Compute Library
 19.08
NESpaceToBatchLayerKernel Class Reference

Interface for the space to batch kernel. More...

#include <NESpaceToBatchLayerKernel.h>

Collaboration diagram for NESpaceToBatchLayerKernel:
[legend]

Public Member Functions

const char * name () const override
 Name of the kernel. More...
 
 NESpaceToBatchLayerKernel ()
 Default constructor. More...
 
 NESpaceToBatchLayerKernel (const NESpaceToBatchLayerKernel &)=delete
 Prevent instances of this class from being copied (As this class contains pointers) More...
 
NESpaceToBatchLayerKerneloperator= (const NESpaceToBatchLayerKernel &)=delete
 Prevent instances of this class from being copied (As this class contains pointers) More...
 
 NESpaceToBatchLayerKernel (NESpaceToBatchLayerKernel &&)=default
 Allow instances of this class to be moved. More...
 
NESpaceToBatchLayerKerneloperator= (NESpaceToBatchLayerKernel &&)=default
 Allow instances of this class to be moved. More...
 
 ~NESpaceToBatchLayerKernel ()=default
 Default destructor. More...
 
void configure (const ITensor *input, const ITensor *block_shape, const ITensor *paddings, ITensor *output)
 Initialise the kernel's inputs and output. More...
 
void configure (const ITensor *input, const int block_shape_x, const int block_shape_y, const Size2D &padding_left, const Size2D &padding_right, ITensor *output)
 Initialise the kernel's input and output. 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...
 
- 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 *block_shape, const ITensorInfo *paddings, const ITensorInfo *output)
 Static function to check if given info will lead to a valid configuration of NESpaceToBatchLayerKernel. More...
 
static Status validate (const ITensorInfo *input, const int block_shape_x, const int block_shape_y, const Size2D &padding_left, const Size2D &padding_right, const ITensorInfo *output)
 Static function to check if given info will lead to a valid configuration of NESpaceToBatchLayerKernel (Static block shape and paddings) More...
 

Detailed Description

Interface for the space to batch kernel.

Definition at line 35 of file NESpaceToBatchLayerKernel.h.

Constructor & Destructor Documentation

◆ NESpaceToBatchLayerKernel() [1/3]

Default constructor.

Definition at line 89 of file NESpaceToBatchLayerKernel.cpp.

90  : _input(nullptr), _block_shape(nullptr), _paddings(nullptr), _output(nullptr), _padding_left(), _block_shape_x(), _block_shape_y()
91 {
92 }

◆ NESpaceToBatchLayerKernel() [2/3]

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

◆ NESpaceToBatchLayerKernel() [3/3]

Allow instances of this class to be moved.

◆ ~NESpaceToBatchLayerKernel()

Default destructor.

Member Function Documentation

◆ configure() [1/2]

void configure ( const ITensor input,
const ITensor block_shape,
const ITensor paddings,
ITensor output 
)

Initialise the kernel's inputs and output.

Parameters
[in]inputTensor input. Supported tensor rank: 4. Data types supported: U8/S8/QASYMM8/U16/S16/F16/U32/S32/F32.
[in]block_shape1-D tensor with shape [M]. Data types supported: S32
[in]paddings2-D tensor with shape [2, M]. Data types supported: S32
[out]outputTensor output. Data types supported: same as input

Definition at line 94 of file NESpaceToBatchLayerKernel.cpp.

95 {
96  ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
97  ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), block_shape->info(), paddings->info(), output->info()));
98 
99  _input = input;
100  _block_shape = block_shape;
101  _paddings = paddings;
102  _output = output;
103 
104  // Configure kernel window
105  Window win = calculate_max_window(*output->info(), Steps());
106  ICPPKernel::configure(win);
107 }
#define ARM_COMPUTE_ERROR_THROW_ON(status)
Definition: Error.h:327
Window calculate_max_window(const ValidRegion &valid_region, const Steps &steps=Steps(), bool skip_border=false, BorderSize border_size=BorderSize())
Calculate the maximum window for a given tensor shape and border setting.
Definition: Helpers.cpp:28
#define ARM_COMPUTE_ERROR_ON_NULLPTR(...)
Definition: Validate.h:161

References ARM_COMPUTE_ERROR_ON_NULLPTR, ARM_COMPUTE_ERROR_THROW_ON, arm_compute::calculate_max_window(), and ITensor::info().

Referenced by NESpaceToBatchLayer::configure().

◆ configure() [2/2]

void configure ( const ITensor input,
const int  block_shape_x,
const int  block_shape_y,
const Size2D padding_left,
const Size2D padding_right,
ITensor output 
)

Initialise the kernel's input and output.

(Static block shape and paddings)

Parameters
[in]inputTensor input. Supported tensor rank: 4. Data types supported: U8/S8/QASYMM8/U16/S16/F16/U32/S32/F32.
[in]block_shape_xBlock shape x value.
[in]block_shape_yBlock shape y value.
[in]padding_leftThe left padding of the output tensor.
[in]padding_rightThe right padding of the output tensor.
[out]outputTensor output. Data types supported: same as input

Definition at line 109 of file NESpaceToBatchLayerKernel.cpp.

111 {
112  ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
113 
114  TensorShape output_shape = misc::shape_calculator::compute_space_to_batch_shape(input->info(), block_shape_x, block_shape_y, padding_left, padding_right);
115  auto_init_if_empty(*output->info(), output_shape, 1, input->info()->data_type(), input->info()->quantization_info());
116 
117  ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_static(input->info(), block_shape_x, block_shape_y, padding_left, padding_right, output->info()));
118 
119  _input = input;
120  _output = output;
121  _block_shape_x = block_shape_x;
122  _block_shape_y = block_shape_y;
123  _padding_left = padding_left;
124 
125  // Configure kernel window
126  Window win = calculate_max_window(*output->info(), Steps());
127  INEKernel::configure(win);
128 }
TensorShape compute_space_to_batch_shape(const ITensorInfo *input, const int block_x, const int block_y, const Size2D &padding_left, const Size2D &padding_right)
Calculate the space to batch output shape of a tensor.
#define ARM_COMPUTE_ERROR_THROW_ON(status)
Definition: Error.h:327
Window calculate_max_window(const ValidRegion &valid_region, const Steps &steps=Steps(), bool skip_border=false, BorderSize border_size=BorderSize())
Calculate the maximum window for a given tensor shape and border setting.
Definition: Helpers.cpp:28
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...
Definition: Helpers.inl:201
#define ARM_COMPUTE_ERROR_ON_NULLPTR(...)
Definition: Validate.h:161

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_space_to_batch_shape(), ITensorInfo::data_type(), ITensor::info(), arm_compute::test::validation::output_shape, and ITensorInfo::quantization_info().

◆ name()

const char* name ( ) const
inlineoverridevirtual

Name of the kernel.

Returns
Kernel name

Implements ICPPKernel.

Definition at line 38 of file NESpaceToBatchLayerKernel.h.

39  {
40  return "NESpaceToBatchLayerKernel";
41  }

◆ operator=() [1/2]

NESpaceToBatchLayerKernel& operator= ( const NESpaceToBatchLayerKernel )
delete

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,
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.

Implements ICPPKernel.

Definition at line 142 of file NESpaceToBatchLayerKernel.cpp.

143 {
147 
148  if(_block_shape != nullptr)
149  {
150  // Retrieve the block shapes dynamically
151  _block_shape_x = *(reinterpret_cast<const int *>(_block_shape->ptr_to_element(0)));
152  _block_shape_y = *(reinterpret_cast<const int *>(_block_shape->ptr_to_element(1)));
153  }
154 
155  if(_paddings != nullptr)
156  {
157  const size_t pad_left_x = *reinterpret_cast<const size_t *>(_paddings->ptr_to_element({ 0, 0 }));
158  const size_t pad_left_y = *reinterpret_cast<const size_t *>(_paddings->ptr_to_element({ 1, 0 }));
159  _padding_left = Size2D(pad_left_x, pad_left_y);
160  }
161  const DataLayout data_layout = _input->info()->data_layout();
164  const int element_size = _input->info()->element_size();
165 
166  const size_t height = _input->info()->dimension(height_idx);
167  const size_t width = _input->info()->dimension(width_idx);
168  const size_t batch_size = _input->info()->dimension(3);
169 
170  Window slice_out = window.first_slice_window_3D();
171 
172  int batch_id = 0;
173 
174  // Main loop for NCHW and NHWC
175  if(_output->info()->data_layout() == DataLayout::NCHW)
176  {
177  do
178  {
179  Iterator out(_output, slice_out);
180  execute_window_loop(slice_out, [&](const Coordinates & id)
181  {
182  const size_t out_x = id.x();
183  const size_t out_y = id.y();
184  const size_t z = id.z();
185  const size_t pos_x = out_x * _block_shape_x + (batch_id / batch_size) % _block_shape_x;
186  const size_t pos_y = out_y * _block_shape_y + (batch_id / batch_size) / _block_shape_x;
187  if(pos_y >= _padding_left.y() && pos_y < _padding_left.y() + height && pos_x >= _padding_left.x() && pos_x < _padding_left.x() + width)
188  {
189  const int w = batch_id % batch_size;
190  const int in_x = pos_x - _padding_left.x();
191  const int in_y = pos_y - _padding_left.y();
192  Coordinates input_coords{ in_x, in_y, z, w };
193  memcpy(out.ptr(), _input->ptr_to_element(input_coords), element_size);
194  }
195  },
196  out);
197  ++batch_id;
198  }
199  while(window.slide_window_slice_3D(slice_out));
200  }
201  else
202  {
203  do
204  {
205  Iterator out(_output, slice_out);
206  execute_window_loop(slice_out, [&](const Coordinates & id)
207  {
208  const size_t out_x = id.y();
209  const size_t out_y = id.z();
210  const size_t z = id.x();
211  const size_t pos_x = out_x * _block_shape_x + (batch_id / batch_size) % _block_shape_x;
212  const size_t pos_y = out_y * _block_shape_y + (batch_id / batch_size) / _block_shape_x;
213  if(pos_y >= _padding_left.y() && pos_y < _padding_left.y() + height && pos_x >= _padding_left.x() && pos_x < _padding_left.x() + width)
214  {
215  const int w = batch_id % batch_size;
216  const int in_x = pos_x - _padding_left.x();
217  const int in_y = pos_y - _padding_left.y();
218  Coordinates input_coords{ z, in_x, in_y, w };
219  memcpy(out.ptr(), _input->ptr_to_element(input_coords), element_size);
220  }
221  },
222  out);
223  ++batch_id;
224  }
225  while(window.slide_window_slice_3D(slice_out));
226  }
227 }
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
const DataLayout data_layout
Definition: Im2Col.cpp:146
virtual size_t dimension(size_t index) const =0
Return the size of the requested dimension.
size_t x() const
Semantic accessor for width as x.
Definition: Size2D.h:77
#define ARM_COMPUTE_UNUSED(...)
To avoid unused variables warnings.
Definition: Error.h:160
virtual ITensorInfo * info() const =0
Interface to be implemented by the child class to return the tensor's metadata.
virtual size_t element_size() const =0
Element size in bytes calculated as data_size() * num_channels()
bool slide_window_slice_3D(Window &slice) const
Slide the passed 3D window slice.
Definition: Window.h:319
Num samples, channels, height, width.
size_t y() const
Semantic accessor for height as y.
Definition: Size2D.h:86
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:122
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:326
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
DataLayout
[DataLayout enum definition]
Definition: Types.h:114
#define ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(k)
Definition: Validate.h:940
virtual DataLayout data_layout() const =0
Get the data layout of the tensor.

References ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW, ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL, ARM_COMPUTE_UNUSED, arm_compute::test::validation::data_layout, ITensorInfo::data_layout(), ITensorInfo::dimension(), ITensorInfo::element_size(), arm_compute::execute_window_loop(), Window::first_slice_window_3D(), arm_compute::get_data_layout_dimension_index(), arm_compute::HEIGHT, ITensor::info(), arm_compute::test::validation::info, arm_compute::NCHW, Iterator::ptr(), ITensor::ptr_to_element(), Window::slide_window_slice_3D(), arm_compute::test::validation::w, arm_compute::WIDTH, IKernel::window(), Size2D::x(), Window::x(), Size2D::y(), and Window::y().

◆ validate() [1/2]

Status validate ( const ITensorInfo input,
const ITensorInfo block_shape,
const ITensorInfo paddings,
const ITensorInfo output 
)
static

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

Parameters
[in]inputTensor input. Supported tensor rank: 4. Data types supported: U8/S8/QASYMM8/U16/S16/F16/U32/S32/F32.
[in]block_shape1-D tensor with shape [M]. Data types supported: S32
[in]paddings2-D tensor with shape [2, M]. Data types supported: S32
[in]outputTensor output. Data types supported: same as input
Returns
a status

Definition at line 130 of file NESpaceToBatchLayerKernel.cpp.

131 {
132  ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, block_shape, paddings, output));
133  return Status{};
134 }
#define ARM_COMPUTE_RETURN_ON_ERROR(status)
Checks if a status contains an error and returns it.
Definition: Error.h:193

References ARM_COMPUTE_RETURN_ON_ERROR.

Referenced by NESpaceToBatchLayer::validate().

◆ validate() [2/2]

Status validate ( const ITensorInfo input,
const int  block_shape_x,
const int  block_shape_y,
const Size2D padding_left,
const Size2D padding_right,
const ITensorInfo output 
)
static

Static function to check if given info will lead to a valid configuration of NESpaceToBatchLayerKernel (Static block shape and paddings)

Parameters
[in]inputTensor input. Supported tensor rank: 4. Data types supported: U8/S8/QASYMM8/U16/S16/F16/U32/S32/F32.
[in]block_shape_xBlock shape x value.
[in]block_shape_yBlock shape y value.
[in]padding_leftThe left padding of the output tensor.
[in]padding_rightThe right padding of the output tensor.
[in]outputTensor output. Data types supported: same as input
Returns
a status

Definition at line 135 of file NESpaceToBatchLayerKernel.cpp.

137 {
138  ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_static(input, block_shape_x, block_shape_y, padding_left, padding_right, output));
139  return Status{};
140 }
#define ARM_COMPUTE_RETURN_ON_ERROR(status)
Checks if a status contains an error and returns it.
Definition: Error.h:193

References ARM_COMPUTE_RETURN_ON_ERROR.


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