Compute Library
 21.08
CpuGemmLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel Class Reference

Kernel used to quantize down the int32 accumulator values of GEMMLowp to QASYMM8. More...

#include <CpuGemmLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel.h>

Collaboration diagram for CpuGemmLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel:
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Public Member Functions

 CpuGemmLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel ()=default
 
 ARM_COMPUTE_DISALLOW_COPY_ALLOW_MOVE (CpuGemmLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel)
 
void configure (ITensorInfo *src, ITensorInfo *bias, ITensorInfo *dst, int result_fixedpoint_multiplier, int result_shift, int result_offset_after_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 QASYMM8.

This kernel takes a final int32 accumulator value (the output of CpuGemmLowpMatrixMultiplyKernel), and processes it to obtain the final QASYMM8 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. Add offset to each result
  5. Clamp the value between the specified min and max bounds
  6. Clamp the resulting int32 values to the [0..255] range and cast to QASYMM8.

Definition at line 52 of file CpuGemmLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel.h.

Constructor & Destructor Documentation

◆ CpuGemmLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel()

Member Function Documentation

◆ ARM_COMPUTE_DISALLOW_COPY_ALLOW_MOVE()

ARM_COMPUTE_DISALLOW_COPY_ALLOW_MOVE ( CpuGemmLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel  )

◆ configure()

void configure ( ITensorInfo src,
ITensorInfo bias,
ITensorInfo dst,
int  result_fixedpoint_multiplier,
int  result_shift,
int  result_offset_after_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: QASYMM8
[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]result_offset_after_shiftOffset to be applied to result before converting it back to QASYMM8
[in]min(Optional) Min value used to saturate down the output result before converting back to QASYMM8
[in]max(Optional) Max value used to saturate up the output result before converting back to QASYMM8, Along with min, this value can be used to implement "rectified linear unit" activation functions

Definition at line 182 of file CpuGemmLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel.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::QASYMM8.

184 {
185  ARM_COMPUTE_UNUSED(bias);
186  // Perform validate step
188  ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(src, bias, dst, min, max));
189 
190  _result_fixedpoint_multiplier = result_fixedpoint_multiplier;
191  _result_shift = result_shift;
192  _result_offset_after_shift = result_offset_after_shift;
193  _min = min;
194  _max = max;
195 
196  // Output auto inizialitation if not yet initialized
197  auto_init_if_empty(*dst, src->clone()->set_data_type(DataType::QASYMM8));
198 
199  // Configure kernel window
200  auto win_config = calculate_max_window(*src, Steps());
201  ICpuKernel::configure(win_config);
202 
203  // Check if we need to clamp the result using min and max
204  const bool is_bounded_relu = !(min <= 0 && max >= 255);
205  _func = is_bounded_relu ? &CpuGemmLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel::run_internal<true> :
206  &CpuGemmLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel::run_internal<false>;
207 }
Window calculate_max_window(const ValidRegion &valid_region, const Steps &steps, bool skip_border, BorderSize border_size)
#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
quantized, asymmetric fixed-point 8-bit number unsigned
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 230 of file CpuGemmLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel.cpp.

231 {
232  return "CpuGemmLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel";
233 }

◆ 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 216 of file CpuGemmLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel.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().

217 {
221  ARM_COMPUTE_ERROR_ON_MSG(tensors.empty(), "No inputs provided");
222 
223  auto src = tensors.get_const_tensor(TensorType::ACL_SRC);
224  auto bias = tensors.get_const_tensor(TensorType::ACL_BIAS);
225  auto dst = tensors.get_tensor(TensorType::ACL_DST);
226 
227  (this->*_func)(src, bias, dst, window);
228 }
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 CpuGemmLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel::configure()

Returns
a status

Definition at line 209 of file CpuGemmLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel.cpp.

References ARM_COMPUTE_ERROR_ON_NULLPTR, and ARM_COMPUTE_RETURN_ON_ERROR.

Referenced by CpuGemmLowpOutputStage::validate().

210 {
212  ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(src, bias, dst, min, max));
213  return Status{};
214 }
#define ARM_COMPUTE_RETURN_ON_ERROR(status)
Checks if a status contains an error and returns it.
Definition: Error.h:204
SimpleTensor< float > src
Definition: DFT.cpp:155
#define ARM_COMPUTE_ERROR_ON_NULLPTR(...)
Definition: Validate.h:157

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