Compute Library
 21.02
CLWeightsReshapeKernel Class Reference

OpenCL kernel to perform reshaping on the weights used by convolution and locally connected layer. More...

#include <CLWeightsReshapeKernel.h>

Collaboration diagram for CLWeightsReshapeKernel:
[legend]

Public Member Functions

 CLWeightsReshapeKernel ()
 Constructor. More...
 
 CLWeightsReshapeKernel (const CLWeightsReshapeKernel &)=delete
 Prevent instances of this class from being copied (As this class contains pointers) More...
 
CLWeightsReshapeKerneloperator= (const CLWeightsReshapeKernel &)=delete
 Prevent instances of this class from being copied (As this class contains pointers) More...
 
 CLWeightsReshapeKernel (CLWeightsReshapeKernel &&)=default
 Allow instances of this class to be moved. More...
 
CLWeightsReshapeKerneloperator= (CLWeightsReshapeKernel &&)=default
 Allow instances of this class to be moved. More...
 
 ~CLWeightsReshapeKernel ()=default
 Default destructor. More...
 
void configure (const ICLTensor *input, const ICLTensor *biases, ICLTensor *output, unsigned int num_groups=1)
 Set the input and output of the kernel. More...
 
void configure (const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *biases, ICLTensor *output, unsigned int num_groups=1)
 Set the input and output of the kernel. 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 *biases, const ITensorInfo *output, unsigned int num_groups=1)
 Static function to check if given info will lead to a valid configuration of CLWeightsReshapeKernel. 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

OpenCL kernel to perform reshaping on the weights used by convolution and locally connected layer.

Rearranges each 3-dimensional kernel to a single row leading to a matrix with linearized kernels. In combination with the CLIm2ColKernel can transform a convolution to a matrix multiplication.

For example assuming a 3D weight kernel of 3x3 dimensions and depth of 2 we have:

\[ \left( \begin{array}{ccc} a000 & a001 & a002 \\ a010 & a011 & a012 \\ a020 & a021 & a022 \\ \end{array} \right) \left( \begin{array}{ccc} a100 & a101 & a102 \\ a110 & a111 & a112 \\ a120 & a121 & a122 \\ \end{array} \right) \rightarrow \left( \begin{array}{ccccccccc} a000 & a001 & a002 & a010 & a011 & a012 & a020 & a021 & a022 & a100 & a101 & a102 & a110 & a111 & a112 & a120 & a121 & a122 \\ \end{array} \right) \]

Definition at line 54 of file CLWeightsReshapeKernel.h.

Constructor & Destructor Documentation

◆ CLWeightsReshapeKernel() [1/3]

Constructor.

Definition at line 69 of file CLWeightsReshapeKernel.cpp.

70  : _input(nullptr), _biases(nullptr), _output(nullptr)
71 {
72 }

◆ CLWeightsReshapeKernel() [2/3]

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

◆ CLWeightsReshapeKernel() [3/3]

Allow instances of this class to be moved.

◆ ~CLWeightsReshapeKernel()

~CLWeightsReshapeKernel ( )
default

Default destructor.

Member Function Documentation

◆ configure() [1/2]

void configure ( const ICLTensor input,
const ICLTensor biases,
ICLTensor output,
unsigned int  num_groups = 1 
)

Set the input and output of the kernel.

Parameters
[in]inputThe input tensor to convert. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM] if shared, and 5D tensor with dimensions [kernel_x, kernel_y, IFM, OFM, num_patches] if unshared. Data types supported: All
[in]biasesThe shared biases tensor to append. Bias is 1D tensor with dimensions [OFM] if shared and 2D tensor with dimensions [OFM, num_patches] if unshared. Data types supported: F16/F32, for quantized types this must be nullptr.
Warning
Appending biases to weights reshaped matrix is not supported for quantized asymmetric types.
Parameters
[out]outputThe output tensor. Should be a 2D Tensor if there are no groups and the weights are not shared; a 3D Tensor otherwise. Data types supported: Same as input
[in]num_groups(Optional) Number of groups when performing a grouped convolution. num_groups != 1 is only supported for NCHW data layout Number of groups greater than one are only supported for NCHW data layout, and the number of weights must be a multiple of it.

Definition at line 74 of file CLWeightsReshapeKernel.cpp.

References CLKernelLibrary::get().

75 {
76  configure(CLKernelLibrary::get().get_compile_context(), input, biases, output, num_groups);
77 }
static CLKernelLibrary & get()
Access the KernelLibrary singleton.
void configure(const ICLTensor *input, const ICLTensor *biases, ICLTensor *output, unsigned int num_groups=1)
Set the input and output of the kernel.
const unsigned int num_groups
Definition: Im2Col.cpp:153

◆ configure() [2/2]

void configure ( const CLCompileContext compile_context,
const ICLTensor input,
const ICLTensor biases,
ICLTensor output,
unsigned int  num_groups = 1 
)

Set the input and output of the kernel.

Parameters
[in]compile_contextThe compile context to be used.
[in]inputThe input tensor to convert. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM] if shared, and 5D tensor with dimensions [kernel_x, kernel_y, IFM, OFM, num_patches] if unshared. Data types supported: All
[in]biasesThe shared biases tensor to append. Bias is 1D tensor with dimensions [OFM] if shared and 2D tensor with dimensions [OFM, num_patches] if unshared. Data types supported: F16/F32, for quantized types this must be nullptr.
Warning
Appending biases to weights reshaped matrix is not supported for quantized asymmetric types.
Parameters
[out]outputThe output tensor. Should be a 2D Tensor if there are no groups and the weights are not shared; a 3D Tensor otherwise. Data types supported: Same as input
[in]num_groups(Optional) Number of groups when performing a grouped convolution. num_groups != 1 is only supported for NCHW data layout Number of groups greater than one are only supported for NCHW data layout, and the number of weights must be a multiple of it.

Definition at line 79 of file CLWeightsReshapeKernel.cpp.

References CLBuildOptions::add_option(), CLBuildOptions::add_option_if(), 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_weights_reshaped_shape(), arm_compute::create_kernel(), arm_compute::data_size_from_type(), arm_compute::test::validation::data_type, ITensorInfo::data_type(), 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, arm_compute::test::validation::num_groups, CLBuildOptions::options(), ITensorInfo::set_valid_region(), ITensorInfo::tensor_shape(), arm_compute::support::cpp11::to_string(), and arm_compute::validate_arguments().

80 {
82 
83  // Output tensor auto inizialitation if not yet initialized
84  auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(compute_weights_reshaped_shape(*input->info(), (biases != nullptr), num_groups)));
85 
86  // Perform validation step
88  (biases != nullptr) ? biases->info() : nullptr,
89  output->info(), num_groups));
90 
91  auto padding_info = get_padding_info({ input, biases, output });
92 
93  const DataType data_type = input->info()->data_type();
94 
95  _biases = biases;
96  _output = output;
97  _input = input;
98 
99  // Create build options
100  CLBuildOptions build_opts;
101  build_opts.add_option("-DDATA_TYPE=" + get_cl_unsigned_type_from_element_size(data_size_from_type(data_type)));
102  build_opts.add_option("-DNUM_GROUPS=" + support::cpp11::to_string(num_groups));
103  build_opts.add_option_if(biases != nullptr, "-DHAS_BIAS");
104 
105  // Create kernel
106  _kernel = create_kernel(compile_context, "reshape_to_columns", build_opts.options());
107 
108  // Configure window
109  Window win = calculate_max_window(*input->info(), Steps());
110  // The CLWeightsReshapeKernel doesn't need padding so update_window_and_padding() can be skipped
111  output->info()->set_valid_region(ValidRegion(Coordinates(), output->info()->tensor_shape()));
112  ICLKernel::configure_internal(win);
113 
115 }
Window calculate_max_window(const ValidRegion &valid_region, const Steps &steps, bool skip_border, BorderSize border_size)
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
const DataType data_type
Definition: Im2Col.cpp:150
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 unsigned int num_groups
Definition: Im2Col.cpp:153
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...
size_t data_size_from_type(DataType data_type)
The size in bytes of the data type.
Definition: Utils.h:106
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
TensorShape compute_weights_reshaped_shape(const ITensorInfo &weights, bool has_bias=false, unsigned int num_groups=1)
Calculate the reshaped shape of the weights.
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
DataType
Available data types.
Definition: Types.h:77

◆ operator=() [1/2]

CLWeightsReshapeKernel& operator= ( const CLWeightsReshapeKernel )
delete

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

◆ operator=() [2/2]

CLWeightsReshapeKernel& operator= ( CLWeightsReshapeKernel &&  )
default

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 123 of file CLWeightsReshapeKernel.cpp.

References ICLKernel::add_1D_tensor_argument(), ICLKernel::add_2D_tensor_argument(), ICLKernel::add_3D_tensor_argument(), ARM_COMPUTE_ERROR_ON_MISMATCHING_WINDOWS, ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL, ARM_COMPUTE_UNUSED, ITensorInfo::dimension(), arm_compute::enqueue(), Window::first_slice_window_1D(), Window::first_slice_window_2D(), Window::first_slice_window_3D(), ITensor::info(), ICLKernel::lws_hint(), ICLKernel::num_arguments_per_1D_tensor(), ICLKernel::num_arguments_per_2D_tensor(), ICLKernel::num_arguments_per_3D_tensor(), Window::slide_window_slice_1D(), Window::slide_window_slice_2D(), Window::slide_window_slice_4D(), ITensorInfo::strides_in_bytes(), ITensorInfo::tensor_shape(), Window::use_tensor_dimensions(), IKernel::window(), and Dimensions< T >::z().

124 {
127 
128  Window out_window;
129  out_window.use_tensor_dimensions(_output->info()->tensor_shape());
130 
131  Window in_slice = window.first_slice_window_3D();
132  Window out_slice = out_window.first_slice_window_2D();
133 
134  Window biases_window;
135  Window biases_slice;
136 
138  idx += (_biases != nullptr) ? num_arguments_per_1D_tensor() : 0;
139  _kernel.setArg<cl_uint>(idx++, _input->info()->dimension(0));
140  _kernel.setArg<cl_uint>(idx++, _input->info()->dimension(1));
141  _kernel.setArg<cl_uint>(idx++, _input->info()->dimension(2));
142  _kernel.setArg<cl_uint>(idx++, _input->info()->dimension(3));
143  _kernel.setArg<cl_uint>(idx++, _output->info()->strides_in_bytes().z());
144 
145  if(_biases != nullptr)
146  {
147  biases_window.use_tensor_dimensions(_biases->info()->tensor_shape());
148  biases_slice = biases_window.first_slice_window_1D();
149  }
150 
151  do
152  {
153  // Set arguments
154  unsigned idx = 0;
155  add_3D_tensor_argument(idx, _input, in_slice);
156  add_2D_tensor_argument(idx, _output, out_slice);
157  if(_biases != nullptr)
158  {
159  add_1D_tensor_argument(idx, _biases, biases_slice);
160  ARM_COMPUTE_UNUSED(biases_window.slide_window_slice_1D(biases_slice));
161  }
162 
163  // Run kernel
164  enqueue(queue, *this, in_slice, lws_hint());
165  }
166  while(window.slide_window_slice_4D(in_slice) && out_window.slide_window_slice_2D(out_slice));
167 }
static constexpr unsigned int num_arguments_per_1D_tensor()
Returns the number of arguments enqueued per 1D tensor object.
Definition: ICLKernel.h:198
Window first_slice_window_2D() const
First 2D slice of the window.
Definition: Window.h:283
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
virtual size_t dimension(size_t index) const =0
Return the size of the requested dimension.
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
static constexpr unsigned int num_arguments_per_3D_tensor()
Returns the number of arguments enqueued per 3D tensor object.
Definition: ICLKernel.h:214
#define ARM_COMPUTE_UNUSED(...)
To avoid unused variables warnings.
Definition: Error.h:152
#define ARM_COMPUTE_ERROR_ON_MISMATCHING_WINDOWS(f, w)
Definition: Validate.h:183
virtual const TensorShape & tensor_shape() const =0
Size for each dimension of the tensor.
T z() const
Alias to access the size of the third dimension.
Definition: Dimensions.h:97
virtual ITensorInfo * info() const =0
Interface to be implemented by the child class to return the tensor&#39;s metadata.
static constexpr unsigned int num_arguments_per_2D_tensor()
Returns the number of arguments enqueued per 2D tensor object.
Definition: ICLKernel.h:206
#define ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(k)
Definition: Validate.h:941
void add_2D_tensor_argument(unsigned int &idx, const ICLTensor *tensor, const Window &window)
Add the passed 2D tensor&#39;s parameters to the object&#39;s kernel&#39;s arguments starting from the index idx...
Definition: ICLKernel.h:148
bool slide_window_slice_4D(Window &slice) const
Slide the passed 4D window slice.
Definition: Window.h:347
virtual const Strides & strides_in_bytes() const =0
The strides in bytes for accessing each dimension of the tensor.
void add_1D_tensor_argument(unsigned int &idx, const ICLTensor *tensor, const Window &window)
Add the passed 1D tensor&#39;s parameters to the object&#39;s kernel&#39;s arguments starting from the index idx...
Definition: ICLKernel.h:124
Window first_slice_window_3D() const
First 3D slice of the window.
Definition: Window.h:291

◆ validate()

Status validate ( const ITensorInfo input,
const ITensorInfo biases,
const ITensorInfo output,
unsigned int  num_groups = 1 
)
static

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

Parameters
[in]inputThe input tensor to convert. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM] if shared, and 5D tensor with dimensions [kernel_x, kernel_y, IFM, OFM, num_patches] if unshared. Data types supported: All
[in]biasesThe shared biases tensor to append. Bias is 1D tensor with dimensions [OFM] if shared and 2D tensor with dimensions [OFM, num_patches] if unshared. Data types supported: F16/F32, for quantized types this must be nullptr.
Warning
Appending biases to weights reshaped matrix is not supported for quantized asymmetric types.
Parameters
[in]outputThe output tensor. Should be a 2D Tensor if there are no groups and the weights are not shared; a 3D Tensor otherwise. Data types supported: Same as input
[in]num_groups(Optional) Number of groups when performing a grouped convolution. num_groups != 1 is only supported for NCHW data layout Number of groups greater than one are only supported for NCHW data layout, and the number of weights must be a multiple of it.
Returns
a status

Definition at line 117 of file CLWeightsReshapeKernel.cpp.

References ARM_COMPUTE_RETURN_ON_ERROR, and arm_compute::validate_arguments().

Referenced by CLConvolutionLayerReshapeWeights::validate().

118 {
120  return Status{};
121 }
#define ARM_COMPUTE_RETURN_ON_ERROR(status)
Checks if a status contains an error and returns it.
Definition: Error.h:204
const unsigned int num_groups
Definition: Im2Col.cpp:153
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: