Compute Library
 22.11
CLPadLayerKernel Class Reference

Interface for the PadLayer function. More...

#include <CLPadLayerKernel.h>

Collaboration diagram for CLPadLayerKernel:
[legend]

Public Member Functions

 CLPadLayerKernel ()
 Default constructor. More...
 
 CLPadLayerKernel (const CLPadLayerKernel &)=delete
 Prevent instances of this class from being copied (As this class contains pointers) More...
 
CLPadLayerKerneloperator= (const CLPadLayerKernel &)=delete
 Prevent instances of this class from being copied (As this class contains pointers) More...
 
 CLPadLayerKernel (CLPadLayerKernel &&)=default
 Allow instances of this class to be moved. More...
 
CLPadLayerKerneloperator= (CLPadLayerKernel &&)=default
 Allow instances of this class to be moved. More...
 
 ~CLPadLayerKernel ()=default
 Default destructor. More...
 
void configure (const ICLTensor *input, ICLTensor *output, const PaddingList &padding, PixelValue constant_value=PixelValue(), PaddingMode mode=PaddingMode::CONSTANT)
 Set the input and output tensor. More...
 
void configure (const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const PaddingList &padding, PixelValue constant_value=PixelValue(), PaddingMode mode=PaddingMode::CONSTANT)
 Set the input and output tensor. 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...
 
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 *output, const PaddingList &padding, PixelValue constant_value=PixelValue(), PaddingMode mode=PaddingMode::CONSTANT)
 Static function to check if given info will lead to a valid configuration of CLPadLayerKernel. 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 PadLayer function.

Definition at line 34 of file CLPadLayerKernel.h.

Constructor & Destructor Documentation

◆ CLPadLayerKernel() [1/3]

Default constructor.

Definition at line 67 of file CLPadLayerKernel.cpp.

References arm_compute::ELEMENTWISE.

68  : _input(nullptr), _output(nullptr), _4d_enabled(false)
69 {
71 }
Elementwise CL kernel type.
Definition: CLTypes.h:85

◆ CLPadLayerKernel() [2/3]

CLPadLayerKernel ( const CLPadLayerKernel )
delete

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

◆ CLPadLayerKernel() [3/3]

Allow instances of this class to be moved.

◆ ~CLPadLayerKernel()

~CLPadLayerKernel ( )
default

Default destructor.

Member Function Documentation

◆ configure() [1/2]

void configure ( const ICLTensor input,
ICLTensor output,
const PaddingList padding,
PixelValue  constant_value = PixelValue(),
PaddingMode  mode = PaddingMode::CONSTANT 
)

Set the input and output tensor.

Parameters
[in]inputSource tensor. Data types supported: All.
[out]outputOutput tensor. Data type supported: same as input
[in]paddingThe padding for each spatial dimension of the input tensor. The pair padding[i] specifies the front and the end padding in the i-th dimension.
[in]constant_value(Optional) Constant value to be used for the padding.
[in]mode(Optional) Controls whether the padding should be filled with constant_value using CONSTANT, or reflect the input, either including the border values (SYMMETRIC) or not (REFLECT).

Definition at line 73 of file CLPadLayerKernel.cpp.

References CLKernelLibrary::get().

74 {
75  configure(CLKernelLibrary::get().get_compile_context(), input, output, padding, constant_value, mode);
76 }
static CLKernelLibrary & get()
Access the KernelLibrary singleton.
void configure(const ICLTensor *input, ICLTensor *output, const PaddingList &padding, PixelValue constant_value=PixelValue(), PaddingMode mode=PaddingMode::CONSTANT)
Set the input and output tensor.

◆ configure() [2/2]

void configure ( const CLCompileContext compile_context,
const ICLTensor input,
ICLTensor output,
const PaddingList padding,
PixelValue  constant_value = PixelValue(),
PaddingMode  mode = PaddingMode::CONSTANT 
)

Set the input and output tensor.

Parameters
[in]compile_contextThe compile context to be used.
[in]inputSource tensor. Data types supported: All.
[out]outputOutput tensor. Data type supported: same as input
[in]paddingThe padding for each spatial dimension of the input tensor. The pair padding[i] specifies the front and the end padding in the i-th dimension.
[in]constant_value(Optional) Constant value to be used for the padding.
[in]mode(Optional) Controls whether the padding should be filled with constant_value using CONSTANT, or reflect the input, either including the border values (SYMMETRIC) or not (REFLECT).

Definition at line 78 of file CLPadLayerKernel.cpp.

References CLBuildOptions::add_option(), arm_compute::adjust_vec_size(), ARM_COMPUTE_ERROR, 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::ceil_to_multiple(), ICloneable< T >::clone(), arm_compute::misc::shape_calculator::compute_padded_shape(), arm_compute::CONSTANT, arm_compute::create_kernel(), arm_compute::test::validation::data_type, ITensorInfo::data_type(), ITensorInfo::dimension(), arm_compute::element_size_from_data_type(), arm_compute::get_cl_type_from_data_type(), arm_compute::get_padding_info(), arm_compute::has_padding_changed(), ITensor::info(), arm_compute::test::validation::input, input_depth, input_height, input_width, kernel_name, clang_tidy_rules::mode, arm_compute::REFLECT, arm_compute::string_from_pixel_value(), arm_compute::SYMMETRIC, ITensorInfo::tensor_shape(), arm_compute::support::cpp11::to_string(), arm_compute::U, and arm_compute::cpu::kernels::validate_arguments().

79 {
81  auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(misc::shape_calculator::compute_padded_shape(input->info()->tensor_shape(), padding)));
82  ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), padding, constant_value, mode));
83 
84  auto padding_info = get_padding_info({ input, output });
85 
86  _input = input;
87  _output = output;
88  _4d_enabled = (mode == PaddingMode::CONSTANT) && (padding.size() > 3);
89 
90  // Set build options
91  const DataType &data_type = input->info()->data_type();
92  const unsigned int input_width = input->info()->dimension(0);
93  const unsigned int input_height = input->info()->dimension(1);
94  const unsigned int input_depth = input->info()->dimension(2);
95  const unsigned int pad_x_before = padding.at(0).first;
96  const unsigned int pad_y_before = padding.size() > 1 ? padding.at(1).first : 0;
97  const unsigned int pad_z_before = padding.size() > 2 ? padding.at(2).first : 0;
98  const unsigned int vec_size = adjust_vec_size(std::min(16U, 32U / static_cast<unsigned int>(element_size_from_data_type(input->info()->data_type()))), input_width);
99  const unsigned int pad_right_start = input_width + pad_x_before;
100  const unsigned int pad_x_before_remainder = pad_x_before % vec_size;
101  const unsigned int vec_size_leftover_write = vec_size - (ceil_to_multiple(output->info()->dimension(0), vec_size) - output->info()->dimension(0));
102 
103  CLBuildOptions build_opts;
104  build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(data_type));
105  build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(vec_size));
106  build_opts.add_option("-DPAD_X_BEFORE=" + support::cpp11::to_string(pad_x_before));
107  build_opts.add_option("-DSRC_WIDTH=" + support::cpp11::to_string(input_width));
108  build_opts.add_option("-DPAD_X_BEFORE_REMAINDER=" + support::cpp11::to_string(pad_x_before_remainder));
109  build_opts.add_option("-DVEC_SIZE_LEFTOVER_WRITE=" + support::cpp11::to_string(vec_size_leftover_write));
110  if(padding.size() > 1)
111  {
112  build_opts.add_option("-DPAD_Y_BEFORE=" + support::cpp11::to_string(pad_y_before));
113  build_opts.add_option("-DSRC_HEIGHT=" + support::cpp11::to_string(input_height));
114 
115  if(padding.size() > 2)
116  {
117  build_opts.add_option("-DPAD_Z_BEFORE=" + support::cpp11::to_string(pad_z_before));
118  build_opts.add_option("-DSRC_DEPTH=" + support::cpp11::to_string(input_depth));
119  }
120  }
121 
122  std::string kernel_name = "pad_layer_";
123  switch(mode)
124  {
126  {
127  kernel_name += "constant";
128 
129  const unsigned int vec_size_leftover_read = vec_size - (ceil_to_multiple(pad_right_start, vec_size) - pad_right_start);
130 
131  build_opts.add_option("-DCONST_VAL=" + string_from_pixel_value(constant_value, data_type));
132  build_opts.add_option("-DVEC_SIZE_LEFTOVER_READ=" + support::cpp11::to_string(vec_size_leftover_read));
133 
134  if(pad_x_before >= vec_size)
135  {
136  build_opts.add_option("-DTHREADS_TO_SKIP_BEFORE=" + support::cpp11::to_string(pad_x_before / vec_size));
137  build_opts.add_option("-DTHREADS_TO_SKIP_AFTER=" + support::cpp11::to_string(pad_right_start / vec_size));
138  }
139  if(_4d_enabled)
140  {
141  build_opts.add_option("-DPAD_W_BEFORE=" + support::cpp11::to_string(padding.at(3).first));
142  build_opts.add_option("-DSRC_BATCH=" + support::cpp11::to_string(input->info()->dimension(3)));
143  }
144 
145  break;
146  }
149  {
150  kernel_name += "symmetric_reflect";
151 
152  const auto is_reflect = static_cast<unsigned int>(mode == PaddingMode::REFLECT);
153 
154  const unsigned int pad_x_after_remainder = pad_right_start % vec_size;
155  const unsigned int after_pad_fact_x = (2 * input_width + pad_x_before) - is_reflect;
156  const unsigned int output_last_x = ceil_to_multiple(pad_right_start + padding.at(0).second, vec_size);
157 
158  build_opts.add_option("-DIS_REFLECT=" + support::cpp11::to_string(is_reflect));
159  build_opts.add_option("-DPAD_X_AFTER_REMAINDER=" + support::cpp11::to_string(pad_x_after_remainder));
160  build_opts.add_option("-DPAD_X_BEFORE_REMAINDER_REFL=" + support::cpp11::to_string((pad_x_before_remainder + is_reflect) % vec_size));
161  build_opts.add_option("-DPAD_X_AFTER_REMAINDER_REFL=" + support::cpp11::to_string((pad_x_after_remainder - is_reflect) % vec_size));
162  build_opts.add_option("-DAFTER_PAD_FACT_X=" + support::cpp11::to_string(after_pad_fact_x));
163  build_opts.add_option_if(after_pad_fact_x < output_last_x, "-DAFTER_PAD_REM=" + support::cpp11::to_string(after_pad_fact_x % vec_size));
164 
165  break;
166  }
167  default:
168  ARM_COMPUTE_ERROR("Padding mode not supported.");
169  }
170 
171  // Create kernel
172  _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
173 
174  // Configure window
175  Window win = calculate_max_window(*output->info(), Steps(vec_size));
176  ICLKernel::configure_internal(win);
177 
179 }
Window calculate_max_window(const ValidRegion &valid_region, const Steps &steps, bool skip_border, BorderSize border_size)
#define ARM_COMPUTE_ERROR(msg)
Print the given message then throw an std::runtime_error.
Definition: Error.h:352
std::string to_string(T &&value)
Convert integer and float values to string.
size_t element_size_from_data_type(DataType dt)
The size in bytes of the data type.
Definition: Utils.h:185
std::string string_from_pixel_value(const PixelValue &value, const DataType data_type)
Convert a PixelValue to a string, represented through the specific data type.
Definition: Utils.cpp:275
#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
const size_t input_height
Definition: impl.cpp:61
#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)
const size_t input_width
Definition: impl.cpp:62
const size_t input_depth
Definition: impl.cpp:63
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
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:71
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...
TensorShape compute_padded_shape(const TensorShape &input_shape, const PaddingList &padding)
Calculate the padded shape of a tensor.
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
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
unsigned int adjust_vec_size(unsigned int vec_size, size_t dim0)
Returns the adjusted vector size in case it is less than the input&#39;s first dimension, getting rounded down to its closest valid vector size.
Definition: Utils.h:1222
std::string kernel_name
DataType
Available data types.
Definition: Types.h:79

◆ operator=() [1/2]

CLPadLayerKernel& operator= ( const CLPadLayerKernel )
delete

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

◆ operator=() [2/2]

CLPadLayerKernel& operator= ( CLPadLayerKernel &&  )
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 187 of file CLPadLayerKernel.cpp.

References ICLKernel::add_3D_tensor_argument(), ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW, ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL, arm_compute::test::validation::batch, 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().

188 {
191 
193  unsigned int batch = 0;
194  do
195  {
196  unsigned int idx = 0;
197  add_3D_tensor_argument(idx, _input, slice);
198  add_3D_tensor_argument(idx, _output, slice);
199  if(_4d_enabled)
200  {
201  add_argument<unsigned int>(idx, batch++);
202  }
203 
204  enqueue(queue, *this, slice, lws_hint());
205  }
206  while(window.slide_window_slice_3D(slice));
207 }
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: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
bool slide_window_slice_3D(Window &slice) const
Slide the passed 3D window slice.
Definition: Window.h:349
#define ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(k)
Definition: Validate.h:915
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)

◆ validate()

Status validate ( const ITensorInfo input,
const ITensorInfo output,
const PaddingList padding,
PixelValue  constant_value = PixelValue(),
PaddingMode  mode = PaddingMode::CONSTANT 
)
static

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

Parameters
[in]inputSource tensor info. Data types supported: All.
[in]outputOutput tensor info. Data type supported: same as input
[in]paddingThe padding for each spatial dimension of the input tensor. The pair padding[i] specifies the front and the end padding in the i-th dimension.
[in]constant_value(Optional) Constant value to be used for the padding.
[in]mode(Optional) Controls whether the padding should be filled with constant_value using CONSTANT, or reflect the input, either including the border values (SYMMETRIC) or not (REFLECT).

Definition at line 181 of file CLPadLayerKernel.cpp.

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

Referenced by CLPadLayer::validate(), and CLGenerateProposalsLayer::validate().

182 {
183  ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, padding, constant_value, mode));
184  return Status{};
185 }
#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: