arm_compute v18.08
diff --git a/tests/validation/reference/PoolingLayer.cpp b/tests/validation/reference/PoolingLayer.cpp
index 6973454..02c430a 100644
--- a/tests/validation/reference/PoolingLayer.cpp
+++ b/tests/validation/reference/PoolingLayer.cpp
@@ -25,7 +25,6 @@
#include "arm_compute/core/Types.h"
#include "arm_compute/core/utils/misc/ShapeCalculator.h"
-#include "tests/validation/FixedPoint.h"
#include "tests/validation/Helpers.h"
namespace arm_compute
@@ -44,7 +43,7 @@
ARM_COMPUTE_ERROR_ON(info.is_global_pooling() && (src.shape().x() != src.shape().y()));
// Create reference
- SimpleTensor<T> dst{ compute_pool_shape(TensorInfo(src.shape(), 1, src.data_type(), src.fixed_point_position()), info), src.data_type(), 1, src.fixed_point_position() };
+ SimpleTensor<T> dst{ compute_pool_shape(TensorInfo(src.shape(), 1, src.data_type()), info), src.data_type(), 1 };
const int pool_size_x = info.is_global_pooling() ? src.shape().x() : info.pool_size().width;
const int pool_size_y = info.is_global_pooling() ? src.shape().y() : info.pool_size().height;
@@ -152,128 +151,6 @@
return dst;
}
-template <typename T, typename std::enable_if<std::is_integral<T>::value, int>::type>
-SimpleTensor<T> pooling_layer(const SimpleTensor<T> &src, const PoolingLayerInfo &info)
-{
- ARM_COMPUTE_ERROR_ON(info.is_global_pooling() && (src.shape().x() != src.shape().y()));
-
- const auto w_src = static_cast<int>(src.shape()[0]);
- const auto h_src = static_cast<int>(src.shape()[1]);
- const int upper_dims = src.shape().total_size() / (w_src * h_src);
-
- const int pool_size_x = info.is_global_pooling() ? src.shape().x() : info.pool_size().width;
- const int pool_size_y = info.is_global_pooling() ? src.shape().y() : info.pool_size().height;
- PoolingType type = info.pool_type();
- int pool_stride_x = info.pad_stride_info().stride().first;
- int pool_stride_y = info.pad_stride_info().stride().second;
- int pad_left = info.pad_stride_info().pad_left();
- int pad_top = info.pad_stride_info().pad_top();
- int pad_right = info.pad_stride_info().pad_right();
- int pad_bottom = info.pad_stride_info().pad_bottom();
- bool exclude_padding = info.exclude_padding();
-
- // Create reference
- SimpleTensor<T> dst{ compute_pool_shape(TensorInfo(src.shape(), 1, src.data_type(), src.fixed_point_position()), info), src.data_type(), 1, src.fixed_point_position() };
-
- const auto w_dst = static_cast<int>(dst.shape()[0]);
- const auto h_dst = static_cast<int>(dst.shape()[1]);
-
- if(type == PoolingType::MAX)
- {
- for(int r = 0; r < upper_dims; ++r)
- {
- for(int h = 0; h < h_dst; ++h)
- {
- for(int w = 0; w < w_dst; ++w)
- {
- 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);
- int hend = std::min(hstart + pool_size_y, h_src);
- wstart = std::max(wstart, 0);
- hstart = std::max(hstart, 0);
-
- T max_val = std::numeric_limits<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];
- if(val > max_val)
- {
- max_val = val;
- }
- }
- }
-
- dst[r * h_dst * w_dst + h * w_dst + w] = max_val;
- }
- }
- }
- }
- else // Average or l2 pooling
- {
- for(int r = 0; r < upper_dims; ++r)
- {
- for(int h = 0; h < h_dst; ++h)
- {
- for(int w = 0; w < w_dst; ++w)
- {
- 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)
- {
- pool = (hend - hstart) * (wend - wstart);
- }
-
- using namespace fixed_point_arithmetic;
-
- const int fixed_point_position = src.fixed_point_position();
- const fixed_point<T> const_1(1, fixed_point_position);
- const fixed_point<T> invpool_fp(1.f / static_cast<float>(pool), fixed_point_position);
- fixed_point<T> avg_val(0, fixed_point_position, true);
-
- if(type == PoolingType::AVG)
- {
- for(int y = hstart; y < hend; ++y)
- {
- for(int x = wstart; x < wend; ++x)
- {
- const fixed_point<T> in_fp(src[r * h_src * w_src + y * w_src + x], fixed_point_position, true);
- avg_val = add(avg_val, in_fp);
- }
- }
- dst[r * h_dst * w_dst + h * w_dst + w] = mul(avg_val, invpool_fp).raw();
- }
- else
- {
- for(int y = hstart; y < hend; ++y)
- {
- for(int x = wstart; x < wend; ++x)
- {
- const fixed_point<T> in_fp(src[r * h_src * w_src + y * w_src + x], fixed_point_position, true);
- avg_val = add(avg_val, mul(in_fp, in_fp));
- }
- }
- auto res = div(const_1, (inv_sqrt(mul(avg_val, invpool_fp))));
- dst[r * h_dst * w_dst + h * w_dst + w] = res.raw();
- }
- }
- }
- }
- }
-
- return dst;
-}
-
template <>
SimpleTensor<uint8_t> pooling_layer<uint8_t>(const SimpleTensor<uint8_t> &src, const PoolingLayerInfo &info)
{
@@ -285,8 +162,6 @@
template SimpleTensor<float> pooling_layer(const SimpleTensor<float> &src, const PoolingLayerInfo &info);
template SimpleTensor<half> pooling_layer(const SimpleTensor<half> &src, const PoolingLayerInfo &info);
-template SimpleTensor<qint8_t> pooling_layer(const SimpleTensor<qint8_t> &src, const PoolingLayerInfo &info);
-template SimpleTensor<qint16_t> pooling_layer(const SimpleTensor<qint16_t> &src, const PoolingLayerInfo &info);
} // namespace reference
} // namespace validation
} // namespace test