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author | Gian Marco <gianmarco.iodice@arm.com> | 2017-11-17 09:27:57 +0000 |
---|---|---|
committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-11-02 16:35:24 +0000 |
commit | 6b77e917801b4e979796ea75c538eef740482089 (patch) | |
tree | 0e693ecb1eb0b05018901a992b56781a08b9c266 /tests/validation/CPP | |
parent | b3c81cb4100b3a449db5232364e18e649b26df58 (diff) | |
download | ComputeLibrary-6b77e917801b4e979796ea75c538eef740482089.tar.gz |
COMPMID-665 - NEON: Add QASYMM8 in place Activation layer
- Added min and max arguments for QuantizeDownInt32ToUint8Scale in order
to apply bounded relu
- Added support for int32_t biases
- Extended tests
Change-Id: I015dae17faa7284766b5435ca33bcf593c1b2b69
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/96512
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>
Diffstat (limited to 'tests/validation/CPP')
-rw-r--r-- | tests/validation/CPP/GEMMLowp.cpp | 54 | ||||
-rw-r--r-- | tests/validation/CPP/GEMMLowp.h | 9 |
2 files changed, 53 insertions, 10 deletions
diff --git a/tests/validation/CPP/GEMMLowp.cpp b/tests/validation/CPP/GEMMLowp.cpp index 8670a22a66..bf002cf2b5 100644 --- a/tests/validation/CPP/GEMMLowp.cpp +++ b/tests/validation/CPP/GEMMLowp.cpp @@ -33,6 +33,36 @@ namespace validation { namespace reference { +namespace +{ +template <typename T> +void quantize_down_int32_to_uint8_scale(const SimpleTensor<T> *in, const SimpleTensor<T> *bias, SimpleTensor<uint8_t> *dst, int32_t result_offset, int32_t result_mult_int, int32_t result_shift, + int32_t min, int32_t max) +{ + const int cols_in = in->shape().x(); + + for(int i = 0; i < in->num_elements(); ++i) + { + int32_t result = ((*in)[i] + result_offset) * result_mult_int; + + if(bias != nullptr) + { + result += (*bias)[i % cols_in]; + } + + result >>= result_shift; + + // Bounded ReLu + if(min != max) + { + result = std::max(min, std::min(max, result)); + } + + (*dst)[i] = static_cast<uint8_t>(std::max(0, std::min(255, result))); + } +} +} // namespace + template <typename T> SimpleTensor<int32_t> gemmlowp_matrix_multiply_core(const SimpleTensor<T> &a, const SimpleTensor<T> &b, int32_t a_offset, int32_t b_offset) { @@ -80,21 +110,31 @@ SimpleTensor<int32_t> gemmlowp(const SimpleTensor<int8_t> &a, const SimpleTensor } template <typename T> -SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale(const SimpleTensor<T> &in, int32_t result_offset, int32_t result_mult_int, int32_t result_shift) +SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale(const SimpleTensor<T> &in, int32_t result_offset, int32_t result_mult_int, int32_t result_shift, int32_t min, int32_t max) { SimpleTensor<uint8_t> dst(in.shape(), DataType::QASYMM8); - for(int i = 0; i < in.num_elements(); ++i) - { - const int32_t result = ((in[i] + result_offset) * result_mult_int) >> result_shift; - dst[i] = static_cast<uint8_t>(std::max(0, std::min(255, result))); - } + quantize_down_int32_to_uint8_scale<T>(&in, nullptr, &dst, result_offset, result_mult_int, result_shift, min, max); + + return dst; +} + +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, int32_t result_mult_int, int32_t result_shift, + int32_t min, int32_t max) +{ + SimpleTensor<uint8_t> dst(in.shape(), DataType::QASYMM8); + + quantize_down_int32_to_uint8_scale<T>(&in, &bias, &dst, result_offset, result_mult_int, result_shift, min, max); return dst; } template SimpleTensor<int32_t> gemmlowp_matrix_multiply_core(const SimpleTensor<uint8_t> &a, const SimpleTensor<uint8_t> &b, int32_t a_offset, int32_t b_offset); -template SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale(const SimpleTensor<int32_t> &a, int32_t result_offset, int32_t result_mult_int, int32_t result_shift); +template SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale(const SimpleTensor<int32_t> &a, int32_t result_offset, int32_t result_mult_int, int32_t result_shift, int32_t min, + int32_t max); +template SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale(const SimpleTensor<int32_t> &a, const SimpleTensor<int32_t> &b, int32_t result_offset, int32_t result_mult_int, + int32_t result_shift, int32_t min, int32_t max); } // namespace reference } // namespace validation } // namespace test diff --git a/tests/validation/CPP/GEMMLowp.h b/tests/validation/CPP/GEMMLowp.h index cbed2206e3..ee33d8e0c0 100644 --- a/tests/validation/CPP/GEMMLowp.h +++ b/tests/validation/CPP/GEMMLowp.h @@ -35,14 +35,17 @@ namespace validation { namespace reference { +SimpleTensor<int32_t> gemmlowp(const SimpleTensor<int8_t> &a, const SimpleTensor<int8_t> &b); + template <typename T> SimpleTensor<int32_t> gemmlowp_matrix_multiply_core(const SimpleTensor<T> &a, const SimpleTensor<T> &b, int32_t a_offset, int32_t b_offset); template <typename T> -SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale(const SimpleTensor<T> &in, int32_t result_offset, int32_t result_mult_int, int32_t result_shift); - -SimpleTensor<int32_t> gemmlowp(const SimpleTensor<int8_t> &a, const SimpleTensor<int8_t> &b); +SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale(const SimpleTensor<T> &in, int32_t result_offset, int32_t result_mult_int, 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(const SimpleTensor<T> &in, const SimpleTensor<T> &bias, int32_t result_offset, int32_t result_mult_int, int32_t result_shift, + int32_t min = 0, int32_t max = 0); } // namespace reference } // namespace validation } // namespace test |