv_infoContains padding and stride information described in PadStrideInfo.
[in]has_biasIn case biases are provided expands the matrix with 1.
[in]dilation(Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
[in]num_groups(Optional) Number of groups when performing a grouped convolution. num_groups != 1 is only supported for NCHW data layout

Definition at line 304 of file ClIm2ColKernel.cpp.

References ClIm2ColKernel::_conv_info, ClIm2ColKernel::_convolved_dims, ClIm2ColKernel::_data_layout, ClIm2ColKernel::_kernel_dims, ClIm2ColKernel::_num_elems_processed_per_iteration, ClIm2ColKernel::_num_groups, ARM_COMPUTE_ERROR_ON, ARM_COMPUTE_ERROR_ON_NULLPTR, ARM_COMPUTE_ERROR_THROW_ON, arm_compute::test::validation::conv_info, arm_compute::create_kernel(), ITensorInfo::data_layout(), ITensorInfo::data_type(), ITensorInfo::dimension(), arm_compute::get_data_layout_dimension_index(), arm_compute::get_padding_info(), arm_compute::has_padding_changed(), Size2D::height, arm_compute::HEIGHT, input_height, input_width, arm_compute::lower_string(), arm_compute::NHWC, arm_compute::test::validation::num_groups, arm_compute::scaled_dimensions(), arm_compute::test::validation::src, arm_compute::string_from_data_layout(), arm_compute::string_from_data_type(), arm_compute::support::cpp11::to_string(), arm_compute::cpu::kernels::validate_and_configure_window(), arm_compute::cpu::kernels::validate_arguments(), Size2D::width, and arm_compute::WIDTH.

307 {
310 
311  auto padding_info = get_padding_info({ src, dst });
312  _data_layout = src->data_layout();
313 
314  const unsigned int width_idx = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::WIDTH);
315  const unsigned int height_idx = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::HEIGHT);
316  const unsigned int input_width = src->dimension(width_idx);
317  const unsigned int input_height = src->dimension(height_idx);
318 
319  // Select and configure the optimal OpenCL kernel to run.
320  // This function returns the OpenCL kernel's name, the arguments to pass at compile time, the number of elements processed per iteration
321  // and the padding requirement flag
322  Im2ColConfiguration im2col_config = configure_opencl_kernel(src, kernel_dims, conv_info, has_bias, dilation, num_groups);
323 
324  // Create kernel
325  _kernel = create_kernel(compile_context, im2col_config.kernel_name, im2col_config.build_options);
326 
327  _convolved_dims = scaled_dimensions(input_width, input_height, kernel_dims.width, kernel_dims.height, conv_info, dilation);
328  _num_elems_processed_per_iteration = im2col_config.num_elems_processed_per_iteration;
329  _kernel_dims = kernel_dims; // Only needed by the Tuner
330  _conv_info = conv_info; // Only needed by the Tuner
332 
333  // Configure kernel window
334  auto win_config = validate_and_configure_window(src, dst, kernel_dims, conv_info, has_bias, dilation, im2col_config.num_elems_processed_per_iteration,
335  im2col_config.is_padding_required_nchw, num_groups);
336  ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
337  IClKernel::configure_internal(win_config.second);
338 
339  // Set config_id for enabling LWS tuning
340  _config_id = im2col_config.kernel_name;
341  _config_id += "_";
342  _config_id += lower_string(string_from_data_type(src->data_type()));
343  _config_id += "_";
344  _config_id += support::cpp11::to_string(num_groups);
345  _config_id += "_";
346  _config_id += support::cpp11::to_string(dst->dimension(0));
347  _config_id += "_";
348  _config_id += support::cpp11::to_string(dst->dimension(1));
349  _config_id += "_";
350  _config_id += lower_string(string_from_data_layout(_data_layout));
351 
352  ARM_COMPUTE_ERROR_ON(src->data_layout() == DataLayout::NHWC && has_padding_changed(padding_info));
353 }
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 size_t input_height
Definition: impl.cpp:61
#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:351
Status validate_arguments(const ITensorInfo *src, const ITensorInfo *weights, const ITensorInfo *dst, const PadStrideInfo &conv_info)
const size_t input_width
Definition: impl.cpp:62
SimpleTensor< float > src
Definition: DFT.cpp:155
std::pair< unsigned int, unsigned int > scaled_dimensions(int width, int height, int kernel_width, int kernel_height, const PadStrideInfo &pad_stride_info, const Size2D &dilation=Size2D(1U, 1U))
Returns expected width and height of output scaled tensor depending on dimensions rounding mode...
Definition: Utils.cpp:427
cl::Kernel create_kernel(const CLCompileContext &ctx, const std::string &kernel_name, const std::set< std::string > &build_opts=std::set< std::string >())
Creates an opencl kernel using a compile context.
Definition: CLHelpers.cpp:391
const std::string & string_from_data_type(DataType dt)
Convert a data type identity into a string.
Definition: Utils.cpp:135
const unsigned int num_groups
Definition: Im2Col.cpp:153
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:601
std::pair< Status, Window > validate_and_configure_window(ITensorInfo *src, ITensorInfo *dst)
const std::string & string_from_data_layout(DataLayout dl)
Convert a data layout identity into a string.
Definition: Utils.cpp:123
size_t get_data_layout_dimension_index(const DataLayout &data_layout, const DataLayoutDimension &data_layout_dimension)
Get the index of the given dimension.
Definition: Helpers.inl:193
Num samples, height, width, channels.
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:586
#define ARM_COMPUTE_ERROR_ON_NULLPTR(...)
Definition: Validate.h:157
std::pair< unsigned int, unsigned int > _convolved_dims

◆ run_op()

void run_op ( ITensorPack tensors,
const Window window,
cl::CommandQueue &  queue 
)
overridevirtual

Enqueue the OpenCL kernel to process the given window on the passed OpenCL command queue.

Note
The queue is not flushed by this method, and therefore the kernel will not have been executed by the time this method returns.
Parameters
[in]tensorsA vector containing the tensors to operato on.
[in]windowRegion on which to execute the kernel. (Must be a valid region of the window returned by window()).
[in,out]queueCommand queue on which to enqueue the kernel.

Reimplemented from ICLKernel.

Definition at line 366 of file ClIm2ColKernel.cpp.

References ClIm2ColKernel::_convolved_dims, ClIm2ColKernel::_data_layout, ClIm2ColKernel::_num_elems_processed_per_iteration, ClIm2ColKernel::_num_groups, arm_compute::ACL_DST, arm_compute::ACL_SRC, ICLKernel::add_2D_tensor_argument(), ICLKernel::add_3D_tensor_argument(), ARM_COMPUTE_ERROR_ON, ARM_COMPUTE_ERROR_ON_MISMATCHING_WINDOWS, ARM_COMPUTE_ERROR_ON_NULLPTR, ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL, arm_compute::ceil_to_multiple(), Window::collapse_if_possible(), Window::DimX, Window::DimY, Window::DimZ, arm_compute::test::validation::dst, ITensorPack::empty(), arm_compute::enqueue(), Window::first_slice_window_2D(), Window::first_slice_window_3D(), ITensorPack::get_const_tensor(), ITensorPack::get_tensor(), ICLKernel::lws_hint(), arm_compute::NHWC, ICLKernel::num_arguments_per_2D_tensor(), ICLKernel::num_arguments_per_3D_tensor(), Window::set(), Window::set_dimension_step(), arm_compute::test::validation::reference::slice(), Window::slide_window_slice_2D(), arm_compute::test::validation::src, Window::use_tensor_dimensions(), and IKernel::window().

367 {
370  ARM_COMPUTE_ERROR_ON(tensors.empty());
371 
372  // Get initial windows
373  // Collapse in order to have (SRC_DEPTH * BATCH_SIZE) on the 3rd dimension
374  Window window_collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimZ);
375  window_collapsed.set_dimension_step(Window::DimZ, 1);
376 
377  auto src = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC));
378  auto dst = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_DST));
380 
381  Window window_output;
382  window_output.use_tensor_dimensions(dst->info()->tensor_shape());
383 
384  const Window first_slice_3d = window_collapsed.first_slice_window_3D();
385 
386  Window slice = first_slice_3d;
387  Window slice_in = first_slice_3d;
388  Window slice_out = window_output.first_slice_window_2D();
389 
391  {
392  const Window tmp_win = window.collapse_if_possible(ICLKernel::window(), 3);
393  const int num_batches = tmp_win[3].end();
394 
395  slice.set(1, Window::Dimension(0, static_cast<int>(dst->info()->tensor_shape()[1]), 1));
396  slice.set(2, Window::Dimension(0, static_cast<int>(num_batches), 1));
397  }
398  else
399  {
400  slice.set(0, Window::Dimension(0, static_cast<int>(ceil_to_multiple(_convolved_dims.first, _num_elems_processed_per_iteration)), _num_elems_processed_per_iteration));
401  slice.set(1, Window::Dimension(0, static_cast<int>(_convolved_dims.second), 1));
402  // Note: In case of NCHW the 3rd dimension is already set collapsing the input window
403  }
404 
405  // Setup input slice
406  // The dimensions of the input are increased within the OpenCL kernel
407  slice_in.set(Window::DimX, Window::Dimension(0, 0, 0));
408  slice_in.set(Window::DimY, Window::Dimension(0, 0, 0));
409  slice_in.set(Window::DimZ, Window::Dimension(0, 0, 0));
410 
411  // Setup output slice
412  // The dimensions of the output are increased within the OpenCL kernel
413  slice_out.set(Window::DimX, Window::Dimension(0, 0, 0));
414  slice_out.set(Window::DimY, Window::Dimension(0, 0, 0));
415 
417  _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(src->info()->strides_in_bytes()[3]));
418  _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(dst->info()->strides_in_bytes()[((_num_groups == 1) ? 2 : 3)]));
419  do
420  {
421  unsigned int idx = 0;
422  add_3D_tensor_argument(idx, src, slice_in);
423  if(_num_groups == 1)
424  {
425  add_2D_tensor_argument(idx, dst, slice_out);
426  }
427  else
428  {
429  add_3D_tensor_argument(idx, dst, slice_out);
430  }
431  enqueue(queue, *this, slice, lws_hint());
432  }
433  while(window_collapsed.slide_window_slice_3D(slice) && window_output.slide_window_slice_2D(slice_out) && window_collapsed.slide_window_slice_3D(slice_in));
434 }
const Window & window() const
The maximum window the kernel can be executed on.
Definition: IKernel.cpp:28
void enqueue(cl::CommandQueue &queue, ICLKernel &kernel, const Window &window, const cl::NDRange &lws_hint=CLKernelLibrary::get().default_ndrange(), bool use_dummy_work_items=false)
Add the kernel to the command queue with the given window.
Definition: ICLKernel.cpp:32
cl::NDRange lws_hint() const
Return the Local-Workgroup-Size hint.
Definition: ICLKernel.h:384
#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
void add_3D_tensor_argument(unsigned int &idx, const ICLTensor *tensor, const Window &window)
Add the passed 3D tensor&#39;s parameters to the object&#39;s kernel&#39;s arguments starting from the index idx...
Definition: ICLKernel.h:227
SimpleTensor< float > src
Definition: DFT.cpp:155
static constexpr size_t DimX
Alias for dimension 0 also known as X dimension.
Definition: Window.h:43
static constexpr unsigned int num_arguments_per_3D_tensor()
Returns the number of arguments enqueued per 3D tensor object.
Definition: ICLKernel.h:314
#define ARM_COMPUTE_ERROR_ON_MISMATCHING_WINDOWS(f, w)
Definition: Validate.h:179
Window collapse_if_possible(const Window &full_window, size_t first, size_t last, bool *has_collapsed=nullptr) const
Collapse the dimensions between first and last if possible.
Definition: Window.inl:68
auto ceil_to_multiple(S value, T divisor) -> decltype(((value+divisor - 1)/divisor) *divisor)
Computes the smallest number larger or equal to value that is a multiple of divisor.
Definition: Utils.h:71
void set(size_t dimension, const Dimension &dim)
Set the values of a given dimension.
Definition: Window.inl:49
static constexpr unsigned int num_arguments_per_2D_tensor()
Returns the number of arguments enqueued per 2D tensor object.
Definition: ICLKernel.h:306
#define ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(k)
Definition: Validate.h:915
static constexpr size_t DimY
Alias for dimension 1 also known as Y dimension.
Definition: Window.h:45
void set_dimension_step(size_t dimension, int step)
Set the step of a given dimension.
Definition: Window.inl:167
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:203
static constexpr size_t DimZ
Alias for dimension 2 also known as Z dimension.
Definition: Window.h:47
Num samples, height, width, channels.
#define ARM_COMPUTE_ERROR_ON_NULLPTR(...)
Definition: Validate.h:157
std::pair< unsigned int, unsigned int > _convolved_dims
SimpleTensor< T > slice(const SimpleTensor< T > &src, Coordinates starts, Coordinates ends)

◆ validate()

Status validate ( const ITensorInfo input,
const ITensorInfo output,
const Size2D kernel_dims,
const PadStrideInfo conv_info,
bool  has_bias,
const Size2D dilation = Size2D(1U, 1U),
unsigned int  num_groups = 1 
)
static

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

Similar to ClIm2ColKernel::configure()

Returns
a status

Definition at line 355 of file ClIm2ColKernel.cpp.

References ARM_COMPUTE_RETURN_ON_ERROR, ICloneable< T >::clone(), arm_compute::test::validation::conv_info, arm_compute::test::validation::has_bias, arm_compute::test::validation::num_groups, arm_compute::cpu::kernels::validate_and_configure_window(), and arm_compute::cpu::kernels::validate_arguments().

Referenced by ClGemmConv2d::validate().

357 {
359  Im2ColConfiguration im2col_config = configure_opencl_kernel(src, kernel_dims, conv_info, has_bias, dilation, num_groups);
360  ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(src->clone().get(), dst->clone().get(), kernel_dims, conv_info, has_bias, dilation, im2col_config.num_elems_processed_per_iteration,
361  im2col_config.is_padding_required_nchw, num_groups)
362  .first);
363  return Status{};
364 }
#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 *src, const ITensorInfo *weights, const ITensorInfo *dst, const PadStrideInfo &conv_info)
SimpleTensor< float > src
Definition: DFT.cpp:155
const unsigned int num_groups
Definition: Im2Col.cpp:153
std::pair< Status, Window > validate_and_configure_window(ITensorInfo *src, ITensorInfo *dst)

Field Documentation

◆ _conv_info

PadStrideInfo _conv_info

Definition at line 100 of file ClIm2ColKernel.h.

Referenced by ClIm2ColKernel::configure().

◆ _convolved_dims

std::pair<unsigned int, unsigned int> _convolved_dims

Definition at line 97 of file ClIm2ColKernel.h.

Referenced by ClIm2ColKernel::configure(), and ClIm2ColKernel::run_op().

◆ _data_layout

DataLayout _data_layout

Definition at line 96 of file ClIm2ColKernel.h.

Referenced by ClIm2ColKernel::configure(), and ClIm2ColKernel::run_op().

◆ _kernel_dims

Size2D _kernel_dims

Definition at line 99 of file ClIm2ColKernel.h.

Referenced by ClIm2ColKernel::configure().

◆ _num_elems_processed_per_iteration

unsigned int _num_elems_processed_per_iteration

Definition at line 98 of file ClIm2ColKernel.h.

Referenced by ClIm2ColKernel::configure(), and ClIm2ColKernel::run_op().

◆ _num_groups

unsigned int _num_groups

Definition at line 101 of file ClIm2ColKernel.h.

Referenced by ClIm2ColKernel::configure(), and ClIm2ColKernel::run_op().


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