Compute Library
 19.08
GCGEMMMatrixAccumulateBiasesKernel Class Reference

Interface to add a bias to each row of the input tensor. More...

#include <GCGEMMMatrixAccumulateBiasesKernel.h>

Collaboration diagram for GCGEMMMatrixAccumulateBiasesKernel:
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Public Member Functions

 GCGEMMMatrixAccumulateBiasesKernel ()
 Default constructor. More...
 
 GCGEMMMatrixAccumulateBiasesKernel (const GCGEMMMatrixAccumulateBiasesKernel &)=delete
 Prevent instances of this class from being copied (As this class contains pointers) More...
 
GCGEMMMatrixAccumulateBiasesKerneloperator= (const GCGEMMMatrixAccumulateBiasesKernel &)=delete
 Prevent instances of this class from being copied (As this class contains pointers) More...
 
 GCGEMMMatrixAccumulateBiasesKernel (GCGEMMMatrixAccumulateBiasesKernel &&)=default
 Allow instances of this class to be moved. More...
 
GCGEMMMatrixAccumulateBiasesKerneloperator= (GCGEMMMatrixAccumulateBiasesKernel &&)=default
 Allow instances of this class to be moved. More...
 
void configure (IGCTensor *accum, const IGCTensor *biases)
 Set the accumulate buffer and the biases of the kernel. More...
 
void run (const Window &window) override
 Enqueue the OpenGL ES shader to process the given window. More...
 
- Public Member Functions inherited from IGCKernel
 IGCKernel ()
 Constructor. More...
 
GCKernelkernel ()
 Returns a reference to the GLES kernel of this object. More...
 
void add_1D_tensor_argument (unsigned int &idx, const IGCTensor *tensor, const unsigned int binding_point, 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_2D_tensor_argument (unsigned int &idx, const IGCTensor *tensor, const unsigned int binding_point, 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_3D_tensor_argument (unsigned int &idx, const IGCTensor *tensor, const unsigned int binding_point, const Window &window)
 Add the passed 3D tensor's parameters to the object's kernel's arguments starting from the index idx. More...
 
unsigned int num_arguments_per_1D_tensor () const
 Returns the number of arguments enqueued per 1D tensor object. More...
 
unsigned int num_arguments_per_2D_tensor () const
 Returns the number of arguments enqueued per 2D tensor object. More...
 
unsigned int num_arguments_per_3D_tensor () const
 Returns the number of arguments enqueued per 3D tensor object. More...
 
void set_lws_hint (gles::NDRange &lws_hint)
 Set the Local-Workgroup-Size hint. More...
 
void set_target (GPUTarget target)
 Set the targeted GPU architecture. More...
 
GPUTarget get_target () const
 Get the targeted GPU architecture. 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...
 

Detailed Description

Interface to add a bias to each row of the input tensor.

Definition at line 34 of file GCGEMMMatrixAccumulateBiasesKernel.h.

Constructor & Destructor Documentation

◆ GCGEMMMatrixAccumulateBiasesKernel() [1/3]

Default constructor.

Definition at line 39 of file GCGEMMMatrixAccumulateBiasesKernel.cpp.

40  : _accum(nullptr), _biases(nullptr), _lws(gles::NDRange(1U, 1U, 1U))
41 {
42 }
Class interface for specifying NDRange values.
Definition: OpenGLES.h:53

◆ GCGEMMMatrixAccumulateBiasesKernel() [2/3]

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

◆ GCGEMMMatrixAccumulateBiasesKernel() [3/3]

Allow instances of this class to be moved.

Member Function Documentation

◆ configure()

void configure ( IGCTensor accum,
const IGCTensor biases 
)

Set the accumulate buffer and the biases of the kernel.

Parameters
[in,out]accumThe accumulate tensor to convert. Data types supported: F16/F32
[in]biasesThe shared biases tensor to append. It must be 1D tensor. Data types supported: Same as input

Definition at line 44 of file GCGEMMMatrixAccumulateBiasesKernel.cpp.

45 {
48  ARM_COMPUTE_ERROR_ON(biases->info()->num_dimensions() != 1);
49 
50  _biases = biases;
51  _accum = accum;
52 
53  std::set<std::string> build_opts;
54  build_opts.emplace("#define LOCAL_SIZE_X " + support::cpp11::to_string(_lws[0]));
55  build_opts.emplace("#define LOCAL_SIZE_Y " + support::cpp11::to_string(_lws[1]));
56  build_opts.emplace("#define LOCAL_SIZE_Z " + support::cpp11::to_string(_lws[2]));
57 
58  // Create kernel
59  build_opts.emplace("#define GEMM_ACCUMULATE_BIASES");
60 
61 #define ACCUM_PROCESS_4X
62 
63 #if defined(ACCUM_PROCESS_4X)
64  build_opts.emplace("#define ACCUM_PROCESS_4X");
65 #elif defined(ACCUM_PROCESS_8X) /* ACCUM_PROCESS_4X */
66  build_opts.emplace("#define ACCUM_PROCESS_8X");
67 #endif /* ACCUM_PROCESS_4X */
68  std::string dt_name = (accum->info()->data_type() == DataType::F32) ? "DATA_TYPE_FP32" : "DATA_TYPE_FP16";
69  build_opts.emplace(("#define " + dt_name));
70 
71  _kernel = GCKernelLibrary::get().create_kernel("gemm_accumulate_biases", build_opts);
72 
73  // Configure kernel window
74  unsigned int num_elems_processed_per_iteration = 1;
75 
76  if(_accum->info()->data_type() == DataType::F32)
77  {
78  num_elems_processed_per_iteration = 16;
79  }
80  else if(_accum->info()->data_type() == DataType::F16)
81  {
82 #if defined(ACCUM_PROCESS_4X)
83  num_elems_processed_per_iteration = 4;
84 #elif defined(ACCUM_PROCESS_8X) /* ACCUM_PROCESS_4X */
85  num_elems_processed_per_iteration = 8;
86 #endif /* ACCUM_PROCESS_4X */
87  }
88 
89  const int accum_width = accum->info()->dimension(0);
90  const int accum_padding_right = ceil_to_multiple(accum_width, num_elems_processed_per_iteration * _lws[0]) - accum_width;
91  BorderSize border = BorderSize(0, accum_padding_right, 0, 0);
92 
93  Window win = calculate_max_enlarged_window(*_accum->info(), Steps(num_elems_processed_per_iteration), border);
94 
95  AccessWindowStatic biases_access(biases->info(), 0, 0, ceil_to_multiple(biases->info()->dimension(0), num_elems_processed_per_iteration * _lws[0]), biases->info()->dimension(1));
96  AccessWindowStatic accum_access(_accum->info(), 0, 0, accum_width + accum_padding_right, _accum->info()->dimension(1));
97 
98  update_window_and_padding(win, biases_access, accum_access);
99 
100  IGCKernel::configure(win);
101 }
virtual size_t num_dimensions() const =0
The number of dimensions of the tensor (rank)
virtual size_t dimension(size_t index) const =0
Return the size of the requested dimension.
#define ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(...)
Definition: Validate.h:543
Container for 2D border size.
Definition: Types.h:259
std::string to_string(T &&value)
Convert integer and float values to string.
virtual DataType data_type() const =0
Data type used for each element of the tensor.
1 channel, 1 F32 per channel
#define ARM_COMPUTE_ERROR_ON(cond)
If the condition is true then an error message is printed and an exception thrown.
Definition: Error.h:337
1 channel, 1 F16 per channel
Implementation of a static rectangular access pattern.
Window calculate_max_enlarged_window(const ValidRegion &valid_region, const Steps &steps=Steps(), BorderSize border_size=BorderSize())
Calculate the maximum window for a given tensor shape and border setting.
Definition: Helpers.cpp:82
bool update_window_and_padding(Window &win, Ts &&... patterns)
Update window and padding size for each of the access patterns.
Definition: Helpers.h:402
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:66
Class to describe a number of elements in each dimension.
Definition: Steps.h:40
virtual ITensorInfo * info() const =0
Interface to be implemented by the child class to return the tensor's metadata.
#define ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(t, c,...)
Definition: Validate.h:789
static GCKernelLibrary & get()
Get the static instance of GCKernelLibrary.
GCKernel create_kernel(const std::string &shader_name, const StringSet &build_options_set={}) const
Creates a kernel from the kernel library.
Describe a multidimensional execution window.
Definition: Window.h:39

References ARM_COMPUTE_ERROR_ON, ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN, ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES, arm_compute::calculate_max_enlarged_window(), arm_compute::ceil_to_multiple(), GCKernelLibrary::create_kernel(), ITensorInfo::data_type(), ITensorInfo::dimension(), arm_compute::F16, arm_compute::F32, GCKernelLibrary::get(), ITensor::info(), ITensorInfo::num_dimensions(), arm_compute::support::cpp11::to_string(), and arm_compute::update_window_and_padding().

Referenced by GCFullyConnectedLayer::configure().

◆ operator=() [1/2]

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)
overridevirtual

Enqueue the OpenGL ES shader to process the given window.

Parameters
[in]windowRegion on which to execute the kernel. (Must be a valid region of the window returned by window()).

Implements IGCKernel.

Definition at line 103 of file GCGEMMMatrixAccumulateBiasesKernel.cpp.

104 {
107 
108  _kernel.use();
109 
110  Window accum_slice = window.first_slice_window_2D();
111 
112  Window biases_slice(accum_slice);
113  biases_slice.set(Window::DimY, Window::Dimension(0, 1, 1));
114 
115  // Run kernel
116  do
117  {
118  // Set arguments
119  unsigned int idx = 0;
120 
121  add_2D_tensor_argument(idx, _accum, 1, accum_slice);
122  add_1D_tensor_argument(idx, _biases, 2, biases_slice);
123  _kernel.update_shader_params();
124 
125  enqueue(*this, accum_slice, _lws);
126  }
127  while(window.slide_window_slice_2D(accum_slice));
128 }
Window first_slice_window_2D() const
First 2D slice of the window.
Definition: Window.h:267
const Window & window() const
The maximum window the kernel can be executed on.
Definition: IKernel.cpp:28
void enqueue(cl::CommandQueue &queue, ICLKernel &kernel, const Window &window, const cl::NDRange &lws_hint=CLKernelLibrary::get().default_ndrange(), bool use_dummy_work_items=false)
Add the kernel to the command queue with the given window.
Definition: ICLKernel.cpp:39
Describe one of the image's dimensions with a start, end and step.
Definition: Window.h:75
bool slide_window_slice_2D(Window &slice) const
Slide the passed 2D window slice.
Definition: Window.h:307
#define ARM_COMPUTE_ERROR_ON_MISMATCHING_WINDOWS(f, w)
Definition: Validate.h:183
void add_2D_tensor_argument(unsigned int &idx, const IGCTensor *tensor, const unsigned int binding_point, const Window &window)
Add the passed 2D tensor's parameters to the object's kernel's arguments starting from the index idx.
Definition: IGCKernel.cpp:127
static constexpr size_t DimY
Alias for dimension 1 also known as Y dimension.
Definition: Window.h:45
Describe a multidimensional execution window.
Definition: Window.h:39
#define ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(k)
Definition: Validate.h:940
void add_1D_tensor_argument(unsigned int &idx, const IGCTensor *tensor, const unsigned int binding_point, const Window &window)
Add the passed 1D tensor's parameters to the object's kernel's arguments starting from the index idx.
Definition: IGCKernel.cpp:122

References IGCKernel::add_1D_tensor_argument(), IGCKernel::add_2D_tensor_argument(), ARM_COMPUTE_ERROR_ON_MISMATCHING_WINDOWS, ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL, Window::DimY, arm_compute::enqueue(), Window::first_slice_window_2D(), Window::set(), Window::slide_window_slice_2D(), and IKernel::window().


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