Compute Library
 21.02
CLPixelWiseMultiplicationKernel Class Reference

Interface for the pixelwise multiplication kernel. More...

#include <CLPixelWiseMultiplicationKernel.h>

Collaboration diagram for CLPixelWiseMultiplicationKernel:
[legend]

Public Member Functions

 CLPixelWiseMultiplicationKernel ()
 Default constructor. More...
 
 CLPixelWiseMultiplicationKernel (const CLPixelWiseMultiplicationKernel &)=delete
 Prevent instances of this class from being copied (As this class contains pointers) More...
 
CLPixelWiseMultiplicationKerneloperator= (const CLPixelWiseMultiplicationKernel &)=delete
 Prevent instances of this class from being copied (As this class contains pointers) More...
 
 CLPixelWiseMultiplicationKernel (CLPixelWiseMultiplicationKernel &&)=default
 Allow instances of this class to be moved. More...
 
CLPixelWiseMultiplicationKerneloperator= (CLPixelWiseMultiplicationKernel &&)=default
 Allow instances of this class to be moved. More...
 
void configure (ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output, float scale, ConvertPolicy overflow_policy, RoundingPolicy rounding_policy, const ActivationLayerInfo &act_info=ActivationLayerInfo())
 Initialise the kernel's input, output and border mode. More...
 
void configure (const CLCompileContext &compile_context, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output, float scale, ConvertPolicy overflow_policy, RoundingPolicy rounding_policy, const ActivationLayerInfo &act_info=ActivationLayerInfo())
 Initialise the kernel's input, output and border mode. 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...
 
BorderSize border_size () const override
 The size of the border for that kernel. 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 (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...
 
const Windowwindow () const
 The maximum window the kernel can be executed on. More...
 

Static Public Member Functions

static Status validate (const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, float scale, ConvertPolicy overflow_policy, RoundingPolicy rounding_policy, const ActivationLayerInfo &act_info=ActivationLayerInfo())
 Static function to check if given info will lead to a valid configuration of CLPixelWiseMultiplicationKernel. 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

Interface for the pixelwise multiplication kernel.

Definition at line 36 of file CLPixelWiseMultiplicationKernel.h.

Constructor & Destructor Documentation

◆ CLPixelWiseMultiplicationKernel() [1/3]

Default constructor.

Definition at line 143 of file CLPixelWiseMultiplicationKernel.cpp.

144  : _input1(nullptr), _input2(nullptr), _output(nullptr)
145 {
146 }

◆ CLPixelWiseMultiplicationKernel() [2/3]

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

◆ CLPixelWiseMultiplicationKernel() [3/3]

Allow instances of this class to be moved.

Member Function Documentation

◆ border_size()

BorderSize border_size ( ) const
overridevirtual

The size of the border for that kernel.

Returns
The width in number of elements of the border.

Reimplemented from IKernel.

Definition at line 319 of file CLPixelWiseMultiplicationKernel.cpp.

References ARM_COMPUTE_CREATE_ERROR, ARM_COMPUTE_RETURN_ERROR_ON, ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN, ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES, ARM_COMPUTE_RETURN_ERROR_ON_MSG, arm_compute::auto_init_if_empty(), Window::broadcast_if_dimension_le_one(), TensorShape::broadcast_shape(), ITensorInfo::broadcast_shape_and_valid_region(), arm_compute::calculate_max_window(), ITensorInfo::data_type(), ITensorInfo::dimension(), ActivationLayerInfo::enabled(), arm_compute::F16, arm_compute::F32, arm_compute::detail::have_different_dimensions(), arm_compute::is_data_type_float(), ITensorInfo::num_channels(), arm_compute::RUNTIME_ERROR, AccessWindowRectangle::set_valid_region(), ITensorInfo::tensor_shape(), TensorShape::total_size(), ITensorInfo::total_size(), arm_compute::U, and arm_compute::update_window_and_padding().

320 {
321  const unsigned int replicateSize = _output->dimension(0) - std::min(_input1->dimension(0), _input2->dimension(0));
322  const unsigned int border = std::min<unsigned int>(num_elems_processed_per_iteration - 1U, replicateSize);
323  return BorderSize{ 0, border, 0, 0 };
324 }
virtual size_t dimension(size_t index) const =0
Return the size of the requested dimension.
unsigned int num_elems_processed_per_iteration

◆ configure() [1/2]

void configure ( ITensorInfo input1,
ITensorInfo input2,
ITensorInfo output,
float  scale,
ConvertPolicy  overflow_policy,
RoundingPolicy  rounding_policy,
const ActivationLayerInfo act_info = ActivationLayerInfo() 
)

Initialise the kernel's input, output and border mode.

Valid configurations (Input1,Input2) -> Output :

  • (U8,U8) -> U8
  • (U8,U8) -> S16
  • (U8,S16) -> S16
  • (S16,U8) -> S16
  • (S16,S16) -> S16
  • (F16,F16) -> F16
  • (F32,F32) -> F32
  • (QASYMM8,QASYMM8) -> QASYMM8
  • (QASYMM8_SIGNED,QASYMM8_SIGNED) -> QASYMM8_SIGNED
  • (QSYMM16,QSYMM16) -> QSYMM16
  • (QSYMM16,QSYMM16) -> S32
Parameters
[in]input1An input tensor info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/F16/F32.
[in]input2An input tensor info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/F16/F32.
[out]outputThe output tensor info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/F16/F32.
[in]scaleScale to apply after multiplication. Scale must be positive and its value must be either 1/255 or 1/2^n where n is between 0 and 15.
[in]overflow_policyOverflow policy. Supported overflow policies: Wrap, Saturate
[in]rounding_policyRounding policy. Supported rounding modes: to zero, to nearest even.
[in]act_info(Optional) Activation layer information in case of a fused activation.

Definition at line 148 of file CLPixelWiseMultiplicationKernel.cpp.

References CLKernelLibrary::get().

150 {
151  configure(CLKernelLibrary::get().get_compile_context(), input1, input2, output, scale, overflow_policy, rounding_policy, act_info);
152 }
static CLKernelLibrary & get()
Access the KernelLibrary singleton.
void configure(ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output, float scale, ConvertPolicy overflow_policy, RoundingPolicy rounding_policy, const ActivationLayerInfo &act_info=ActivationLayerInfo())
Initialise the kernel&#39;s input, output and border mode.

◆ configure() [2/2]

void configure ( const CLCompileContext compile_context,
ITensorInfo input1,
ITensorInfo input2,
ITensorInfo output,
float  scale,
ConvertPolicy  overflow_policy,
RoundingPolicy  rounding_policy,
const ActivationLayerInfo act_info = ActivationLayerInfo() 
)

Initialise the kernel's input, output and border mode.

Valid configurations (Input1,Input2) -> Output :

  • (U8,U8) -> U8
  • (U8,U8) -> S16
  • (U8,S16) -> S16
  • (S16,U8) -> S16
  • (S16,S16) -> S16
  • (F16,F16) -> F16
  • (F32,F32) -> F32
  • (QASYMM8,QASYMM8) -> QASYMM8
  • (QASYMM8_SIGNED,QASYMM8_SIGNED) -> QASYMM8_SIGNED
  • (QSYMM16,QSYMM16) -> QSYMM16
  • (QSYMM16,QSYMM16) -> S32
Parameters
[in]compile_contextThe compile context to be used.
[in]input1An input tensor info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/F16/F32.
[in]input2An input tensor info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/F16/F32.
[out]outputThe output tensor info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/F16/F32.
[in]scaleScale to apply after multiplication. Scale must be positive and its value must be either 1/255 or 1/2^n where n is between 0 and 15.
[in]overflow_policyOverflow policy. Supported overflow policies: Wrap, Saturate
[in]rounding_policyRounding policy. Supported rounding modes: to zero, to nearest even.
[in]act_info(Optional) Activation layer information in case of a fused activation.

Definition at line 154 of file CLPixelWiseMultiplicationKernel.cpp.

References ActivationLayerInfo::a(), ActivationLayerInfo::activation(), CLBuildOptions::add_option(), CLBuildOptions::add_option_if(), CLBuildOptions::add_option_if_else(), ARM_COMPUTE_ERROR_ON_NULLPTR, ARM_COMPUTE_ERROR_THROW_ON, ActivationLayerInfo::b(), arm_compute::create_kernel(), ITensorInfo::data_type(), ITensorInfo::element_size(), ActivationLayerInfo::enabled(), arm_compute::F32, arm_compute::float_to_string_with_full_precision(), arm_compute::get_cl_type_from_data_type(), arm_compute::is_data_type_float(), arm_compute::is_data_type_quantized(), arm_compute::is_data_type_quantized_asymmetric(), kernel_name, arm_compute::lower_string(), ICLKernel::num_arguments_per_3D_tensor(), UniformQuantizationInfo::offset, CLBuildOptions::options(), ITensorInfo::quantization_info(), arm_compute::S32, UniformQuantizationInfo::scale, arm_compute::string_from_activation_func(), arm_compute::support::cpp11::to_string(), arm_compute::TO_ZERO, QuantizationInfo::uniform(), arm_compute::validate_arguments(), and arm_compute::WRAP.

156 {
157  ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output);
158  ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input1, input2, output,
159  scale, overflow_policy, rounding_policy, act_info));
160 
161  // Configure kernel window
162  auto win_config = validate_and_configure_window(input1, input2, output);
163  ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
164 
165  _input1 = input1;
166  _input2 = input2;
167  _output = output;
168 
169  int scale_int = -1;
170  // Extract sign, exponent and mantissa
171  int exponent = 0;
172  float normalized_mantissa = std::frexp(scale, &exponent);
173  // Use int scaling if factor is equal to 1/2^n for 0 <= n <= 15
174  // frexp returns 0.5 as mantissa which means that the exponent will be in the range of -1 <= e <= 14
175  // Moreover, it will be negative as we deal with 1/2^n
176  if((normalized_mantissa == 0.5f) && (-14 <= exponent) && (exponent <= 1))
177  {
178  // Store the positive exponent. We know that we compute 1/2^n
179  // Additionally we need to subtract 1 to compensate that frexp used a mantissa of 0.5
180  scale_int = std::abs(exponent - 1);
181  }
182 
183  std::string acc_type;
184  // Check if it has float inputs and output
185  if(is_data_type_float(input1->data_type()) || is_data_type_float(input2->data_type()))
186  {
187  scale_int = -1;
188  acc_type = (input1->data_type() == DataType::F32 || input2->data_type() == DataType::F32) ? "float" : "half";
189  }
190  else
191  {
192  if(input1->element_size() == 2 || input2->element_size() == 2)
193  {
194  // Use 32-bit accumulator for 16-bit input
195  acc_type = "int";
196  }
197  else
198  {
199  // Use 16-bit accumulator for 8-bit input
200  acc_type = "ushort";
201  }
202  }
203 
204  const bool is_quantized = is_data_type_quantized(input1->data_type());
205 
206  // Set kernel build options
207  std::string kernel_name = "pixelwise_mul";
208  CLBuildOptions build_opts;
209  build_opts.add_option("-DDATA_TYPE_IN1=" + get_cl_type_from_data_type(input1->data_type()));
210  build_opts.add_option("-DDATA_TYPE_IN2=" + get_cl_type_from_data_type(input2->data_type()));
211  build_opts.add_option("-DDATA_TYPE_OUT=" + get_cl_type_from_data_type(output->data_type()));
212  build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration));
213  if(is_quantized && (output->data_type() != DataType::S32))
214  {
215  const UniformQuantizationInfo iq1_info = input1->quantization_info().uniform();
216  const UniformQuantizationInfo iq2_info = input2->quantization_info().uniform();
217  const UniformQuantizationInfo oq_info = output->quantization_info().uniform();
218 
219  build_opts.add_option_if(is_data_type_quantized_asymmetric(input1->data_type()),
220  "-DOFFSET_IN1=" + support::cpp11::to_string(iq1_info.offset));
221  build_opts.add_option_if(is_data_type_quantized_asymmetric(input2->data_type()),
222  "-DOFFSET_IN2=" + support::cpp11::to_string(iq2_info.offset));
223  build_opts.add_option_if(is_data_type_quantized_asymmetric(output->data_type()),
224  "-DOFFSET_OUT=" + support::cpp11::to_string(oq_info.offset));
225  build_opts.add_option("-DSCALE_IN1=" + float_to_string_with_full_precision(iq1_info.scale));
226  build_opts.add_option("-DSCALE_IN2=" + float_to_string_with_full_precision(iq2_info.scale));
227  build_opts.add_option("-DSCALE_OUT=" + float_to_string_with_full_precision(oq_info.scale));
228  kernel_name += "_quantized";
229  }
230  else
231  {
232  kernel_name += (scale_int >= 0) ? "_int" : "_float";
233  build_opts.add_option_if_else(overflow_policy == ConvertPolicy::WRAP || is_data_type_float(output->data_type()), "-DWRAP", "-DSATURATE");
234  build_opts.add_option_if_else(rounding_policy == RoundingPolicy::TO_ZERO, "-DROUND=_rtz", "-DROUND=_rte");
235  build_opts.add_option("-DACC_DATA_TYPE=" + acc_type);
236  if(act_info.enabled())
237  {
238  build_opts.add_option("-DACTIVATION_TYPE=" + lower_string(string_from_activation_func(act_info.activation())));
239  build_opts.add_option("-DA_VAL=" + float_to_string_with_full_precision(act_info.a()));
240  build_opts.add_option("-DB_VAL=" + float_to_string_with_full_precision(act_info.b()));
241  }
242  }
243 
244  // Create kernel
245  _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
246 
247  // Set scale argument
248  unsigned int idx = 3 * num_arguments_per_3D_tensor(); // Skip the inputs and output parameters
249 
250  if(scale_int >= 0 && !is_quantized)
251  {
252  _kernel.setArg(idx++, scale_int);
253  }
254  else
255  {
256  _kernel.setArg(idx++, scale);
257  }
258 
259  ICLKernel::configure_internal(win_config.second);
260 }
bool is_data_type_quantized(DataType dt)
Check if a given data type is of quantized type.
Definition: Utils.h:1168
std::string to_string(T &&value)
Convert integer and float values to string.
1 channel, 1 F32 per channel
const std::string & string_from_activation_func(ActivationLayerInfo::ActivationFunction act)
Translates a given activation function to a string.
Definition: Utils.cpp:163
#define ARM_COMPUTE_ERROR_THROW_ON(status)
Definition: Error.h:455
std::string lower_string(const std::string &val)
Lower a given string.
Definition: Utils.cpp:350
1 channel, 1 S32 per channel
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
static constexpr unsigned int num_arguments_per_3D_tensor()
Returns the number of arguments enqueued per 3D tensor object.
Definition: ICLKernel.h:214
std::string float_to_string_with_full_precision(float val)
Create a string with the float in full precision.
Definition: Utils.h:1262
std::string kernel_name
std::string get_cl_type_from_data_type(const DataType &dt)
Translates a tensor data type to the appropriate OpenCL type.
Definition: CLHelpers.cpp:37
bool is_data_type_quantized_asymmetric(DataType dt)
Check if a given data type is of asymmetric quantized type.
Definition: Utils.h:1190
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, const GEMMLowpOutputStageInfo *output_stage)
unsigned int num_elems_processed_per_iteration
#define ARM_COMPUTE_ERROR_ON_NULLPTR(...)
Definition: Validate.h:161
Truncates the least significant values that are lost in operations.
bool is_data_type_float(DataType dt)
Check if a given data type is of floating point type.
Definition: Utils.h:1148

◆ 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_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 272 of file CLPixelWiseMultiplicationKernel.cpp.

References arm_compute::ACL_DST, arm_compute::ACL_SRC_0, arm_compute::ACL_SRC_1, ICLKernel::add_3D_tensor_argument(), ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW, ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL, ARM_COMPUTE_UNUSED, Window::broadcast_if_dimension_le_one(), Window::collapse_if_possible(), TensorShape::collapsed_from(), Window::DimZ, arm_compute::test::validation::dst, arm_compute::enqueue(), Window::first_slice_window_3D(), ITensorPack::get_const_tensor(), ITensorPack::get_tensor(), ICLKernel::lws_hint(), Dimensions< T >::num_dimensions(), arm_compute::test::validation::reference::slice(), Window::slide_window_slice_3D(), TensorShape::total_size(), and IKernel::window().

273 {
276 
277  const auto src_0 = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC_0));
278  const auto src_1 = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC_1));
279  auto dst = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_DST));
280 
281  const TensorShape &in_shape1 = src_0->info()->tensor_shape();
282  const TensorShape &in_shape2 = src_1->info()->tensor_shape();
283  const TensorShape &out_shape = dst->info()->tensor_shape();
284 
285  bool can_collapse = true;
286  if(std::min(in_shape1.total_size(), in_shape2.total_size()) > 1)
287  {
288  can_collapse = (std::min(in_shape1.num_dimensions(), in_shape2.num_dimensions()) > Window::DimZ);
289  for(size_t d = Window::DimZ; can_collapse && (d < out_shape.num_dimensions()); ++d)
290  {
291  can_collapse = (in_shape1[d] == in_shape2[d]);
292  }
293  }
294 
295  bool has_collapsed = false;
296  Window collapsed = can_collapse ? window.collapse_if_possible(ICLKernel::window(), Window::DimZ, &has_collapsed) : window;
297 
298  const TensorShape &in_shape1_collapsed = has_collapsed ? in_shape1.collapsed_from(Window::DimZ) : in_shape1;
299  const TensorShape &in_shape2_collapsed = has_collapsed ? in_shape2.collapsed_from(Window::DimZ) : in_shape2;
300 
301  Window slice = collapsed.first_slice_window_3D();
302  Window slice_input1 = slice.broadcast_if_dimension_le_one(in_shape1_collapsed);
303  Window slice_input2 = slice.broadcast_if_dimension_le_one(in_shape2_collapsed);
304 
305  do
306  {
307  unsigned int idx = 0;
308  add_3D_tensor_argument(idx, src_0, slice_input1);
309  add_3D_tensor_argument(idx, src_1, slice_input2);
310  add_3D_tensor_argument(idx, dst, slice);
311  enqueue(queue, *this, slice, lws_hint());
312 
313  ARM_COMPUTE_UNUSED(collapsed.slide_window_slice_3D(slice_input1));
314  ARM_COMPUTE_UNUSED(collapsed.slide_window_slice_3D(slice_input2));
315  }
316  while(collapsed.slide_window_slice_3D(slice));
317 }
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
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
#define ARM_COMPUTE_UNUSED(...)
To avoid unused variables warnings.
Definition: Error.h:152
Window collapse_if_possible(const Window &full_window, size_t first, size_t last, bool *has_collapsed=nullptr) const
Collapse the dimensions between first and last if possible.
Definition: Window.inl:68
#define ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(k)
Definition: Validate.h:941
static constexpr size_t DimZ
Alias for dimension 2 also known as Z dimension.
Definition: Window.h:47
#define ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(f, s)
Definition: Validate.h:205
SimpleTensor< T > slice(const SimpleTensor< T > &src, Coordinates starts, Coordinates ends)

◆ validate()

Status validate ( const ITensorInfo input1,
const ITensorInfo input2,
const ITensorInfo output,
float  scale,
ConvertPolicy  overflow_policy,
RoundingPolicy  rounding_policy,
const ActivationLayerInfo act_info = ActivationLayerInfo() 
)
static

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

Valid configurations (Input1,Input2) -> Output :

  • (U8,U8) -> U8
  • (U8,U8) -> S16
  • (U8,S16) -> S16
  • (S16,U8) -> S16
  • (S16,S16) -> S16
  • (F16,F16) -> F16
  • (F32,F32) -> F32
  • (QASYMM8,QASYMM8) -> QASYMM8
  • (QASYMM8_SIGNED,QASYMM8_SIGNED) -> QASYMM8_SIGNED
  • (QSYMM16,QSYMM16) -> QSYMM16
  • (QSYMM16,QSYMM16) -> S32
Parameters
[in]input1An input tensor info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/F16/F32.
[in]input2An input tensor info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/F16/F32.
[in]outputThe output tensor info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/F16/F32.
[in]scaleScale to apply after multiplication. Scale must be positive and its value must be either 1/255 or 1/2^n where n is between 0 and 15.
[in]overflow_policyOverflow policy. Supported overflow policies: Wrap, Saturate
[in]rounding_policyRounding policy. Supported rounding modes: to zero, to nearest even.
[in]act_info(Optional) Activation layer information in case of a fused activation.
Returns
a status

Definition at line 262 of file CLPixelWiseMultiplicationKernel.cpp.

References ARM_COMPUTE_ERROR_ON_NULLPTR, ARM_COMPUTE_RETURN_ON_ERROR, ICloneable< T >::clone(), and arm_compute::validate_arguments().

Referenced by CLPixelWiseMultiplication::validate().

264 {
265  ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output);
266  ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input1, input2, output, scale, overflow_policy, rounding_policy, act_info));
267  ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input1->clone().get(), input2->clone().get(), output->clone().get()).first);
268 
269  return Status{};
270 }
#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 *input, const ITensorInfo *bias, const ITensorInfo *output, const GEMMLowpOutputStageInfo *output_stage)
#define ARM_COMPUTE_ERROR_ON_NULLPTR(...)
Definition: Validate.h:161

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