diff options
Diffstat (limited to 'tests/validation/reference/GEMMLowp.cpp')
| -rw-r--r-- | tests/validation/reference/GEMMLowp.cpp | 71 |
1 files changed, 39 insertions, 32 deletions
diff --git a/tests/validation/reference/GEMMLowp.cpp b/tests/validation/reference/GEMMLowp.cpp index 4283cb5bac..08be4a5182 100644 --- a/tests/validation/reference/GEMMLowp.cpp +++ b/tests/validation/reference/GEMMLowp.cpp @@ -39,10 +39,11 @@ 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) +void quantize_down_int32_to_uint8_scale(const SimpleTensor<T> *in, const SimpleTensor<T> *bias, SimpleTensor<uint8_t> *dst, int32_t result_offset, std::vector<int32_t> result_mult_int, + std::vector<int32_t> result_shift, int32_t min, int32_t max) { - const int cols_in = in->shape().x(); + const int cols_in = in->shape().x(); + const bool is_per_channel = result_mult_int.size() > 1; for(int i = 0; i < in->num_elements(); ++i) { @@ -53,9 +54,9 @@ void quantize_down_int32_to_uint8_scale(const SimpleTensor<T> *in, const SimpleT result += (*bias)[i % cols_in]; } - result *= result_mult_int; + result *= (is_per_channel) ? result_mult_int[i % cols_in] : result_mult_int[0]; - result >>= result_shift; + result >>= (is_per_channel) ? result_shift[i % cols_in] : result_shift[0]; // Bounded ReLu if(min != max) @@ -68,10 +69,11 @@ void quantize_down_int32_to_uint8_scale(const SimpleTensor<T> *in, const SimpleT } template <typename T> -void quantize_down_int32_to_uint8_scale_by_fixedpoint(const SimpleTensor<T> *in, const SimpleTensor<T> *bias, SimpleTensor<uint8_t> *dst, int32_t result_fixedpoint_multiplier, int32_t result_shift, - int32_t result_offset_after_shift, int32_t min, int32_t max) +void quantize_down_int32_to_uint8_scale_by_fixedpoint(const SimpleTensor<T> *in, const SimpleTensor<T> *bias, SimpleTensor<uint8_t> *dst, std::vector<int32_t> result_fixedpoint_multiplier, + std::vector<int32_t> result_shift, int32_t result_offset_after_shift, int32_t min, int32_t max) { - const int cols_in = in->shape().x(); + const int cols_in = in->shape().x(); + const bool is_per_channel = result_fixedpoint_multiplier.size() > 1; for(int i = 0; i < in->num_elements(); ++i) { @@ -83,7 +85,10 @@ void quantize_down_int32_to_uint8_scale_by_fixedpoint(const SimpleTensor<T> *in, } // Fixed point multiplication - result = asymm_rounding_divide_by_pow2(asymm_int_mult(result, result_fixedpoint_multiplier), result_shift); + const int32_t multiplier = (is_per_channel) ? result_fixedpoint_multiplier[i % cols_in] : result_fixedpoint_multiplier[0]; + const int32_t shift = (is_per_channel) ? result_shift[i % cols_in] : result_shift[0]; + + result = asymm_rounding_divide_by_pow2(asymm_int_mult(result, multiplier), shift); result += result_offset_after_shift; // Bounded ReLu @@ -132,8 +137,8 @@ void quantize_down_int32_to_int16_scale_by_fixedpoint(const SimpleTensor<T> *in, } } // namespace -template <typename T_out, typename T_in> -SimpleTensor<T_out> gemmlowp_matrix_multiply_core(const SimpleTensor<T_in> &a, const SimpleTensor<T_in> &b, TensorShape shape_c, int32_t a_offset, int32_t b_offset) +template <typename T_out, typename T_in, typename T_in_1> +SimpleTensor<T_out> gemmlowp_matrix_multiply_core(const SimpleTensor<T_in> &a, const SimpleTensor<T_in_1> &b, TensorShape shape_c, int32_t a_offset, int32_t b_offset) { static_assert(std::is_same<typename std::decay<T_out>::type, int32_t>::value, "Only int32_t is allowed for the output"); @@ -186,14 +191,15 @@ SimpleTensor<T_out> gemmlowp_matrix_multiply_core(const SimpleTensor<T_in> &a, c } // used to validate assembly kernels which don't know anything about offsets -template <typename T1, typename T2> -SimpleTensor<T1> gemmlowp(const SimpleTensor<T2> &a, const SimpleTensor<T2> &b, TensorShape shape_c) +template <typename T1, typename T2, typename T3> +SimpleTensor<T1> gemmlowp(const SimpleTensor<T2> &a, const SimpleTensor<T3> &b, TensorShape shape_c) { - return gemmlowp_matrix_multiply_core<T1, T2>(a, b, shape_c, 0, 0); + return gemmlowp_matrix_multiply_core<T1, T2, T3>(a, b, shape_c, 0, 0); } 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, int32_t min, int32_t max) +SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale(const SimpleTensor<T> &in, int32_t result_offset, std::vector<int32_t> result_mult_int, std::vector<int32_t> result_shift, + int32_t min, int32_t max) { SimpleTensor<uint8_t> dst(in.shape(), DataType::QASYMM8); @@ -203,8 +209,8 @@ SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale(const SimpleTe } 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> 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, int32_t max) { SimpleTensor<uint8_t> dst(in.shape(), DataType::QASYMM8); @@ -214,9 +220,8 @@ SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale(const SimpleTe } template <typename T> -SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale_by_fixedpoint(const SimpleTensor<T> &in, int32_t result_fixedpoint_multiplier, int32_t result_shift, - int32_t result_offset_after_shift, int32_t min, - int32_t max) +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, int32_t max) { SimpleTensor<uint8_t> dst(in.shape(), DataType::QASYMM8); @@ -226,8 +231,8 @@ SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale_by_fixedpoint( } template <typename T> -SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale_by_fixedpoint(const SimpleTensor<T> &in, const SimpleTensor<T> &bias, int32_t result_fixedpoint_multiplier, int32_t result_shift, - int32_t result_offset_after_shift, int32_t min, int32_t max) +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, int32_t max) { SimpleTensor<uint8_t> dst(in.shape(), DataType::QASYMM8); @@ -258,22 +263,24 @@ SimpleTensor<int16_t> gemmlowp_quantize_down_int32_to_int16_scale_by_fixedpoint( return dst; } -template SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale_by_fixedpoint(const SimpleTensor<int32_t> &a, int32_t result_fixedpoint_multiplier, int32_t result_shift, - int32_t result_offset_after_shift, int32_t min, int32_t max); -template SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale_by_fixedpoint(const SimpleTensor<int32_t> &a, const SimpleTensor<int32_t> &b, int32_t result_fixedpoint_multiplier, - int32_t result_shift, int32_t result_offset_after_shift, int32_t min, int32_t max); +template SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale_by_fixedpoint(const SimpleTensor<int32_t> &a, std::vector<int32_t> result_fixedpoint_multiplier, + std::vector<int32_t> result_shift, int32_t result_offset_after_shift, int32_t min, int32_t max); +template SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale_by_fixedpoint(const SimpleTensor<int32_t> &a, const SimpleTensor<int32_t> &b, + std::vector<int32_t> result_fixedpoint_multiplier, + std::vector<int32_t> result_shift, int32_t result_offset_after_shift, int32_t min, int32_t max); template SimpleTensor<int16_t> gemmlowp_quantize_down_int32_to_int16_scale_by_fixedpoint(const SimpleTensor<int32_t> &a, int32_t result_fixedpoint_multiplier, int32_t result_shift, int32_t min, int32_t max); template SimpleTensor<int16_t> gemmlowp_quantize_down_int32_to_int16_scale_by_fixedpoint(const SimpleTensor<int32_t> &a, const SimpleTensor<int32_t> &b, int32_t result_fixedpoint_multiplier, 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, 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); +template SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale(const SimpleTensor<int32_t> &a, int32_t result_offset, std::vector<int32_t> result_mult_int, + std::vector<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, std::vector<int32_t> result_mult_int, + std::vector<int32_t> result_shift, int32_t min, int32_t max); template SimpleTensor<int32_t> gemmlowp_matrix_multiply_core(const SimpleTensor<int8_t> &a, const SimpleTensor<int8_t> &b, TensorShape shape_c, int32_t a_offset, int32_t b_offset); template SimpleTensor<int32_t> gemmlowp_matrix_multiply_core(const SimpleTensor<uint8_t> &a, const SimpleTensor<uint8_t> &b, TensorShape shape_c, int32_t a_offset, int32_t b_offset); -template SimpleTensor<int32_t> gemmlowp(const SimpleTensor<int8_t> &a, const SimpleTensor<int8_t> &b, TensorShape shape_c); -template SimpleTensor<int32_t> gemmlowp(const SimpleTensor<uint8_t> &a, const SimpleTensor<uint8_t> &b, TensorShape shape_c); +template SimpleTensor<int32_t> gemmlowp<int32_t, int8_t, int8_t>(const SimpleTensor<int8_t> &a, const SimpleTensor<int8_t> &b, TensorShape shape_c); +template SimpleTensor<int32_t> gemmlowp<int32_t, uint8_t, uint8_t>(const SimpleTensor<uint8_t> &a, const SimpleTensor<uint8_t> &b, TensorShape shape_c); +template SimpleTensor<int32_t> gemmlowp<int32_t, uint8_t, int8_t>(const SimpleTensor<uint8_t> &a, const SimpleTensor<int8_t> &b, TensorShape shape_c); } // namespace reference } // namespace validation } // namespace test |