Compute Library
 21.02
NETileKernel Class Reference

Neon kernel to perform a tile operation. More...

#include <NETileKernel.h>

Collaboration diagram for NETileKernel:
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Public Member Functions

 NETileKernel ()
 Default constructor. More...
 
 NETileKernel (const NETileKernel &)=delete
 Prevent instances of this class from being copied (As this class contains pointers). More...
 
NETileKerneloperator= (const NETileKernel &)=delete
 Prevent instances of this class from being copied (As this class contains pointers). More...
 
 NETileKernel (NETileKernel &&)=default
 Allow instances of this class to be moved. More...
 
NETileKerneloperator= (NETileKernel &&)=default
 Allow instances of this class to be moved. More...
 
 ~NETileKernel ()=default
 Default destructor. More...
 
const char * name () const override
 Name of the kernel. More...
 
void configure (const ITensor *input, ITensor *output, const Multiples &multiples)
 Set the source, destination of the kernel. More...
 
void run (const Window &window, const ThreadInfo &info) override
 Execute the kernel on the passed window. More...
 
- Public Member Functions inherited from ICPPKernel
virtual ~ICPPKernel ()=default
 Default destructor. More...
 
virtual void run_nd (const Window &window, const ThreadInfo &info, const Window &thread_locator)
 legacy compatibility layer for implemantions which do not support thread_locator In these cases we simply narrow the interface down the legacy version More...
 
virtual void run_op (ITensorPack &tensors, const Window &window, const ThreadInfo &info)
 Execute the kernel on the passed window. 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 Multiples &multiples)
 Static function to check if given info will lead to a valid configuration of NETileKernel. More...
 

Detailed Description

Neon kernel to perform a tile operation.

Definition at line 34 of file NETileKernel.h.

Constructor & Destructor Documentation

◆ NETileKernel() [1/3]

Default constructor.

Definition at line 62 of file NETileKernel.cpp.

63  : _input(nullptr), _output(nullptr)
64 {
65 }

◆ NETileKernel() [2/3]

NETileKernel ( const NETileKernel )
delete

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

◆ NETileKernel() [3/3]

NETileKernel ( NETileKernel &&  )
default

Allow instances of this class to be moved.

◆ ~NETileKernel()

~NETileKernel ( )
default

Default destructor.

Member Function Documentation

◆ configure()

void configure ( const ITensor input,
ITensor output,
const Multiples multiples 
)

Set the source, destination of the kernel.

Parameters
[in]inputSource tensor. Data type supported: All.
[out]outputDestination tensor. Same as input
[in]multiplesContains the number of times the input tensor should be replicated on the given dimension.

Definition at line 67 of file NETileKernel.cpp.

References ARM_COMPUTE_ERROR_ON_NULLPTR, ARM_COMPUTE_ERROR_THROW_ON, arm_compute::auto_init_if_empty(), arm_compute::calculate_max_window(), arm_compute::misc::shape_calculator::compute_tiled_shape(), ITensorInfo::data_type(), ITensor::info(), arm_compute::test::validation::input, ITensorInfo::tensor_shape(), and arm_compute::validate_arguments().

Referenced by NETileKernel::name().

68 {
70 
71  // Auto initialize output
72  TensorShape tiled_shape = misc::shape_calculator::compute_tiled_shape(input->info()->tensor_shape(), multiples);
73  auto_init_if_empty(*output->info(), tiled_shape, 1, input->info()->data_type());
74 
75  // Validate
76  ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), multiples));
77 
78  _input = input;
79  _output = output;
80 
81  // Configure window without padding
82  Window win = calculate_max_window(*output->info());
83  INEKernel::configure(win);
84 }
Window calculate_max_window(const ValidRegion &valid_region, const Steps &steps, bool skip_border, BorderSize border_size)
#define ARM_COMPUTE_ERROR_THROW_ON(status)
Definition: Error.h:455
TensorShape compute_tiled_shape(const TensorShape &input_shape, const Multiples &multiples)
Calculate the tiled shape of a tensor.
bool auto_init_if_empty(ITensorInfo &info, const TensorShape &shape, int num_channels, DataType data_type, QuantizationInfo quantization_info=QuantizationInfo())
Auto initialize the tensor info (shape, number of channels and data type) if the current assignment i...
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, const GEMMLowpOutputStageInfo *output_stage)
#define ARM_COMPUTE_ERROR_ON_NULLPTR(...)
Definition: Validate.h:161

◆ name()

const char* name ( ) const
inlineoverridevirtual

Name of the kernel.

Returns
Kernel name

Implements ICPPKernel.

Definition at line 49 of file NETileKernel.h.

References NETileKernel::configure(), arm_compute::test::validation::info, arm_compute::test::validation::input, NETileKernel::run(), NETileKernel::validate(), and IKernel::window().

50  {
51  return "NETileKernel";
52  }

◆ operator=() [1/2]

NETileKernel& operator= ( const NETileKernel )
delete

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

◆ operator=() [2/2]

NETileKernel& operator= ( NETileKernel &&  )
default

Allow instances of this class to be moved.

◆ run()

void run ( const Window window,
const ThreadInfo info 
)
overridevirtual

Execute the kernel on the passed window.

Warning
If is_parallelisable() returns false then the passed window must be equal to window()
Note
The window has to be a region within the window returned by the window() method
The width of the window has to be a multiple of num_elems_processed_per_iteration().
Parameters
[in]windowRegion on which to execute the kernel. (Must be a region of the window returned by window())
[in]infoInfo about executing thread and CPU.

Reimplemented from ICPPKernel.

Definition at line 92 of file NETileKernel.cpp.

References ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW, ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL, ARM_COMPUTE_UNUSED, ITensorInfo::dimension(), Window::DimX, ITensorInfo::element_size(), arm_compute::execute_window_loop(), Window::first_slice_window_1D(), ITensor::info(), Iterator::ptr(), ITensor::ptr_to_element(), Window::set(), ITensorInfo::tensor_shape(), arm_compute::test::validation::w, IKernel::window(), and Window::x().

Referenced by NETileKernel::name().

93 {
97 
98  Window output_window{ window };
99  output_window.set(Window::DimX, Window::Dimension(output_window.x().start(), output_window.x().end(), _input->info()->dimension(0)));
100  Window out_slice = output_window.first_slice_window_1D();
101 
102  const auto src_shape = _input->info()->tensor_shape();
103  do
104  {
105  Iterator output_it(_output, out_slice);
106 
107  execute_window_loop(out_slice, [&](const Coordinates & id)
108  {
109  const size_t x = id.x();
110  const size_t y = id.y();
111  const size_t z = id.z();
112  const size_t w = id[3];
113  Coordinates input_coords{ x % src_shape[0], y % src_shape[1], z % src_shape[2], w % src_shape[3] };
114  memcpy(output_it.ptr(), _input->ptr_to_element(input_coords), _input->info()->dimension(0) * _input->info()->element_size());
115  },
116  output_it);
117  }
118  while(output_window.slide_window_slice_1D(out_slice));
119 }
SimpleTensor< float > w
Definition: DFT.cpp:156
const Window & window() const
The maximum window the kernel can be executed on.
Definition: IKernel.cpp:28
uint8_t * ptr_to_element(const Coordinates &id) const
Return a pointer to the element at the passed coordinates.
Definition: ITensor.h:63
virtual size_t dimension(size_t index) const =0
Return the size of the requested dimension.
static constexpr size_t DimX
Alias for dimension 0 also known as X dimension.
Definition: Window.h:43
#define ARM_COMPUTE_UNUSED(...)
To avoid unused variables warnings.
Definition: Error.h:152
virtual const TensorShape & tensor_shape() const =0
Size for each dimension of the tensor.
virtual ITensorInfo * info() const =0
Interface to be implemented by the child class to return the tensor&#39;s metadata.
virtual size_t element_size() const =0
Element size in bytes calculated as data_size() * num_channels()
void set(size_t dimension, const Dimension &dim)
Set the values of a given dimension.
Definition: Window.inl:49
#define ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(k)
Definition: Validate.h:941
ScaleKernelInfo info(interpolation_policy, default_border_mode, PixelValue(), sampling_policy, false)
void execute_window_loop(const Window &w, L &&lambda_function, Ts &&... iterators)
Iterate through the passed window, automatically adjusting the iterators and calling the lambda_funct...
Definition: Helpers.inl:77
#define ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(f, s)
Definition: Validate.h:205

◆ validate()

Status validate ( const ITensorInfo input,
const ITensorInfo output,
const Multiples multiples 
)
static

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

Parameters
[in]inputSource tensor info. Data type supported: All.
[in]outputDestination tensor info. Same as input
[in]multiplesContains the number of times the input tensor should be replicated on the given dimension.
Returns
a status

Definition at line 86 of file NETileKernel.cpp.

References ARM_COMPUTE_RETURN_ON_ERROR, and arm_compute::validate_arguments().

Referenced by NETileKernel::name(), and NETile::validate().

87 {
89  return Status{};
90 }
#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 *input, const ITensorInfo *bias, const ITensorInfo *output, const GEMMLowpOutputStageInfo *output_stage)

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