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| author | Georgios Pinitas <georgios.pinitas@arm.com> | 2019-11-21 14:10:25 +0000 |
|---|---|---|
| committer | Georgios Pinitas <georgios.pinitas@arm.com> | 2019-11-27 10:56:10 +0000 |
| commit | 448a81fcec04333364a1e3266d5081596d3a0477 (patch) | |
| tree | bd5382a58fae39a8014157423a8ff339d39e14b9 /tests/validation/reference/GEMMLowp.h | |
| 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 'tests/validation/reference/GEMMLowp.h')
| -rw-r--r-- | tests/validation/reference/GEMMLowp.h | 19 |
1 files changed, 6 insertions, 13 deletions
diff --git a/tests/validation/reference/GEMMLowp.h b/tests/validation/reference/GEMMLowp.h index 815527e1b7..7ff01ef611 100644 --- a/tests/validation/reference/GEMMLowp.h +++ b/tests/validation/reference/GEMMLowp.h @@ -52,20 +52,13 @@ template <typename T> SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale(const SimpleTensor<T> &in, const SimpleTensor<T> &bias, int32_t result_offset, std::vector<int32_t> result_mult_int, std::vector<int32_t> result_shift, int32_t min = 0, int32_t max = 0); -template <typename T> -SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale_by_fixedpoint(const SimpleTensor<T> &in, std::vector<int32_t> result_fixedpoint_multiplier, std::vector<int32_t> result_shift, - int32_t result_offset_after_shift, int32_t min = 0, int32_t max = 0); - -template <typename T> -SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale_by_fixedpoint(const SimpleTensor<T> &in, const SimpleTensor<T> &bias, std::vector<int32_t> result_fixedpoint_multiplier, - std::vector<int32_t> result_shift, int32_t result_offset_after_shift, int32_t min = 0, int32_t max = 0); +template <typename TIn, typename TOut> +SimpleTensor<TOut> gemmlowp_quantize_down_scale_by_fixedpoint(const SimpleTensor<TIn> &in, std::vector<int32_t> result_fixedpoint_multiplier, std::vector<int32_t> result_shift, + int32_t result_offset_after_shift, int32_t min = 0, int32_t max = 0); -template <typename T> -SimpleTensor<int16_t> gemmlowp_quantize_down_int32_to_int16_scale_by_fixedpoint(const SimpleTensor<T> &in, int32_t result_fixedpoint_multiplier, int32_t result_shift, - int32_t min, int32_t max); -template <typename T> -SimpleTensor<int16_t> gemmlowp_quantize_down_int32_to_int16_scale_by_fixedpoint(const SimpleTensor<T> &in, const SimpleTensor<T> &bias, int32_t result_fixedpoint_multiplier, - int32_t result_shift, int32_t min, int32_t max); +template <typename TIn, typename TOut> +SimpleTensor<TOut> gemmlowp_quantize_down_scale_by_fixedpoint(const SimpleTensor<TIn> &in, const SimpleTensor<TIn> &bias, std::vector<int32_t> result_fixedpoint_multiplier, + std::vector<int32_t> result_shift, int32_t result_offset_after_shift, int32_t min = 0, int32_t max = 0); } // namespace reference } // namespace validation } // namespace test |