Compute Library
 22.11
CLROIAlignLayerKernel Class Reference

Interface for the RoIAlign kernel. More...

#include <CLROIAlignLayerKernel.h>

Collaboration diagram for CLROIAlignLayerKernel:
[legend]

Public Member Functions

 CLROIAlignLayerKernel ()
 Constructor. More...
 
 CLROIAlignLayerKernel (const CLROIAlignLayerKernel &)=delete
 Prevent instances of this class from being copied (As this class contains pointers) More...
 
CLROIAlignLayerKerneloperator= (const CLROIAlignLayerKernel &)=delete
 Prevent instances of this class from being copied (As this class contains pointers) More...
 
 CLROIAlignLayerKernel (CLROIAlignLayerKernel &&)=default
 Default Move Constructor. More...
 
CLROIAlignLayerKerneloperator= (CLROIAlignLayerKernel &&)=default
 Default move assignment operator. More...
 
 ~CLROIAlignLayerKernel ()=default
 Default destructor. More...
 
void configure (const ICLTensor *input, const ICLTensor *rois, ICLTensor *output, const ROIPoolingLayerInfo &pool_info)
 Set the input and output tensors. More...
 
void configure (const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *rois, ICLTensor *output, const ROIPoolingLayerInfo &pool_info)
 Set the input and output tensors. More...
 
void run (const Window &window, cl::CommandQueue &queue)
 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_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...
 
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 *input, const ITensorInfo *rois, ITensorInfo *output, const ROIPoolingLayerInfo &pool_info)
 Static function to check if given info will lead to a valid configuration of CLROIAlignLayerKernel. 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

Interface for the RoIAlign kernel.

Definition at line 34 of file CLROIAlignLayerKernel.h.

Constructor & Destructor Documentation

◆ CLROIAlignLayerKernel() [1/3]

Constructor.

Definition at line 79 of file CLROIAlignLayerKernel.cpp.

References arm_compute::ELEMENTWISE.

80  : _input(nullptr), _output(nullptr), _rois(nullptr), _pool_info(0, 0, 0.f)
81 {
83 }
Elementwise CL kernel type.
Definition: CLTypes.h:85

◆ CLROIAlignLayerKernel() [2/3]

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

◆ CLROIAlignLayerKernel() [3/3]

Default Move Constructor.

◆ ~CLROIAlignLayerKernel()

~CLROIAlignLayerKernel ( )
default

Default destructor.

Member Function Documentation

◆ configure() [1/2]

void configure ( const ICLTensor input,
const ICLTensor rois,
ICLTensor output,
const ROIPoolingLayerInfo pool_info 
)

Set the input and output tensors.

Parameters
[in]inputSource tensor. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
[in]roisROIs tensor, it is a 2D tensor of size [5, N] (where N is the number of ROIs) containing top left and bottom right corner as coordinate of an image and batch_id of ROI [ batch_id, x1, y1, x2, y2 ]. Data types supported: QASYMM16 with scale of 0.125 and 0 offset if input is QASYMM8/QASYMM8_SIGNED, otherwise same as input
[out]outputDestination tensor. Data types supported: Same as input.
[in]pool_infoContains pooling operation information described in ROIPoolingLayerInfo.
Note
The x and y dimensions of output tensor must be the same as pool_info 's pooled width and pooled height.
The z dimensions of output tensor and input tensor must be the same.
The fourth dimension of output tensor must be the same as the number of elements in rois array.

Definition at line 85 of file CLROIAlignLayerKernel.cpp.

References CLKernelLibrary::get().

86 {
87  configure(CLKernelLibrary::get().get_compile_context(), input, rois, output, pool_info);
88 }
static CLKernelLibrary & get()
Access the KernelLibrary singleton.
void configure(const ICLTensor *input, const ICLTensor *rois, ICLTensor *output, const ROIPoolingLayerInfo &pool_info)
Set the input and output tensors.

◆ configure() [2/2]

void configure ( const CLCompileContext compile_context,
const ICLTensor input,
const ICLTensor rois,
ICLTensor output,
const ROIPoolingLayerInfo pool_info 
)

Set the input and output tensors.

Parameters
[in]compile_contextThe compile context to be used.
[in]inputSource tensor. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
[in]roisROIs tensor, it is a 2D tensor of size [5, N] (where N is the number of ROIs) containing top left and bottom right corner as coordinate of an image and batch_id of ROI [ batch_id, x1, y1, x2, y2 ]. Data types supported: QASYMM16 with scale of 0.125 and 0 offset if input is QASYMM8/QASYMM8_SIGNED, otherwise same as input
[out]outputDestination tensor. Data types supported: Same as input.
[in]pool_infoContains pooling operation information described in ROIPoolingLayerInfo.
Note
The x and y dimensions of output tensor must be the same as pool_info 's pooled width and pooled height.
The z dimensions of output tensor and input tensor must be the same.
The fourth dimension of output tensor must be the same as the number of elements in rois array.

Definition at line 90 of file CLROIAlignLayerKernel.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(), arm_compute::CHANNEL, arm_compute::misc::shape_calculator::compute_roi_align_shape(), arm_compute::create_kernel(), ITensorInfo::data_layout(), arm_compute::test::validation::data_type, ITensorInfo::data_type(), arm_compute::float_to_string_with_full_precision(), arm_compute::get_cl_type_from_data_type(), arm_compute::get_data_layout_dimension_index(), arm_compute::get_data_size_from_data_type(), arm_compute::get_padding_info(), arm_compute::has_padding_changed(), arm_compute::HEIGHT, ITensor::info(), arm_compute::test::validation::input, arm_compute::is_data_type_quantized_asymmetric(), kernel_name, arm_compute::NHWC, UniformQuantizationInfo::offset, CLBuildOptions::options(), arm_compute::test::validation::output_shape, ROIPoolingLayerInfo::pooled_height(), ROIPoolingLayerInfo::pooled_width(), ITensorInfo::quantization_info(), ROIPoolingLayerInfo::sampling_ratio(), UniformQuantizationInfo::scale, ITensorInfo::set_data_layout(), ROIPoolingLayerInfo::spatial_scale(), arm_compute::support::cpp11::to_string(), QuantizationInfo::uniform(), arm_compute::cpu::kernels::validate_arguments(), and arm_compute::WIDTH.

91 {
92  ARM_COMPUTE_ERROR_ON_NULLPTR(input, output, rois);
93  ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), rois->info(), output->info(), pool_info));
94 
95  // Output auto inizialitation if not yet initialized
96  const TensorShape output_shape = compute_roi_align_shape(*input->info(), *rois->info(), pool_info);
97  auto_init_if_empty(*output->info(), output_shape, 1, input->info()->data_type());
98  output->info()->set_data_layout(input->info()->data_layout());
99 
100  auto padding_info = get_padding_info({ input, rois, output });
101 
102  _input = input;
103  _output = output;
104  _rois = rois;
105  _pool_info = pool_info;
106 
107  const DataType data_type = input->info()->data_type();
108  const bool is_qasymm = is_data_type_quantized_asymmetric(data_type);
109 
110  // Set build options
111  CLBuildOptions build_opts;
112  build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(data_type));
113  build_opts.add_option("-DDATA_SIZE=" + get_data_size_from_data_type(input->info()->data_type()));
114  build_opts.add_option("-DMAX_DIM_X=" + support::cpp11::to_string(_input->info()->dimension(get_data_layout_dimension_index(input->info()->data_layout(), DataLayoutDimension::WIDTH))));
115  build_opts.add_option("-DMAX_DIM_Y=" + support::cpp11::to_string(_input->info()->dimension(get_data_layout_dimension_index(input->info()->data_layout(), DataLayoutDimension::HEIGHT))));
116  build_opts.add_option("-DMAX_DIM_Z=" + support::cpp11::to_string(_input->info()->dimension(get_data_layout_dimension_index(input->info()->data_layout(), DataLayoutDimension::CHANNEL))));
117  build_opts.add_option("-DPOOLED_DIM_X=" + support::cpp11::to_string(pool_info.pooled_width()));
118  build_opts.add_option("-DPOOLED_DIM_Y=" + support::cpp11::to_string(pool_info.pooled_height()));
119  build_opts.add_option("-DSPATIAL_SCALE=" + float_to_string_with_full_precision(pool_info.spatial_scale()));
120  build_opts.add_option_if(input->info()->data_layout() == DataLayout::NHWC, "-DNHWC");
121  build_opts.add_option_if(pool_info.sampling_ratio() > 0, "-DSAMPLING_RATIO=" + support::cpp11::to_string(pool_info.sampling_ratio()));
122 
123  if(is_qasymm)
124  {
125  const UniformQuantizationInfo iq_info = input->info()->quantization_info().uniform();
126  const UniformQuantizationInfo roisq_info = rois->info()->quantization_info().uniform();
127  const UniformQuantizationInfo oq_info = output->info()->quantization_info().uniform();
128 
129  build_opts.add_option("-DOFFSET_IN=" + float_to_string_with_full_precision(iq_info.offset));
130  build_opts.add_option("-DSCALE_IN=" + float_to_string_with_full_precision(iq_info.scale));
131  build_opts.add_option("-DOFFSET_ROIS=" + float_to_string_with_full_precision(roisq_info.offset));
132  build_opts.add_option("-DSCALE_ROIS=" + float_to_string_with_full_precision(roisq_info.scale));
133  build_opts.add_option("-DOFFSET_OUT=" + float_to_string_with_full_precision(oq_info.offset));
134  build_opts.add_option("-DSCALE_OUT=" + float_to_string_with_full_precision(oq_info.scale));
135  }
136 
137  // Create kernel
138  const std::string kernel_name = (is_qasymm) ? "roi_align_layer_quantized" : "roi_align_layer";
139  _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
140 
141  // Configure kernel window
142  Window win = calculate_max_window(*output->info(), Steps());
143  ICLKernel::configure_internal(win);
145 }
Window calculate_max_window(const ValidRegion &valid_region, const Steps &steps, bool skip_border, BorderSize border_size)
TensorShape compute_roi_align_shape(const ITensorInfo &input, const ITensorInfo &rois, ROIPoolingLayerInfo pool_info)
Calculate the output roi align shape of a tensor.
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)
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:404
std::string get_data_size_from_data_type(const DataType &dt)
Get the size of a data type in number of bits.
Definition: CLHelpers.cpp:193
std::string float_to_string_with_full_precision(float val)
Create a string with the float in full precision.
Definition: Utils.h:1124
std::string get_cl_type_from_data_type(const DataType &dt)
Translates a tensor data type to the appropriate OpenCL type.
Definition: CLHelpers.cpp:39
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:603
bool is_data_type_quantized_asymmetric(DataType dt)
Check if a given data type is of asymmetric quantized type.
Definition: Utils.h:1052
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
Num samples, height, width, channels.
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:588
#define ARM_COMPUTE_ERROR_ON_NULLPTR(...)
Definition: Validate.h:157
std::string kernel_name
DataType
Available data types.
Definition: Types.h:79

◆ operator=() [1/2]

CLROIAlignLayerKernel& operator= ( const CLROIAlignLayerKernel )
delete

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

◆ operator=() [2/2]

CLROIAlignLayerKernel& operator= ( CLROIAlignLayerKernel &&  )
default

Default move assignment operator.

◆ run()

void run ( const Window window,
cl::CommandQueue &  queue 
)
virtual

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 153 of file CLROIAlignLayerKernel.cpp.

References ICLKernel::add_2D_tensor_argument(), ICLKernel::add_3D_tensor_argument(), ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW, ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL, arm_compute::CHANNEL, ITensorInfo::data_layout(), ITensorInfo::dimension(), Window::DimX, arm_compute::enqueue(), Window::first_slice_window_3D(), arm_compute::get_data_layout_dimension_index(), ITensor::info(), ICLKernel::lws_hint(), Window::set(), Window::set_dimension_step(), arm_compute::test::validation::reference::slice(), ITensorInfo::strides_in_bytes(), and IKernel::window().

154 {
157 
159  Window slice_rois = slice;
160  // Parallelize spatially and across the fourth dimension of the output tensor (also across ROITensor)
161  slice_rois.set_dimension_step(Window::DimX, _rois->info()->dimension(0));
163 
164  // Set arguments
165  unsigned int idx = 0;
166  add_3D_tensor_argument(idx, _input, slice);
167  add_2D_tensor_argument(idx, _rois, slice_rois);
168  add_3D_tensor_argument(idx, _output, slice);
169  add_argument<cl_uint>(idx, _input->info()->strides_in_bytes()[3]);
170  add_argument<cl_uint>(idx, _output->info()->strides_in_bytes()[3]);
171 
172  enqueue(queue, *this, slice, lws_hint());
173 }
const Window & window() const
The maximum window the kernel can be executed on.
Definition: IKernel.cpp:28
virtual size_t dimension(size_t index) const =0
Return the size of the requested dimension.
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:383
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:226
static constexpr size_t DimX
Alias for dimension 0 also known as X dimension.
Definition: Window.h:43
virtual ITensorInfo * info() const =0
Interface to be implemented by the child class to return the tensor&#39;s metadata.
#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:202
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
virtual const Strides & strides_in_bytes() const =0
The strides in bytes for accessing each dimension of the tensor.
Window first_slice_window_3D() const
First 3D slice of the window.
Definition: Window.h:305
#define ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(f, s)
Definition: Validate.h:201
SimpleTensor< T > slice(const SimpleTensor< T > &src, Coordinates starts, Coordinates ends)
virtual DataLayout data_layout() const =0
Get the data layout of the tensor.

◆ validate()

Status validate ( const ITensorInfo input,
const ITensorInfo rois,
ITensorInfo output,
const ROIPoolingLayerInfo pool_info 
)
static

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

Parameters
[in]inputSource tensor info. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
[in]roisROIs tensor info. Data types supported: QASYMM16 with scale of 0.125 and 0 offset if input is QASYMM8/QASYMM8_SIGNED, otherwise same as input
[in]outputDestination tensor info. Data types supported: Same as input.
[in]pool_infoContains pooling operation information described in ROIPoolingLayerInfo.
Note
The x and y dimensions of output tensor must be the same as pool_info 's pooled width and pooled height.
The z dimensions of output tensor and input tensor must be the same.
The fourth dimension of output tensor must be the same as the number of elements in rois array.
Returns
a Status

Definition at line 147 of file CLROIAlignLayerKernel.cpp.

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

Referenced by CLROIAlignLayer::validate().

148 {
149  ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, rois, output, pool_info));
150  return Status{};
151 }
#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)

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