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| author | Kevin Cheng <kevin.cheng@arm.com> | 2020-10-19 12:35:05 -0700 |
|---|---|---|
| committer | Kevin Cheng <kevin.cheng@arm.com> | 2020-10-19 12:35:05 -0700 |
| commit | 99bea145a050e12f1b5f8301979713d9a9b04e12 (patch) | |
| tree | bc53dd8cf4566c22b75404dd5cc4ffb849b358d8 /reference_model/src/ops | |
| parent | e5e2676409a936431f87d31fb74d825257b20804 (diff) | |
| download | reference_model-99bea145a050e12f1b5f8301979713d9a9b04e12.tar.gz | |
Update apply_scale_32()
Signed-off-by: Kevin Cheng <kevin.cheng@arm.com>
Change-Id: Ida8e3a17d74e5d6379b2244896ddf9e295d0ecc9
Diffstat (limited to 'reference_model/src/ops')
| -rw-r--r-- | reference_model/src/ops/tensor_ops.cc | 4 | ||||
| -rw-r--r-- | reference_model/src/ops/type_conversion.cc | 6 |
2 files changed, 5 insertions, 5 deletions
diff --git a/reference_model/src/ops/tensor_ops.cc b/reference_model/src/ops/tensor_ops.cc index a735334..82ce3d2 100644 --- a/reference_model/src/ops/tensor_ops.cc +++ b/reference_model/src/ops/tensor_ops.cc @@ -268,9 +268,9 @@ int OpAvgPool2d<Dtype>::eval() { this->out->getTensor() = sum.binaryExpr(div_map, [](AccEigenType value, int32_t div) -> OutEigenType { int32_t multiplier, shift; - TosaReference::QuantUtil<AccDtype>::reciprocal_scale(div, multiplier, shift); + TosaReference::QuantUtil::reciprocal_scale(div, multiplier, shift); - return (OutEigenType)TosaReference::QuantUtil<AccDtype>::apply_scale(value, multiplier, shift, false); + return (OutEigenType)TosaReference::QuantUtil::apply_scale_32(value, multiplier, shift, false); }); this->out->getTensor() = this->out->getTensor() + (OutEigenType)(this->qinfo->output_zp()); this->out->getTensor() = this->out->getTensor().cwiseMax((OutEigenType)QMin); diff --git a/reference_model/src/ops/type_conversion.cc b/reference_model/src/ops/type_conversion.cc index 61a19f4..a97bc0d 100644 --- a/reference_model/src/ops/type_conversion.cc +++ b/reference_model/src/ops/type_conversion.cc @@ -130,7 +130,7 @@ int OpRescale<Rank, InDtype, OutDtype>::eval() curr_channel_slice_prescaled.unaryExpr([input_zp, output_zp, channel_multiplier, channel_shift, double_round](InEigenType in_val) -> OutEigenType { InEigenType input_zp_shifted = in_val - (InEigenType)input_zp; - int32_t scaled = TosaReference::QuantUtil<InDtype>::apply_scale( + int32_t scaled = TosaReference::QuantUtil::apply_scale_32( input_zp_shifted, channel_multiplier, channel_shift, double_round); OutEigenType out_val = (OutEigenType)(scaled + output_zp); out_val = std::max<OutEigenType>(out_val, QMin); @@ -151,8 +151,8 @@ int OpRescale<Rank, InDtype, OutDtype>::eval() output_2d = input_reshaped.unaryExpr( [input_zp, output_zp, tensor_multiplier, tensor_shift, double_round](InEigenType in_val) -> OutEigenType { InEigenType input_zp_shifted = in_val - (InEigenType)input_zp; - int32_t scaled = TosaReference::QuantUtil<InDtype>::apply_scale(input_zp_shifted, tensor_multiplier, - tensor_shift, double_round); + int32_t scaled = TosaReference::QuantUtil::apply_scale_32(input_zp_shifted, tensor_multiplier, + tensor_shift, double_round); OutEigenType out_val = (OutEigenType)(scaled + output_zp); out_val = std::max<OutEigenType>(out_val, QMin); out_val = std::min<OutEigenType>(out_val, QMax); |