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author | Georgios Pinitas <georgios.pinitas@arm.com> | 2019-11-21 14:10:25 +0000 |
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committer | Georgios Pinitas <georgios.pinitas@arm.com> | 2019-11-27 10:56:10 +0000 |
commit | 448a81fcec04333364a1e3266d5081596d3a0477 (patch) | |
tree | bd5382a58fae39a8014157423a8ff339d39e14b9 /arm_compute/runtime/NEON | |
parent | 449cbf9c20287fca9a56898cdc5821c061a66ce3 (diff) | |
download | ComputeLibrary-448a81fcec04333364a1e3266d5081596d3a0477.tar.gz |
COMPMID-2805: Add QASYMM8_SIGNED support in NEGEMMLowpOutputStage
Add support from requantizing down from S32 to Int8 with fixed point
requantization. This involves the following:
- Compute fixed point multiplication between each entry of input by
result_fixedpoint_multiplier
- Add bias to final result if bias tensor is not a nullptr
- Round to nearest division by a power-of-two using result_shift
- Add offset to each result
- Clamp the value between the specified min and max bounds
- Cast to int8 data type
Change-Id: I641b3fac0833c568d8565ccb859bbc561a24c17d
Signed-off-by: Georgios Pinitas <georgios.pinitas@arm.com>
Reviewed-on: https://review.mlplatform.org/c/2340
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'arm_compute/runtime/NEON')
-rw-r--r-- | arm_compute/runtime/NEON/functions/NEGEMMLowpOutputStage.h | 59 |
1 files changed, 59 insertions, 0 deletions
diff --git a/arm_compute/runtime/NEON/functions/NEGEMMLowpOutputStage.h b/arm_compute/runtime/NEON/functions/NEGEMMLowpOutputStage.h index 5ece753660..1a65f3b6ce 100644 --- a/arm_compute/runtime/NEON/functions/NEGEMMLowpOutputStage.h +++ b/arm_compute/runtime/NEON/functions/NEGEMMLowpOutputStage.h @@ -147,6 +147,65 @@ public: */ static Status validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, int min = 0, int max = 0); }; +/** Basic function to execute NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPoint on NEON. + * + * NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPoint depends on 3 parameters: + * + * result_fixedpoint_multiplier, result_shift, result_offset_after_shift + * + * The final result is: + * + * (FixedPointMul(input[i][k], result_fixedpoint_multiplier) >> result_shift) + result_offset_after_shift + * + * where FixedPointMul(x, y) is the nearest integer to the following + * mathematical expression, evaluated without overflow or intermediate rounding: + * + * (x * y) / 2^31 + * + * For more information: https://github.com/google/gemmlowp/blob/master/public/output_stages.h#L68 + * + * In case the bias tensor is provided, the final result is: + * + * ((FixedPointMul(input[i][k] + bias[k], result_fixedpoint_multiplier)) >> result_shift) + result_offset_after_shift + * + * This function calls the following NEON kernels: + * + * -# @ref NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel + * + * @note The function accepts also 2 optional input arguments (min and max) which can be used to implement "rectified linear unit" activation functions + * after the result is shifted right by result_shift +*/ +class NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPoint : public INESimpleFunctionNoBorder +{ +public: + /** Initialise the kernel's inputs, output + * + * @param[in] input Input tensor. Data type supported: S32 + * @param[in] bias Biases tensor. 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 @p input. + * @param[out] output Output tensor. Data type supported: Data type supported: QASYMM8_SIGNED + * @param[in] result_fixedpoint_multiplier Fixed point value to be multiplied to each element of the input matrix when once the result_offset has been add + * @param[in] result_shift Number of bits to shift right the result after the fixed point multiplication + * @param[in] result_offset_after_shift Offset to be applied to result before converting it back to QASYMM8_SIGNED + * @param[in] min (Optional) Min value used to saturate down the output result before converting back to QASYMM8_SIGNED + * @param[in] max (Optional) Max value used to saturate up the output result before converting back to QASYMM8_SIGNED, + * Along with @p min, this value can be used to implement "rectified linear unit" activation functions + */ + void configure(const ITensor *input, const ITensor *bias, ITensor *output, int result_fixedpoint_multiplier, int result_shift, int result_offset_after_shift, int min = 0, int max = 0); + /** Static function to check if given info will lead to a valid configuration of @ref NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPoint + * + * @param[in] input Input tensor. It is the output of @ref NEGEMMLowpMatrixMultiplyCore function. Data type supported: S32 + * @param[in] bias Biases tensor. Only shared biases supported and it can be a nullptr if the addition of biases is not required. + * Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input. + * @param[in] output Output tensor. Data type supported: Data type supported: QASYMM8_SIGNED + * @param[in] min (Optional) Min value used to saturate down the output result before converting back to QASYMM8_SIGNED + * @param[in] max (Optional) Max value used to saturate up the output result before converting back to QASYMM8_SIGNED, + * Along with @p min, this value can be used to implement "rectified linear unit" activation functions + * + * @return a status + */ + static Status validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, int min = 0, int max = 0); +}; /** Basic function to execute NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPoint on NEON. * * NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPoint depends on 2 parameters: |