Compute Library
 22.05
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 ()
 
 ARM_COMPUTE_DISALLOW_COPY_ALLOW_MOVE (ClWeightsReshapeKernel)
 
void configure (const ClCompileContext &compile_context, const ITensorInfo *src, const ITensorInfo *biases, ITensorInfo *dst, unsigned int num_groups=1)
 Set the input and output of the kernel. More...
 
void run_op (ITensorPack &tensors, 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...
 
CLKernelType type () const
 Returns the CL kernel type. 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...
 
void add_5D_tensor_argument (unsigned int &idx, const ICLTensor *tensor, const Window &window)
 Add the passed 5D tensor's parameters to the object's kernel's arguments starting from the index idx. More...
 
void add_3d_tensor_nhw_argument (unsigned int &idx, const ICLTensor *tensor)
 Add the passed NHW 3D tensor's parameters to the object's kernel's arguments by passing strides, dimensions and the offset to the first valid element in bytes. More...
 
void add_4d_tensor_nhwc_argument (unsigned int &idx, const ICLTensor *tensor)
 Add the passed NHWC 4D tensor's parameters to the object's kernel's arguments by passing strides, dimensions and the offset to the first valid element in bytes. More...
 
virtual void run (const Window &window, cl::CommandQueue &queue)
 Enqueue the OpenCL kernel to process the given window on the passed OpenCL command queue. More...
 
virtual void run_composite_op (ITensorPack &tensors, const Window &window, cl::CommandQueue &queue, const experimental::dynamic_fusion::ClExecutionDescriptor &exec_desc)
 The execution is carried out through run_op method. But the run_op method needs to be extended to include ClExecutionDescriptor as now LWS GWS tuning will be separated from the IKernel. 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...
 
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 *src, const ITensorInfo *biases, const ITensorInfo *dst, unsigned int num_groups=1)
 Static function to check if given info will lead to a valid configuration. More...
 
- Static Public Member Functions inherited from ICLKernel
static constexpr unsigned int num_arguments_per_3d_tensor_nhw ()
 Returns the number of arguments enqueued per NHW 3D Tensor object. More...
 
static constexpr unsigned int num_arguments_per_4d_tensor_nhwc ()
 Returns the number of arguments enqueued per NHWC 4D Tensor object. More...
 
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 opencl::kernels::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 60 of file ClWeightsReshapeKernel.h.

Constructor & Destructor Documentation

◆ ClWeightsReshapeKernel()

Definition at line 73 of file ClWeightsReshapeKernel.cpp.

References arm_compute::ELEMENTWISE.

74 {
76 }
Elementeise CL kernel type.
Definition: CLTypes.h:84

Member Function Documentation

◆ ARM_COMPUTE_DISALLOW_COPY_ALLOW_MOVE()

ARM_COMPUTE_DISALLOW_COPY_ALLOW_MOVE ( ClWeightsReshapeKernel  )

◆ configure()

void configure ( const ClCompileContext compile_context,
const ITensorInfo src,
const ITensorInfo biases,
ITensorInfo dst,
unsigned int  num_groups = 1 
)

Set the input and output of the kernel.

Parameters
[in]compile_contextThe compile context to be used.
[in]srcThe input tensor info 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 info 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]dstThe output tensor info. 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 78 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(), CLBuildOptions::options(), arm_compute::test::validation::src, arm_compute::support::cpp11::to_string(), and arm_compute::cpu::kernels::validate_arguments().

79 {
81 
82  // Output tensor auto inizialitation if not yet initialized
83  auto_init_if_empty(*dst, src->clone()->set_tensor_shape(compute_weights_reshaped_shape(*src, (biases != nullptr), num_groups)));
84 
85  // Perform validation step
87  auto padding_info = get_padding_info({ src, biases, dst });
88 
89  const DataType data_type = src->data_type();
90 
91  // Create build options
92  CLBuildOptions build_opts;
93  build_opts.add_option("-DDATA_TYPE=" + get_cl_unsigned_type_from_element_size(data_size_from_type(data_type)));
94  build_opts.add_option("-DNUM_GROUPS=" + support::cpp11::to_string(num_groups));
95  build_opts.add_option_if(biases != nullptr, "-DHAS_BIAS");
96 
97  // Create kernel
98  _kernel = create_kernel(compile_context, "reshape_to_columns", build_opts.options());
99 
100  // Configure window
101  Window win = calculate_max_window(*src, Steps());
102  ICLKernel::configure_internal(win);
103 
105 }
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
Status validate_arguments(const ITensorInfo *src, const ITensorInfo *weights, const ITensorInfo *dst, const PadStrideInfo &conv_info)
SimpleTensor< float > src
Definition: DFT.cpp:155
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:391
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:601
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:105
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:586
#define ARM_COMPUTE_ERROR_ON_NULLPTR(...)
Definition: Validate.h:157
DataType
Available data types.
Definition: Types.h:79

◆ run_op()

void run_op ( ITensorPack tensors,
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]tensorsA vector containing the tensors to operato on.
[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 113 of file ClWeightsReshapeKernel.cpp.

References arm_compute::ACL_BIAS, arm_compute::ACL_DST, arm_compute::ACL_SRC, ARM_COMPUTE_ERROR_ON_MISMATCHING_WINDOWS, ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL, ARM_COMPUTE_UNUSED, arm_compute::test::validation::dst, arm_compute::enqueue(), Window::first_slice_window_1D(), Window::first_slice_window_2D(), Window::first_slice_window_3D(), ITensorPack::get_const_tensor(), ITensorPack::get_tensor(), Window::slide_window_slice_1D(), Window::slide_window_slice_4D(), arm_compute::test::validation::src, Window::use_tensor_dimensions(), and IKernel::window().

114 {
117 
118  auto src = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC));
119  auto biases = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_BIAS));
120  auto dst = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_DST));
121 
122  Window out_window;
123  out_window.use_tensor_dimensions(dst->info()->tensor_shape());
124 
125  Window in_slice = window.first_slice_window_3D();
126  Window out_slice = out_window.first_slice_window_2D();
127 
128  Window biases_window;
129  Window biases_slice;
130 
132  idx += (biases != nullptr) ? num_arguments_per_1D_tensor() : 0;
133  _kernel.setArg<cl_uint>(idx++, src->info()->dimension(0));
134  _kernel.setArg<cl_uint>(idx++, src->info()->dimension(1));
135  _kernel.setArg<cl_uint>(idx++, src->info()->dimension(2));
136  _kernel.setArg<cl_uint>(idx++, src->info()->dimension(3));
137  _kernel.setArg<cl_uint>(idx++, dst->info()->strides_in_bytes().z());
138 
139  if(biases != nullptr)
140  {
141  biases_window.use_tensor_dimensions(biases->info()->tensor_shape());
142  biases_slice = biases_window.first_slice_window_1D();
143  }
144 
145  do
146  {
147  // Set arguments
148  unsigned idx = 0;
149  add_3D_tensor_argument(idx, src, in_slice);
150  add_2D_tensor_argument(idx, dst, out_slice);
151  if(biases != nullptr)
152  {
153  add_1D_tensor_argument(idx, biases, biases_slice);
154  ARM_COMPUTE_UNUSED(biases_window.slide_window_slice_1D(biases_slice));
155  }
156 
157  // Run kernel
158  enqueue(queue, *this, in_slice, lws_hint());
159  }
160  while(window.slide_window_slice_4D(in_slice) && out_window.slide_window_slice_2D(out_slice));
161 }
static constexpr unsigned int num_arguments_per_1D_tensor()
Returns the number of arguments enqueued per 1D tensor object.
Definition: ICLKernel.h:298
Window first_slice_window_2D() const
First 2D slice of the window.
Definition: Window.h:296
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:32
cl::NDRange lws_hint() const
Return the Local-Workgroup-Size hint.
Definition: ICLKernel.h:384
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:227
SimpleTensor< float > src
Definition: DFT.cpp:155
static constexpr unsigned int num_arguments_per_3D_tensor()
Returns the number of arguments enqueued per 3D tensor object.
Definition: ICLKernel.h:314
#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:179
static constexpr unsigned int num_arguments_per_2D_tensor()
Returns the number of arguments enqueued per 2D tensor object.
Definition: ICLKernel.h:306
#define ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(k)
Definition: Validate.h:915
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:203
bool slide_window_slice_4D(Window &slice) const
Slide the passed 4D window slice.
Definition: Window.h:360
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:179
Window first_slice_window_3D() const
First 3D slice of the window.
Definition: Window.h:304

◆ validate()

Status validate ( const ITensorInfo src,
const ITensorInfo biases,
const ITensorInfo dst,
unsigned int  num_groups = 1 
)
static

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

Similar to ClWeightsReshapeKernel::configure()

Returns
a status

Definition at line 107 of file ClWeightsReshapeKernel.cpp.

References ARM_COMPUTE_RETURN_ON_ERROR, and arm_compute::cpu::kernels::validate_arguments().

Referenced by arm_compute::test::validation::DATA_TEST_CASE().

108 {
110  return Status{};
111 }
#define ARM_COMPUTE_RETURN_ON_ERROR(status)
Checks if a status contains an error and returns it.
Definition: Error.h:204
Status validate_arguments(const ITensorInfo *src, const ITensorInfo *weights, const ITensorInfo *dst, const PadStrideInfo &conv_info)
SimpleTensor< float > src
Definition: DFT.cpp:155
const unsigned int num_groups
Definition: Im2Col.cpp:153

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