Compute Library
 21.08
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...
 
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...
 
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 *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 36 of file NESpaceToBatchLayerKernel.h.

Constructor & Destructor Documentation

◆ NESpaceToBatchLayerKernel() [1/3]

Default constructor.

Definition at line 88 of file NESpaceToBatchLayerKernel.cpp.

References arm_compute::UNKNOWN.

Referenced by NESpaceToBatchLayerKernel::name().

89  : _input(nullptr), _block_shape(nullptr), _paddings(nullptr), _output(nullptr), _data_layout(DataLayout::UNKNOWN), _padding_left(), _block_shape_x(), _block_shape_y()
90 {
91 }

◆ 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.

Referenced by NESpaceToBatchLayerKernel::name().

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: All.
[in]block_shape1-D tensor with shape [M]. Supported M: 2. Data types supported: S32
[in]paddings2-D tensor with shape [2, M] (First dimension is the fastest-changing dimension). Supported M: 2. Data types supported: S32
[out]outputTensor output. Data types supported: same as input

Definition at line 93 of file NESpaceToBatchLayerKernel.cpp.

References ARM_COMPUTE_ERROR_ON_NULLPTR, ARM_COMPUTE_ERROR_THROW_ON, arm_compute::calculate_max_window(), ITensorInfo::data_layout(), ITensor::info(), and arm_compute::test::validation::input.

Referenced by NESpaceToBatchLayerKernel::name().

94 {
95  ARM_COMPUTE_ERROR_ON_NULLPTR(input, block_shape, paddings, output);
96  ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), block_shape->info(), paddings->info(), output->info()));
97 
98  _input = input;
99  _block_shape = block_shape;
100  _paddings = paddings;
101  _output = output;
102  _data_layout = input->info()->data_layout();
103 
104  // Configure kernel window
105  Window win = calculate_max_window(*output->info(), Steps());
106  ICPPKernel::configure(win);
107 }
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
#define ARM_COMPUTE_ERROR_ON_NULLPTR(...)
Definition: Validate.h:157

◆ 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: All.
[in]block_shape_xBlock shape x value.
[in]block_shape_yBlock shape y value.
[in]padding_leftThe padding at the beginning of every dimension of the output tensor.
[in]padding_rightThe padding at the end of every dimension of the output tensor.
[out]outputTensor output. Data types supported: same as input

Definition at line 109 of file NESpaceToBatchLayerKernel.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_space_to_batch_shape(), ITensorInfo::data_layout(), ITensorInfo::data_type(), ITensor::info(), arm_compute::test::validation::input, arm_compute::test::validation::output_shape, and ITensorInfo::quantization_info().

111 {
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  _data_layout = input->info()->data_layout();
125 
126  // Configure kernel window
127  Window win = calculate_max_window(*output->info(), Steps());
128  INEKernel::configure(win);
129 }
Window calculate_max_window(const ValidRegion &valid_region, const Steps &steps, bool skip_border, BorderSize border_size)
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:455
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...
#define ARM_COMPUTE_ERROR_ON_NULLPTR(...)
Definition: Validate.h:157

◆ name()

◆ operator=() [1/2]

NESpaceToBatchLayerKernel& operator= ( const NESpaceToBatchLayerKernel )
delete

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

Referenced by NESpaceToBatchLayerKernel::name().

◆ 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.

Reimplemented from ICPPKernel.

Definition at line 143 of file NESpaceToBatchLayerKernel.cpp.

References ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW, ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL, ARM_COMPUTE_UNUSED, arm_compute::BATCHES, 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::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().

Referenced by NESpaceToBatchLayerKernel::name().

144 {
148 
149  if(_block_shape != nullptr)
150  {
151  // Retrieve the block shapes dynamically
152  _block_shape_x = *(reinterpret_cast<const int *>(_block_shape->ptr_to_element(0)));
153  _block_shape_y = *(reinterpret_cast<const int *>(_block_shape->ptr_to_element(1)));
154  }
155 
156  if(_paddings != nullptr)
157  {
158  const size_t pad_left_x = *reinterpret_cast<const size_t *>(_paddings->ptr_to_element({ 0, 0 }));
159  const size_t pad_left_y = *reinterpret_cast<const size_t *>(_paddings->ptr_to_element({ 1, 0 }));
160  _padding_left = Size2D(pad_left_x, pad_left_y);
161  }
162  const int height_idx = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::HEIGHT);
163  const int width_idx = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::WIDTH);
164  const int batch_idx = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::BATCHES);
165  const int element_size = _input->info()->element_size();
166 
167  const size_t height = _input->info()->dimension(height_idx);
168  const size_t width = _input->info()->dimension(width_idx);
169  const size_t batch_size = _input->info()->dimension(batch_idx);
170 
171  Window slice_out = window.first_slice_window_3D();
172 
173  int batch_id = 0;
174 
175  // Main loop for NCHW and NHWC
176  if(_data_layout == DataLayout::NCHW)
177  {
178  do
179  {
180  Iterator out(_output, slice_out);
181  execute_window_loop(slice_out, [&](const Coordinates & id)
182  {
183  const size_t out_x = id.x();
184  const size_t out_y = id.y();
185  const size_t z = id.z();
186  const size_t pos_x = out_x * _block_shape_x + (batch_id / batch_size) % _block_shape_x;
187  const size_t pos_y = out_y * _block_shape_y + (batch_id / batch_size) / _block_shape_x;
188  if(pos_y >= _padding_left.y() && pos_y < _padding_left.y() + height && pos_x >= _padding_left.x() && pos_x < _padding_left.x() + width)
189  {
190  const int w = batch_id % batch_size;
191  const int in_x = pos_x - _padding_left.x();
192  const int in_y = pos_y - _padding_left.y();
193  Coordinates input_coords{ in_x, in_y, z, w };
194  memcpy(out.ptr(), _input->ptr_to_element(input_coords), element_size);
195  }
196  },
197  out);
198  ++batch_id;
199  }
200  while(window.slide_window_slice_3D(slice_out));
201  }
202  else
203  {
204  do
205  {
206  Iterator out(_output, slice_out);
207  execute_window_loop(slice_out, [&](const Coordinates & id)
208  {
209  const size_t out_x = id.y();
210  const size_t out_y = id.z();
211  const size_t z = id.x();
212  const size_t pos_x = out_x * _block_shape_x + (batch_id / batch_size) % _block_shape_x;
213  const size_t pos_y = out_y * _block_shape_y + (batch_id / batch_size) / _block_shape_x;
214  if(pos_y >= _padding_left.y() && pos_y < _padding_left.y() + height && pos_x >= _padding_left.x() && pos_x < _padding_left.x() + width)
215  {
216  const int w = batch_id % batch_size;
217  const int in_x = pos_x - _padding_left.x();
218  const int in_y = pos_y - _padding_left.y();
219  Coordinates input_coords{ z, in_x, in_y, w };
220  memcpy(out.ptr(), _input->ptr_to_element(input_coords), element_size);
221  }
222  },
223  out);
224  ++batch_id;
225  }
226  while(window.slide_window_slice_3D(slice_out));
227  }
228 }
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.
size_t x() const
Semantic accessor for width as x.
Definition: Size2D.h:74
#define ARM_COMPUTE_UNUSED(...)
To avoid unused variables warnings.
Definition: Error.h:152
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()
bool slide_window_slice_3D(Window &slice) const
Slide the passed 3D window slice.
Definition: Window.h:335
#define ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(k)
Definition: Validate.h:915
Num samples, channels, height, width.
size_t y() const
Semantic accessor for height as y.
Definition: Size2D.h:83
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
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
Window first_slice_window_3D() const
First 3D slice of the window.
Definition: Window.h:291
#define ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(f, s)
Definition: Validate.h:201

◆ 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: All.
[in]block_shape1-D tensor with shape [M]. Supported M: 2. Data types supported: S32
[in]paddings2-D tensor with shape [2, M] (First dimension is the fastest-changing dimension). Supported M: 2. Data types supported: S32
[in]outputTensor output. Data types supported: same as input
Returns
a status

Definition at line 131 of file NESpaceToBatchLayerKernel.cpp.

References ARM_COMPUTE_RETURN_ON_ERROR.

Referenced by NESpaceToBatchLayerKernel::name(), and NESpaceToBatchLayer::validate().

132 {
133  ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, block_shape, paddings, output));
134  return Status{};
135 }
#define ARM_COMPUTE_RETURN_ON_ERROR(status)
Checks if a status contains an error and returns it.
Definition: Error.h:204

◆ 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: All.
[in]block_shape_xBlock shape x value.
[in]block_shape_yBlock shape y value.
[in]padding_leftThe padding at the beginning of every dimension of the output tensor.
[in]padding_rightThe padding at the end of every dimension of the output tensor.
[in]outputTensor output. Data types supported: same as input
Returns
a status

Definition at line 136 of file NESpaceToBatchLayerKernel.cpp.

References ARM_COMPUTE_RETURN_ON_ERROR.

138 {
139  ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_static(input, block_shape_x, block_shape_y, padding_left, padding_right, output));
140  return Status{};
141 }
#define ARM_COMPUTE_RETURN_ON_ERROR(status)
Checks if a status contains an error and returns it.
Definition: Error.h:204

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