Compute Library
 21.02
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...
 
 CLIm2ColKernel (const CLIm2ColKernel &)=delete
 Prevent instances of this class from being copied (As this class contains pointers) More...
 
CLIm2ColKerneloperator= (const CLIm2ColKernel &)=delete
 Prevent instances of this class from being copied (As this class contains pointers) More...
 
 CLIm2ColKernel (CLIm2ColKernel &&)=default
 Allow instances of this class to be moved. More...
 
CLIm2ColKerneloperator= (CLIm2ColKernel &&)=default
 Allow instances of this class to be moved. More...
 
void configure (const ICLTensor *input, ICLTensor *output, 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 configure (const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, 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 (const Window &window, cl::CommandQueue &queue) override
 Enqueue the OpenCL kernel to process the given window on the passed OpenCL command queue. More...
 
- Public Member Functions inherited from ICLKernel
 ICLKernel ()
 Constructor. More...
 
cl::Kernel & kernel ()
 Returns a reference to the OpenCL kernel of this object. More...
 
template<typename T >
void add_1D_array_argument (unsigned int &idx, const ICLArray< T > *array, const Strides &strides, unsigned int num_dimensions, const Window &window)
 Add the passed 1D array's parameters to the object's kernel's arguments starting from the index idx. More...
 
void add_1D_tensor_argument (unsigned int &idx, const ICLTensor *tensor, const Window &window)
 Add the passed 1D tensor's parameters to the object's kernel's arguments starting from the index idx. More...
 
void add_1D_tensor_argument_if (bool cond, unsigned int &idx, const ICLTensor *tensor, const Window &window)
 Add the passed 1D tensor's parameters to the object's kernel's arguments starting from the index idx if the condition is true. More...
 
void add_2D_tensor_argument (unsigned int &idx, const ICLTensor *tensor, const Window &window)
 Add the passed 2D tensor's parameters to the object's kernel's arguments starting from the index idx. More...
 
void add_2D_tensor_argument_if (bool cond, unsigned int &idx, const ICLTensor *tensor, const Window &window)
 Add the passed 2D tensor's parameters to the object's kernel's arguments starting from the index idx if the condition is true. More...
 
void add_3D_tensor_argument (unsigned int &idx, const ICLTensor *tensor, const Window &window)
 Add the passed 3D tensor's parameters to the object's kernel's arguments starting from the index idx. More...
 
void add_4D_tensor_argument (unsigned int &idx, const ICLTensor *tensor, const Window &window)
 Add the passed 4D tensor's parameters to the object's kernel's arguments starting from the index idx. More...
 
virtual void run_op (ITensorPack &tensors, const Window &window, cl::CommandQueue &queue)
 Enqueue the OpenCL kernel to process the given window on the passed OpenCL command queue. More...
 
template<typename T >
void add_argument (unsigned int &idx, T value)
 Add the passed parameters to the object's kernel's arguments starting from the index idx. More...
 
void set_lws_hint (const cl::NDRange &lws_hint)
 Set the Local-Workgroup-Size hint. More...
 
cl::NDRange lws_hint () const
 Return the Local-Workgroup-Size hint. More...
 
void set_wbsm_hint (const cl_int &wbsm_hint)
 Set the workgroup batch size modifier hint. More...
 
cl_int wbsm_hint () const
 Return the workgroup batch size modifier hint. More...
 
const std::string & config_id () const
 Get the configuration ID. More...
 
void set_target (GPUTarget target)
 Set the targeted GPU architecture. More...
 
void set_target (cl::Device &device)
 Set the targeted GPU architecture according to the CL device. More...
 
GPUTarget get_target () const
 Get the targeted GPU architecture. More...
 
size_t get_max_workgroup_size ()
 Get the maximum workgroup size for the device the CLKernelLibrary uses. More...
 
template<unsigned int dimension_size>
void add_tensor_argument (unsigned &idx, const ICLTensor *tensor, const Window &window)
 
template<typename T , unsigned int dimension_size>
void add_array_argument (unsigned &idx, const ICLArray< T > *array, const Strides &strides, unsigned int num_dimensions, const Window &window)
 Add the passed array's parameters to the object's kernel's arguments starting from the index idx. More...
 
- Public Member Functions inherited from IKernel
 IKernel ()
 Constructor. More...
 
virtual ~IKernel ()=default
 Destructor. More...
 
virtual bool is_parallelisable () const
 Indicates whether or not the kernel is parallelisable. More...
 
virtual BorderSize border_size () const
 The size of the border for that kernel. More...
 
const Windowwindow () const
 The maximum window the kernel can be executed on. More...
 

Static Public Member Functions

static Status validate (const ITensorInfo *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 of CLIm2ColKernel. 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...
 

Data Fields

const ICLTensor_input
 
ICLTensor_output
 
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 56 of file CLIm2ColKernel.h.

Constructor & Destructor Documentation

◆ CLIm2ColKernel() [1/3]

Default constructor.

Definition at line 302 of file CLIm2ColKernel.cpp.

◆ CLIm2ColKernel() [2/3]

CLIm2ColKernel ( const CLIm2ColKernel )
delete

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

◆ CLIm2ColKernel() [3/3]

CLIm2ColKernel ( CLIm2ColKernel &&  )
default

Allow instances of this class to be moved.

Member Function Documentation

◆ configure() [1/2]

void configure ( const ICLTensor input,
ICLTensor output,
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]inputThe input tensor 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]outputThe output tensor. 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. This is valid only for non-quantized inputs.
[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. Number of groups other than 1 is only supported for NCHW data layout. Number of groups should be multiple to the number of channels.

Definition at line 307 of file CLIm2ColKernel.cpp.

References CLKernelLibrary::get().

309 {
310  configure(CLKernelLibrary::get().get_compile_context(), input, output, kernel_dims, conv_info, has_bias, dilation, num_groups);
311 }
void configure(const ICLTensor *input, ICLTensor *output, 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.
static CLKernelLibrary & get()
Access the KernelLibrary singleton.
const unsigned int num_groups
Definition: Im2Col.cpp:153

◆ configure() [2/2]

void configure ( const CLCompileContext compile_context,
const ICLTensor input,
ICLTensor output,
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]inputThe input tensor 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]outputThe output tensor. 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 313 of file CLIm2ColKernel.cpp.

References CLIm2ColKernel::_conv_info, CLIm2ColKernel::_convolved_dims, CLIm2ColKernel::_data_layout, CLIm2ColKernel::_input, CLIm2ColKernel::_kernel_dims, CLIm2ColKernel::_num_elems_processed_per_iteration, CLIm2ColKernel::_num_groups, CLIm2ColKernel::_output, 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::test::validation::has_bias, arm_compute::has_padding_changed(), Size2D::height, arm_compute::HEIGHT, ITensor::info(), arm_compute::test::validation::input, input_height, input_width, arm_compute::lower_string(), arm_compute::NHWC, arm_compute::test::validation::num_groups, arm_compute::scaled_dimensions(), arm_compute::string_from_data_layout(), arm_compute::string_from_data_type(), arm_compute::support::cpp11::to_string(), arm_compute::validate_arguments(), Size2D::width, and arm_compute::WIDTH.

316 {
318  ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), kernel_dims, conv_info, has_bias, dilation, num_groups));
319 
320  auto padding_info = get_padding_info({ input, output });
321  _data_layout = input->info()->data_layout();
322 
323  const unsigned int width_idx = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::WIDTH);
324  const unsigned int height_idx = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::HEIGHT);
325  const unsigned int input_width = input->info()->dimension(width_idx);
326  const unsigned int input_height = input->info()->dimension(height_idx);
327 
328  // Select and configure the optimal OpenCL kernel to run.
329  // This function returns the OpenCL kernel's name, the arguments to pass at compile time, the number of elements processed per iteration
330  // and the padding requirement flag
331  Im2ColConfiguration im2col_config = configure_opencl_kernel(input->info(), kernel_dims, conv_info, has_bias, dilation, num_groups);
332 
333  // Create kernel
334  _kernel = create_kernel(compile_context, im2col_config.kernel_name, im2col_config.build_options);
335 
336  _input = input;
337  _output = output;
338  _convolved_dims = scaled_dimensions(input_width, input_height, kernel_dims.width, kernel_dims.height, conv_info, dilation);
339  _num_elems_processed_per_iteration = im2col_config.num_elems_processed_per_iteration;
340  _kernel_dims = kernel_dims; // Only needed by the Tuner
341  _conv_info = conv_info; // Only needed by the Tuner
343 
344  // Configure kernel window
345  auto win_config = validate_and_configure_window(input->info(), output->info(), kernel_dims, conv_info, has_bias, dilation, im2col_config.num_elems_processed_per_iteration,
346  im2col_config.is_padding_required_nchw, num_groups);
347  ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
348  ICLKernel::configure_internal(win_config.second);
349 
350  // Set config_id for enabling LWS tuning
351  _config_id = im2col_config.kernel_name;
352  _config_id += "_";
353  _config_id += lower_string(string_from_data_type(input->info()->data_type()));
354  _config_id += "_";
355  _config_id += support::cpp11::to_string(num_groups);
356  _config_id += "_";
357  _config_id += support::cpp11::to_string(output->info()->dimension(0));
358  _config_id += "_";
359  _config_id += support::cpp11::to_string(output->info()->dimension(1));
360  _config_id += "_";
361  _config_id += lower_string(string_from_data_layout(_data_layout));
362 
363  ARM_COMPUTE_ERROR_ON(input->info()->data_layout() == DataLayout::NHWC && has_padding_changed(padding_info));
364 }
std::pair< unsigned int, unsigned int > _convolved_dims
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
#define ARM_COMPUTE_ERROR_THROW_ON(status)
Definition: Error.h:455
std::string lower_string(const std::string &val)
Lower a given string.
Definition: Utils.cpp:350
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:419
cl::Kernel create_kernel(const CLCompileContext &ctx, const std::string &kernel_name, const std::set< std::string > &build_opts=std::set< std::string >())
Creates an opencl kernel using a compile context.
Definition: CLHelpers.cpp:403
const std::string & string_from_data_type(DataType dt)
Convert a data type identity into a string.
Definition: Utils.cpp:135
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:528
const std::string & string_from_data_layout(DataLayout dl)
Convert a data layout identity into a string.
Definition: Utils.cpp:123
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:513
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, const GEMMLowpOutputStageInfo *output_stage)
unsigned int _num_elems_processed_per_iteration
#define ARM_COMPUTE_ERROR_ON_NULLPTR(...)
Definition: Validate.h:161
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

◆ operator=() [1/2]

CLIm2ColKernel& operator= ( const CLIm2ColKernel )
delete

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

◆ operator=() [2/2]

CLIm2ColKernel& operator= ( CLIm2ColKernel &&  )
default

Allow instances of this class to be moved.

◆ run()

void run ( const Window window,
cl::CommandQueue &  queue 
)
overridevirtual

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

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

Reimplemented from ICLKernel.

Definition at line 377 of file CLIm2ColKernel.cpp.

References CLIm2ColKernel::_convolved_dims, CLIm2ColKernel::_data_layout, CLIm2ColKernel::_input, CLIm2ColKernel::_num_elems_processed_per_iteration, CLIm2ColKernel::_num_groups, CLIm2ColKernel::_output, ICLKernel::add_2D_tensor_argument(), ICLKernel::add_3D_tensor_argument(), ARM_COMPUTE_ERROR_ON_MISMATCHING_WINDOWS, ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL, arm_compute::ceil_to_multiple(), Window::collapse_if_possible(), Window::DimX, Window::DimY, Window::DimZ, arm_compute::enqueue(), Window::first_slice_window_2D(), Window::first_slice_window_3D(), ITensor::info(), 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(), Window::slide_window_slice_3D(), ITensorInfo::strides_in_bytes(), ITensorInfo::tensor_shape(), Window::use_tensor_dimensions(), and IKernel::window().

378 {
381 
382  // Get initial windows
383  // Collapse in order to have (SRC_DEPTH * BATCH_SIZE) on the 3rd dimension
384  Window window_collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimZ);
385  window_collapsed.set_dimension_step(Window::DimZ, 1);
386 
387  Window window_output;
388  window_output.use_tensor_dimensions(_output->info()->tensor_shape());
389 
390  const Window first_slice_3d = window_collapsed.first_slice_window_3D();
391 
392  Window slice = first_slice_3d;
393  Window slice_in = first_slice_3d;
394  Window slice_out = window_output.first_slice_window_2D();
395 
397  {
398  const Window tmp_win = window.collapse_if_possible(ICLKernel::window(), 3);
399  const int num_batches = tmp_win[3].end();
400 
401  slice.set(1, Window::Dimension(0, static_cast<int>(_output->info()->tensor_shape()[1]), 1));
402  slice.set(2, Window::Dimension(0, static_cast<int>(num_batches), 1));
403  }
404  else
405  {
406  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));
407  slice.set(1, Window::Dimension(0, static_cast<int>(_convolved_dims.second), 1));
408  // Note: In case of NCHW the 3rd dimension is already set collapsing the input window
409  }
410 
411  // Setup input slice
412  // The dimensions of the input are increased within the OpenCL kernel
413  slice_in.set(Window::DimX, Window::Dimension(0, 0, 0));
414  slice_in.set(Window::DimY, Window::Dimension(0, 0, 0));
415  slice_in.set(Window::DimZ, Window::Dimension(0, 0, 0));
416 
417  // Setup output slice
418  // The dimensions of the output are increased within the OpenCL kernel
419  slice_out.set(Window::DimX, Window::Dimension(0, 0, 0));
420  slice_out.set(Window::DimY, Window::Dimension(0, 0, 0));
421 
423  _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_input->info()->strides_in_bytes()[3]));
424  _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_output->info()->strides_in_bytes()[((_num_groups == 1) ? 2 : 3)]));
425  do
426  {
427  unsigned int idx = 0;
428  add_3D_tensor_argument(idx, _input, slice_in);
429  if(_num_groups == 1)
430  {
431  add_2D_tensor_argument(idx, _output, slice_out);
432  }
433  else
434  {
435  add_3D_tensor_argument(idx, _output, slice_out);
436  }
437  enqueue(queue, *this, slice, lws_hint());
438  }
439  while(window_collapsed.slide_window_slice_3D(slice) && window_output.slide_window_slice_2D(slice_out) && window_collapsed.slide_window_slice_3D(slice_in));
440 }
const Window & window() const
The maximum window the kernel can be executed on.
Definition: IKernel.cpp:28
void enqueue(IGCKernel &kernel, const Window &window, const gles::NDRange &lws=gles::NDRange(1U, 1U, 1U))
Add the kernel to the command queue with the given window.
Definition: IGCKernel.cpp:41
std::pair< unsigned int, unsigned int > _convolved_dims
cl::NDRange lws_hint() const
Return the Local-Workgroup-Size hint.
Definition: ICLKernel.h:276
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:172
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:214
#define ARM_COMPUTE_ERROR_ON_MISMATCHING_WINDOWS(f, w)
Definition: Validate.h:183
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
virtual const TensorShape & tensor_shape() const =0
Size for each dimension of the tensor.
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
virtual ITensorInfo * info() const =0
Interface to be implemented by the child class to return the tensor&#39;s metadata.
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:206
#define ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(k)
Definition: Validate.h:941
static constexpr size_t DimY
Alias for dimension 1 also known as Y dimension.
Definition: Window.h:45
void 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:148
static constexpr size_t DimZ
Alias for dimension 2 also known as Z dimension.
Definition: Window.h:47
Num samples, height, width, channels.
unsigned int _num_elems_processed_per_iteration
virtual const Strides & strides_in_bytes() const =0
The strides in bytes for accessing each dimension of the tensor.
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 of CLIm2ColKernel.

Parameters
[in]inputThe input tensor 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
[in]outputThe output tensor. 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. This is valid only for non-quantized inputs.
[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. Number of groups other than 1 is only supported for NCHW data layout. Number of groups should be multiple to the number of channels.
Returns
a status

Definition at line 366 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, and arm_compute::validate_arguments().

Referenced by CLGEMMConvolutionLayer::validate().

368 {
370  Im2ColConfiguration im2col_config = configure_opencl_kernel(input, kernel_dims, conv_info, has_bias, dilation, num_groups);
371  ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), output->clone().get(), kernel_dims, conv_info, has_bias, dilation, im2col_config.num_elems_processed_per_iteration,
372  im2col_config.is_padding_required_nchw, num_groups)
373  .first);
374  return Status{};
375 }
#define ARM_COMPUTE_RETURN_ON_ERROR(status)
Checks if a status contains an error and returns it.
Definition: Error.h:204
const unsigned int num_groups
Definition: Im2Col.cpp:153
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, const GEMMLowpOutputStageInfo *output_stage)

Field Documentation

◆ _conv_info

PadStrideInfo _conv_info

Definition at line 132 of file CLIm2ColKernel.h.

Referenced by CLIm2ColKernel::configure().

◆ _convolved_dims

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

Definition at line 129 of file CLIm2ColKernel.h.

Referenced by CLIm2ColKernel::configure(), and CLIm2ColKernel::run().

◆ _data_layout

DataLayout _data_layout

Definition at line 128 of file CLIm2ColKernel.h.

Referenced by CLIm2ColKernel::configure(), and CLIm2ColKernel::run().

◆ _input

const ICLTensor* _input

Definition at line 126 of file CLIm2ColKernel.h.

Referenced by CLIm2ColKernel::configure(), and CLIm2ColKernel::run().

◆ _kernel_dims

Size2D _kernel_dims

Definition at line 131 of file CLIm2ColKernel.h.

Referenced by CLIm2ColKernel::configure().

◆ _num_elems_processed_per_iteration

unsigned int _num_elems_processed_per_iteration

Definition at line 130 of file CLIm2ColKernel.h.

Referenced by CLIm2ColKernel::configure(), and CLIm2ColKernel::run().

◆ _num_groups

unsigned int _num_groups

Definition at line 133 of file CLIm2ColKernel.h.

Referenced by CLIm2ColKernel::configure(), and CLIm2ColKernel::run().

◆ _output

ICLTensor* _output

Definition at line 127 of file CLIm2ColKernel.h.

Referenced by CLIm2ColKernel::configure(), and CLIm2ColKernel::run().


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