Compute Library
 21.08
CpuGemmLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel Class Reference

Kernel used to quantize down the int32 accumulator values of GEMMLowp to QSYMM16. More...

#include <CpuGemmLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel.h>

Collaboration diagram for CpuGemmLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel:
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Public Member Functions

 CpuGemmLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel ()=default
 
 ARM_COMPUTE_DISALLOW_COPY_ALLOW_MOVE (CpuGemmLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel)
 
void configure (ITensorInfo *src, ITensorInfo *bias, ITensorInfo *dst, int result_fixedpoint_multiplier, int result_shift, int min=0, int max=0)
 Initialise the kernel's input and output. More...
 
void run_op (ITensorPack &tensors, const Window &window, const ThreadInfo &info) override
 Execute the kernel on the passed window. More...
 
const char * name () const override
 Name of the kernel. More...
 
- Public Member Functions inherited from ICPPKernel
virtual ~ICPPKernel ()=default
 Default destructor. More...
 
virtual void run (const Window &window, const ThreadInfo &info)
 Execute the kernel on the passed window. More...
 
virtual void run_nd (const Window &window, const ThreadInfo &info, const Window &thread_locator)
 legacy compatibility layer for implemantions which do not support thread_locator In these cases we simply narrow the interface down the legacy version 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 *bias, const ITensorInfo *dst, int min=0, int max=0)
 Static function to check if given info will lead to a valid configuration. More...
 

Detailed Description

Kernel used to quantize down the int32 accumulator values of GEMMLowp to QSYMM16.

This kernel takes a final int32 accumulator value (the output of CpuGemmLowpMatrixMultiplyKernel), and processes it to obtain the final QSYMM16 value. The following computations will be performed by the kernel:

  1. Compute fixed point multiplication between each entry of input by result_fixedpoint_multiplier
  2. Add bias to final result if bias tensor is not a nullptr
  3. Round to nearest division by a power-of-two using result_shift
  4. Clamp the value between the specified min and max bounds
  5. Clamp the resulting int32 values to the [-32768, 32767] range and cast to QSYMM16.

Definition at line 51 of file CpuGemmLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel.h.

Constructor & Destructor Documentation

◆ CpuGemmLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel()

Member Function Documentation

◆ ARM_COMPUTE_DISALLOW_COPY_ALLOW_MOVE()

ARM_COMPUTE_DISALLOW_COPY_ALLOW_MOVE ( CpuGemmLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel  )

◆ configure()

void configure ( ITensorInfo src,
ITensorInfo bias,
ITensorInfo dst,
int  result_fixedpoint_multiplier,
int  result_shift,
int  min = 0,
int  max = 0 
)

Initialise the kernel's input and output.

Parameters
[in]srcInput tensor info. Data type supported: S32
[in]biasBiases tensor info. Only shared biases supported and it can be a nullptr if the biases addition is not required. Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as input.
[out]dstOutput tensor info. Data type supported: Data type supported: QSYMM16
[in]result_fixedpoint_multiplierFixed point value to be multiplied to each element of the input matrix when once the result_offset has been add
[in]result_shiftInteger value used to round to nearest division by a power-of-two the result after the fixed point multiplication
[in]min(Optional) Min value used to saturate down the output result before converting back to QSYMM16. Defaults to 0.
[in]max(Optional) Max value used to saturate up the output result before converting back to QSYMM16. Along with min, this value can be used to implement "rectified linear unit" activation functions. Defaults to 0.

Definition at line 175 of file CpuGemmLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel.cpp.

References ARM_COMPUTE_ERROR_ON_NULLPTR, ARM_COMPUTE_ERROR_THROW_ON, ARM_COMPUTE_UNUSED, arm_compute::auto_init_if_empty(), arm_compute::calculate_max_window(), ICloneable< T >::clone(), and arm_compute::QSYMM16.

177 {
178  // Perform validate step
179  ARM_COMPUTE_UNUSED(bias, dst);
181  ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(src, bias, dst, min, max));
182 
183  _result_fixedpoint_multiplier = result_fixedpoint_multiplier;
184  _result_shift = result_shift;
185  _min = min;
186  _max = max;
187 
188  // Output auto inizialitation if not yet initialized
189  auto_init_if_empty(*src, src->clone()->set_data_type(DataType::QSYMM16));
190  // Configure kernel window
191  Window win_config = calculate_max_window(*src, Steps());
192  ICpuKernel::configure(win_config);
193 
194  // Check if we need to clamp the result using min and max
195  const bool is_bounded_relu = !(min <= -32768 && max >= 32767);
196  _func = is_bounded_relu ? &CpuGemmLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel::run_internal<true> :
197  &CpuGemmLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel::run_internal<false>;
198 }
Window calculate_max_window(const ValidRegion &valid_region, const Steps &steps, bool skip_border, BorderSize border_size)
quantized, symmetric fixed-point 16-bit number
#define ARM_COMPUTE_ERROR_THROW_ON(status)
Definition: Error.h:455
SimpleTensor< float > src
Definition: DFT.cpp:155
#define ARM_COMPUTE_UNUSED(...)
To avoid unused variables warnings.
Definition: Error.h:152
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...
#define ARM_COMPUTE_ERROR_ON_NULLPTR(...)
Definition: Validate.h:157

◆ name()

const char * name ( ) const
overridevirtual

Name of the kernel.

Returns
Kernel name

Implements ICPPKernel.

Definition at line 221 of file CpuGemmLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel.cpp.

222 {
223  return "CpuGemmLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel";
224 }

◆ run_op()

void run_op ( ITensorPack tensors,
const Window window,
const ThreadInfo info 
)
overridevirtual

Execute the kernel on the passed window.

Warning
If is_parallelisable() returns false then the passed window must be equal to window()
Note
The window has to be a region within the window returned by the window() method
The width of the window has to be a multiple of num_elems_processed_per_iteration().
Parameters
[in]tensorsA vector containing the tensors to operate on.
[in]windowRegion on which to execute the kernel. (Must be a region of the window returned by window())
[in]infoInfo about executing thread and CPU.

Reimplemented from ICPPKernel.

Definition at line 207 of file CpuGemmLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel.cpp.

References arm_compute::ACL_BIAS, arm_compute::ACL_DST, arm_compute::ACL_SRC, ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW, ARM_COMPUTE_ERROR_ON_MSG, ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL, ARM_COMPUTE_UNUSED, ITensorPack::empty(), ITensorPack::get_const_tensor(), ITensorPack::get_tensor(), and IKernel::window().

208 {
212  ARM_COMPUTE_ERROR_ON_MSG(tensors.empty(), "No inputs provided");
213 
214  auto src = tensors.get_const_tensor(TensorType::ACL_SRC);
215  auto bias = tensors.get_const_tensor(TensorType::ACL_BIAS);
216  auto dst = tensors.get_tensor(TensorType::ACL_DST);
217 
218  (this->*_func)(src, bias, dst, window);
219 }
const Window & window() const
The maximum window the kernel can be executed on.
Definition: IKernel.cpp:28
SimpleTensor< float > src
Definition: DFT.cpp:155
#define ARM_COMPUTE_UNUSED(...)
To avoid unused variables warnings.
Definition: Error.h:152
#define ARM_COMPUTE_ERROR_ON_MSG(cond, msg)
Definition: Error.h:456
#define ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(k)
Definition: Validate.h:915
ScaleKernelInfo info(interpolation_policy, default_border_mode, PixelValue(), sampling_policy, false)
#define ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(f, s)
Definition: Validate.h:201

◆ validate()

Status validate ( const ITensorInfo src,
const ITensorInfo bias,
const ITensorInfo dst,
int  min = 0,
int  max = 0 
)
static

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

Similar to CpuGemmLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel::configure()

Returns
a status

Definition at line 200 of file CpuGemmLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel.cpp.

References ARM_COMPUTE_ERROR_ON_NULLPTR, and ARM_COMPUTE_RETURN_ON_ERROR.

Referenced by CpuGemmLowpOutputStage::validate().

201 {
203  ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, bias, output, min, max));
204  return Status{};
205 }
#define ARM_COMPUTE_RETURN_ON_ERROR(status)
Checks if a status contains an error and returns it.
Definition: Error.h:204
#define ARM_COMPUTE_ERROR_ON_NULLPTR(...)
Definition: Validate.h:157

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