commit d42c1f37be18e716dff7705d38e66222d975114c
author Michele Di Giorgio <michele.digiorgio@arm.com> Wed Feb 19 15:55:01 2020 +0000
committer Giuseppe Rossini <giuseppe.rossini@arm.com> Thu Feb 20 10:09:14 2020 +0000
tree 1c0b623a271d8bbeffac64ba81f00d2ab0349989
parent 5979b217ee887c4442e1affa7dc4378a4a642b95

COMPMID-3209: Failing VTS/NN Tests on CpuAcc for avg_pool_quant and mobilenet quant

Rounding-to-nearest is already taken into account by adding 0.5f to the
result, so no need to use vcvtnq.

Change-Id: I2ee78d0abd5d1fb2c7d3133c316cb48d59d2497b
Signed-off-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/2751
Reviewed-by: James Conroy <james.conroy@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>

src/core/NEON/kernels/NEPoolingLayerKernel.cpp

diff --git a/src/core/NEON/kernels/NEPoolingLayerKernel.cpp b/src/core/NEON/kernels/NEPoolingLayerKernel.cpp
index 349e646..326bc77 100644
--- a/src/core/NEON/kernels/NEPoolingLayerKernel.cpp
+++ b/src/core/NEON/kernels/NEPoolingLayerKernel.cpp
@@ -329,21 +329,13 @@
 template <>
 inline uint32x4_t vcvtq_q32_f32(float32x4_t values)
 {
-#ifdef __aarch64__
-    return vcvtnq_u32_f32(values);
-#else  //__aarch64__
     return vcvtq_u32_f32(values);
-#endif //__aarch64__
 }
 
 template <>
 inline int32x4_t vcvtq_q32_f32(float32x4_t values)
 {
-#ifdef __aarch64__
-    return vcvtnq_s32_f32(values);
-#else  //__aarch64__
     return vcvtq_s32_f32(values);
-#endif //__aarch64__
 }
 
 template <typename T>
@@ -1904,10 +1896,10 @@
     const UniformQuantizationInfo input_qinfo  = _input->info()->quantization_info().uniform();
     const UniformQuantizationInfo output_qinfo = _output->info()->quantization_info().uniform();
 
-    const float   quant_rescale = output_qinfo.scale / input_qinfo.scale;
+    const float quant_rescale = output_qinfo.scale / input_qinfo.scale;
     // "new_offset" doesn't have to consider the "half_scale_v" in its computation
     // With a requantization performed in a single step there won't be uncertainties introduced
-    const int32_t new_offset    = output_qinfo.offset - static_cast<int32_t>( static_cast<float>(input_qinfo.offset) / quant_rescale);
+    const int32_t new_offset = output_qinfo.offset - static_cast<int32_t>(static_cast<float>(input_qinfo.offset) / quant_rescale);
 
     const float                   requant_scale  = output_qinfo.scale / input_qinfo.scale;
     const int32_t                 requant_offset = output_qinfo.offset - static_cast<int32_t>(static_cast<float>(input_qinfo.offset) / requant_scale);