Compute Library
 21.02
CLMaxUnpoolingLayerKernel Class Reference

Interface for the pooling layer kernel. More...

#include <CLMaxUnpoolingLayerKernel.h>

Collaboration diagram for CLMaxUnpoolingLayerKernel:
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Public Member Functions

 CLMaxUnpoolingLayerKernel ()
 Default constructor. More...
 
 CLMaxUnpoolingLayerKernel (const CLMaxUnpoolingLayerKernel &)=delete
 Prevent instances of this class from being copied (As this class contains pointers) More...
 
CLMaxUnpoolingLayerKerneloperator= (const CLMaxUnpoolingLayerKernel &)=delete
 Prevent instances of this class from being copied (As this class contains pointers) More...
 
 CLMaxUnpoolingLayerKernel (CLMaxUnpoolingLayerKernel &&)=default
 Allow instances of this class to be moved. More...
 
CLMaxUnpoolingLayerKerneloperator= (CLMaxUnpoolingLayerKernel &&)=default
 Allow instances of this class to be moved. More...
 
 ~CLMaxUnpoolingLayerKernel ()=default
 Default destructor. More...
 
void configure (const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *indices, ICLTensor *output, const PoolingLayerInfo &pool_info)
 Set the input and output tensors. 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 *indices, const ITensorInfo *output, const PoolingLayerInfo &pool_info)
 Static function to check if given info will lead to a valid configuration of CLMaxUnpoolingLayerKernel. 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...
 

Detailed Description

Interface for the pooling layer kernel.

Definition at line 34 of file CLMaxUnpoolingLayerKernel.h.

Constructor & Destructor Documentation

◆ CLMaxUnpoolingLayerKernel() [1/3]

Default constructor.

Definition at line 75 of file CLMaxUnpoolingLayerKernel.cpp.

76  : _input(nullptr), _output(nullptr), _indices(nullptr)
77 {
78 }

◆ CLMaxUnpoolingLayerKernel() [2/3]

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

◆ CLMaxUnpoolingLayerKernel() [3/3]

Allow instances of this class to be moved.

◆ ~CLMaxUnpoolingLayerKernel()

Default destructor.

Member Function Documentation

◆ configure()

void configure ( const CLCompileContext compile_context,
const ICLTensor input,
const ICLTensor indices,
ICLTensor output,
const PoolingLayerInfo pool_info 
)

Set the input and output tensors.

Note
Output shape must be equal to the shape of the original input to pool.
Parameters
[in]compile_contextThe compile context to be used.
[in]inputSource tensor. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
[in]indicesTensor containing the offset to store the input elements in the output tensor. opencl::ClPooling with indices should precede this function in order to properly reconstruct the output tensor. The tensor shape of this tensor has to be equal to the input tensor shape. Data type supported: U32.
[out]outputDestination tensor. Data types supported: Same as input.
[in]pool_infoContains pooling operation information described in PoolingLayerInfo.

Definition at line 80 of file CLMaxUnpoolingLayerKernel.cpp.

References CLBuildOptions::add_option(), ARM_COMPUTE_ERROR_ON, ARM_COMPUTE_ERROR_ON_NULLPTR, ARM_COMPUTE_ERROR_THROW_ON, arm_compute::auto_init_if_empty(), arm_compute::calculate_max_window(), ICloneable< T >::clone(), arm_compute::misc::shape_calculator::compute_unpool_shape(), arm_compute::create_kernel(), ITensorInfo::data_type(), ITensorInfo::dimension(), ITensorInfo::element_size(), arm_compute::get_cl_unsigned_type_from_element_size(), arm_compute::get_padding_info(), arm_compute::has_padding_changed(), ITensor::info(), arm_compute::test::validation::input, kernel_name, arm_compute::lower_string(), CLBuildOptions::options(), arm_compute::test::validation::output_shape, arm_compute::string_from_data_type(), arm_compute::support::cpp11::to_string(), arm_compute::validate_arguments(), and IKernel::window().

81 {
83  ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), pool_info, indices->info()));
84  auto padding_info = get_padding_info({ input, indices, output });
85 
86  _input = input;
87  _output = output;
88  _indices = indices;
89 
90  // Create build options
91  CLBuildOptions build_opts;
92  build_opts.add_option("-DDATA_TYPE=" + get_cl_unsigned_type_from_element_size(input->info()->element_size()));
93  build_opts.add_option("-DWIDTH_DST=" + support::cpp11::to_string(output->info()->dimension(0)));
94  build_opts.add_option("-DHEIGHT_DST=" + support::cpp11::to_string(output->info()->dimension(1)));
95  build_opts.add_option("-DDEPTH_DST=" + support::cpp11::to_string(output->info()->dimension(2)));
96 
97  const std::string kernel_name("max_unpooling_layer_2");
98 
99  // Create kernel
100  _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
101 
102  const TensorShape output_shape = compute_unpool_shape(*input->info(), pool_info);
103  auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(output_shape));
104 
105  auto window = calculate_max_window(*input->info(), Steps());
106  ICLKernel::configure_internal(window);
107 
108  // Set config_id for enabling LWS tuning
109  _config_id = kernel_name;
110  _config_id += lower_string(string_from_data_type(input->info()->data_type()));
111  _config_id += "_";
112  _config_id += support::cpp11::to_string(output->info()->dimension(0));
113  _config_id += "_";
114  _config_id += support::cpp11::to_string(output->info()->dimension(1));
115  _config_id += "_";
116  _config_id += support::cpp11::to_string(output->info()->dimension(2));
117  _config_id += "_";
118  _config_id += support::cpp11::to_string(output->info()->dimension(3));
120 }
Window calculate_max_window(const ValidRegion &valid_region, const Steps &steps, bool skip_border, BorderSize border_size)
const Window & window() const
The maximum window the kernel can be executed on.
Definition: IKernel.cpp:28
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
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
TensorShape compute_unpool_shape(const ITensorInfo &input, PoolingLayerInfo pool_info)
Calculate the output unpool shape of a tensor.
std::string kernel_name
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...
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
std::string get_cl_unsigned_type_from_element_size(size_t element_size)
Translates the element size to an unsigned integer data type.
Definition: CLHelpers.cpp:103
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)
#define ARM_COMPUTE_ERROR_ON_NULLPTR(...)
Definition: Validate.h:161

◆ operator=() [1/2]

CLMaxUnpoolingLayerKernel& operator= ( const CLMaxUnpoolingLayerKernel )
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,
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 129 of file CLMaxUnpoolingLayerKernel.cpp.

References ICLKernel::add_3D_tensor_argument(), ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW, ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL, arm_compute::enqueue(), Window::first_slice_window_3D(), ICLKernel::lws_hint(), arm_compute::test::validation::reference::slice(), Window::slide_window_slice_3D(), and IKernel::window().

130 {
133 
135 
136  do
137  {
138  unsigned int idx = 0;
139  add_3D_tensor_argument(idx, _input, slice);
140  add_3D_tensor_argument(idx, _output, slice);
141  add_3D_tensor_argument(idx, _indices, slice);
142  enqueue(queue, *this, slice, lws_hint());
143  }
144  while(window.slide_window_slice_3D(slice));
145 }
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
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
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:941
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:205
SimpleTensor< T > slice(const SimpleTensor< T > &src, Coordinates starts, Coordinates ends)

◆ validate()

Status validate ( const ITensorInfo input,
const ITensorInfo indices,
const ITensorInfo output,
const PoolingLayerInfo pool_info 
)
static

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

Parameters
[in]inputSource tensor info. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
[in]outputDestination tensor info. Data types supported: Same as input.
[in]indicesTensorInfo associated to the tensor containing the offset to store the input elements in the output tensor. opencl::ClPooling with indices should precede this function in order to properly reconstruct the output tensor. The tensor shape of this tensor has to be equal to the input tensor shape. Data type supported: U32.
[in]pool_infoContains pooling operation information described in PoolingLayerInfo.
Returns
a status

Definition at line 122 of file CLMaxUnpoolingLayerKernel.cpp.

References ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR, ARM_COMPUTE_RETURN_ON_ERROR, and arm_compute::validate_arguments().

Referenced by CLMaxUnpoolingLayer::validate().

123 {
124  ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, indices, output);
125  ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, pool_info, indices));
126  return Status{};
127 }
#define ARM_COMPUTE_RETURN_ON_ERROR(status)
Checks if a status contains an error and returns it.
Definition: Error.h:204
#define ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(...)
Definition: Validate.h:163
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: