diff options
Diffstat (limited to 'tests/validation/reference/PoolingLayer.cpp')
| -rw-r--r-- | tests/validation/reference/PoolingLayer.cpp | 60 |
1 files changed, 40 insertions, 20 deletions
diff --git a/tests/validation/reference/PoolingLayer.cpp b/tests/validation/reference/PoolingLayer.cpp index 34b19ffb4f..010412c92b 100644 --- a/tests/validation/reference/PoolingLayer.cpp +++ b/tests/validation/reference/PoolingLayer.cpp @@ -37,8 +37,8 @@ namespace reference { using namespace arm_compute::misc::shape_calculator; -template <typename T> -SimpleTensor<T> pooling_layer(const SimpleTensor<T> &src, const PoolingLayerInfo &info, const QuantizationInfo &output_qinfo) +template <typename T, typename ACC_T, typename std::enable_if<is_floating_point<T>::value, int>::type> +SimpleTensor<T> pooling_layer_internal(const SimpleTensor<T> &src, const PoolingLayerInfo &info, const QuantizationInfo &output_qinfo) { ARM_COMPUTE_UNUSED(output_qinfo); // requantization occurs in pooling_layer<uint8_t> ARM_COMPUTE_ERROR_ON(info.is_global_pooling() && (src.shape().x() != src.shape().y())); @@ -79,12 +79,12 @@ SimpleTensor<T> pooling_layer(const SimpleTensor<T> &src, const PoolingLayerInfo wstart = std::max(wstart, 0); hstart = std::max(hstart, 0); - T max_val = std::numeric_limits<T>::lowest(); + auto max_val = std::numeric_limits<ACC_T>::lowest(); for(int y = hstart; y < hend; ++y) { for(int x = wstart; x < wend; ++x) { - const T val = src[r * h_src * w_src + y * w_src + x]; + const auto val = static_cast<ACC_T>(src[r * h_src * w_src + y * w_src + x]); if(val > max_val) { max_val = val; @@ -92,7 +92,7 @@ SimpleTensor<T> pooling_layer(const SimpleTensor<T> &src, const PoolingLayerInfo } } - dst[r * h_dst * w_dst + h * w_dst + w] = max_val; + dst[r * h_dst * w_dst + h * w_dst + w] = static_cast<T>(max_val); } } } @@ -105,16 +105,16 @@ SimpleTensor<T> pooling_layer(const SimpleTensor<T> &src, const PoolingLayerInfo { for(int w = 0; w < w_dst; ++w) { - T avg_val(0); - int wstart = w * pool_stride_x - pad_left; - int hstart = h * pool_stride_y - pad_top; - int wend = std::min(wstart + pool_size_x, w_src + pad_right); - int hend = std::min(hstart + pool_size_y, h_src + pad_bottom); - int pool = (hend - hstart) * (wend - wstart); - wstart = std::max(wstart, 0); - hstart = std::max(hstart, 0); - wend = std::min(wend, w_src); - hend = std::min(hend, h_src); + ACC_T avg_val(0); + int wstart = w * pool_stride_x - pad_left; + int hstart = h * pool_stride_y - pad_top; + int wend = std::min(wstart + pool_size_x, w_src + pad_right); + int hend = std::min(hstart + pool_size_y, h_src + pad_bottom); + int pool = (hend - hstart) * (wend - wstart); + wstart = std::max(wstart, 0); + hstart = std::max(hstart, 0); + wend = std::min(wend, w_src); + hend = std::min(hend, h_src); // Exclude padding pixels from the average if(exclude_padding) { @@ -127,7 +127,7 @@ SimpleTensor<T> pooling_layer(const SimpleTensor<T> &src, const PoolingLayerInfo { for(int x = wstart; x < wend; ++x) { - avg_val += src[r * h_src * w_src + y * w_src + x]; + avg_val += static_cast<ACC_T>(src[r * h_src * w_src + y * w_src + x]); } } dst[r * h_dst * w_dst + h * w_dst + w] = avg_val / pool; @@ -138,11 +138,11 @@ SimpleTensor<T> pooling_layer(const SimpleTensor<T> &src, const PoolingLayerInfo { for(int x = wstart; x < wend; ++x) { - const T val = src[r * h_src * w_src + y * w_src + x]; + const auto val = static_cast<ACC_T>(src[r * h_src * w_src + y * w_src + x]); avg_val += val * val; } } - dst[r * h_dst * w_dst + h * w_dst + w] = std::sqrt(avg_val / pool); + dst[r * h_dst * w_dst + h * w_dst + w] = static_cast<T>(std::sqrt(avg_val / pool)); } } } @@ -152,17 +152,37 @@ SimpleTensor<T> pooling_layer(const SimpleTensor<T> &src, const PoolingLayerInfo return dst; } +template SimpleTensor<float> pooling_layer_internal<float>(const SimpleTensor<float> &src, const PoolingLayerInfo &info, const QuantizationInfo &output_qinfo); +template SimpleTensor<half> pooling_layer_internal<half>(const SimpleTensor<half> &src, const PoolingLayerInfo &info, const QuantizationInfo &output_qinfo); +template SimpleTensor<half> pooling_layer_internal<half, float>(const SimpleTensor<half> &src, const PoolingLayerInfo &info, const QuantizationInfo &output_qinfo); + +template <typename T> +SimpleTensor<T> pooling_layer(const SimpleTensor<T> &src, const PoolingLayerInfo &info, const QuantizationInfo &output_qinfo) +{ + return pooling_layer_internal<T, T>(src, info, output_qinfo); +} + template <> SimpleTensor<uint8_t> pooling_layer<uint8_t>(const SimpleTensor<uint8_t> &src, const PoolingLayerInfo &info, const QuantizationInfo &output_qinfo) { SimpleTensor<float> src_tmp = convert_from_asymmetric(src); - SimpleTensor<float> dst_tmp = pooling_layer<float>(src_tmp, info, output_qinfo); + SimpleTensor<float> dst_tmp = pooling_layer_internal<float>(src_tmp, info, output_qinfo); SimpleTensor<uint8_t> dst = convert_to_asymmetric<uint8_t>(dst_tmp, output_qinfo); return dst; } +template <> +SimpleTensor<half> pooling_layer(const SimpleTensor<half> &src, const PoolingLayerInfo &info, const QuantizationInfo &output_qinfo) +{ + if(src.data_type() == DataType::F16 && info.fp_mixed_precision()) + { + return pooling_layer_internal<half, float>(src, info, output_qinfo); + } + + return pooling_layer_internal<half>(src, info, output_qinfo); +} + template SimpleTensor<float> pooling_layer(const SimpleTensor<float> &src, const PoolingLayerInfo &info, const QuantizationInfo &output_qinfo); -template SimpleTensor<half> pooling_layer(const SimpleTensor<half> &src, const PoolingLayerInfo &info, const QuantizationInfo &output_qinfo); } // namespace reference } // namespace validation } // namespace test |