COMPMID-647: Exclude padding pixels from averaging factor.
Adds support for excluding the padding pixels from the average scaling
factor calculation.
Change-Id: Ia13fbfeae235aff564db74191613921848231a01
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/93715
Reviewed-by: Robert Hughes <robert.hughes@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>
diff --git a/src/core/NEON/kernels/NEPoolingLayerKernel.cpp b/src/core/NEON/kernels/NEPoolingLayerKernel.cpp
index 0024e33..122540b 100644
--- a/src/core/NEON/kernels/NEPoolingLayerKernel.cpp
+++ b/src/core/NEON/kernels/NEPoolingLayerKernel.cpp
@@ -47,13 +47,19 @@
namespace
{
+template <bool exclude_padding>
inline float calculate_avg_scale(const Coordinates &id, const int pool_size, const int upper_bound_w, const int upper_bound_h,
const int pad_x, const int pad_y, const int stride_x, const int stride_y)
{
- const int start_x = id.x() * stride_x - pad_x;
- const int start_y = id.y() * stride_y - pad_y;
+ int start_x = id.x() * stride_x - pad_x;
+ int start_y = id.y() * stride_y - pad_y;
const int end_x = std::min(start_x + pool_size, upper_bound_w);
const int end_y = std::min(start_y + pool_size, upper_bound_h);
+ if(exclude_padding)
+ {
+ start_x = std::max(0, start_x);
+ start_y = std::max(0, start_y);
+ }
return 1.f / ((end_y - start_y) * (end_x - start_x));
}
@@ -105,6 +111,7 @@
PoolingType pool_type = pool_info.pool_type();
int pool_size = pool_info.pool_size();
const PadStrideInfo pad_stride_info = pool_info.pad_stride_info();
+ bool exclude_padding = pool_info.exclude_padding();
std::tie(pool_pad_x, pool_pad_y) = pad_stride_info.pad();
std::tie(pool_stride_x, pool_stride_y) = pad_stride_info.stride();
@@ -117,6 +124,7 @@
ARM_COMPUTE_ERROR_ON((supported_pool_sizes.find(pool_size) == supported_pool_sizes.end()) && (input->info()->data_type() != DataType::F32));
ARM_COMPUTE_ERROR_ON(pool_pad_x >= pool_size || pool_pad_y >= pool_size);
ARM_COMPUTE_ERROR_ON(is_data_type_fixed_point(input->info()->data_type()) && pool_stride_x > 2);
+ ARM_COMPUTE_ERROR_ON(exclude_padding && is_data_type_fixed_point(input->info()->data_type()));
// Check output dimensions
std::tie(pooled_w, pooled_h) = scaled_dimensions(input->info()->dimension(0), input->info()->dimension(1),
@@ -268,13 +276,13 @@
switch(pool_type)
{
case PoolingType::AVG:
- _func = &NEPoolingLayerKernel::pooling2_f16<PoolingType::AVG>;
+ _func = (exclude_padding) ? &NEPoolingLayerKernel::pooling2_f16<PoolingType::AVG, true> : &NEPoolingLayerKernel::pooling2_f16<PoolingType::AVG, false>;
break;
case PoolingType::L2:
- _func = &NEPoolingLayerKernel::pooling2_f16<PoolingType::L2>;
+ _func = (exclude_padding) ? &NEPoolingLayerKernel::pooling2_f16<PoolingType::L2, true> : &NEPoolingLayerKernel::pooling2_f16<PoolingType::L2, false>;
break;
case PoolingType::MAX:
- _func = &NEPoolingLayerKernel::pooling2_f16<PoolingType::MAX>;
+ _func = &NEPoolingLayerKernel::pooling2_f16<PoolingType::MAX, false>;
break;
default:
ARM_COMPUTE_ERROR("Unsupported pooling type!");
@@ -285,13 +293,13 @@
switch(pool_type)
{
case PoolingType::AVG:
- _func = &NEPoolingLayerKernel::pooling2_f32<PoolingType::AVG>;
+ _func = (exclude_padding) ? &NEPoolingLayerKernel::pooling2_f32<PoolingType::AVG, true> : &NEPoolingLayerKernel::pooling2_f32<PoolingType::AVG, false>;
break;
case PoolingType::L2:
- _func = &NEPoolingLayerKernel::pooling2_f32<PoolingType::L2>;
+ _func = (exclude_padding) ? &NEPoolingLayerKernel::pooling2_f32<PoolingType::L2, true> : &NEPoolingLayerKernel::pooling2_f32<PoolingType::L2, false>;
break;
case PoolingType::MAX:
- _func = &NEPoolingLayerKernel::pooling2_f32<PoolingType::MAX>;
+ _func = &NEPoolingLayerKernel::pooling2_f32<PoolingType::MAX, false>;
break;
default:
ARM_COMPUTE_ERROR("Unsupported pooling type!");
@@ -332,13 +340,13 @@
switch(pool_type)
{
case PoolingType::AVG:
- _func = &NEPoolingLayerKernel::pooling3_f16<PoolingType::AVG>;
+ _func = (exclude_padding) ? &NEPoolingLayerKernel::pooling3_f16<PoolingType::AVG, true> : &NEPoolingLayerKernel::pooling3_f16<PoolingType::AVG, false>;
break;
case PoolingType::L2:
- _func = &NEPoolingLayerKernel::pooling3_f16<PoolingType::L2>;
+ _func = (exclude_padding) ? &NEPoolingLayerKernel::pooling3_f16<PoolingType::L2, true> : &NEPoolingLayerKernel::pooling3_f16<PoolingType::L2, false>;
break;
case PoolingType::MAX:
- _func = &NEPoolingLayerKernel::pooling3_f16<PoolingType::MAX>;
+ _func = &NEPoolingLayerKernel::pooling3_f16<PoolingType::MAX, false>;
break;
default:
ARM_COMPUTE_ERROR("Unsupported pooling type!");
@@ -349,13 +357,13 @@
switch(pool_type)
{
case PoolingType::AVG:
- _func = &NEPoolingLayerKernel::pooling3_f32<PoolingType::AVG>;
+ _func = (exclude_padding) ? &NEPoolingLayerKernel::pooling3_f32<PoolingType::AVG, true> : &NEPoolingLayerKernel::pooling3_f32<PoolingType::AVG, false>;
break;
case PoolingType::L2:
- _func = &NEPoolingLayerKernel::pooling3_f32<PoolingType::L2>;
+ _func = (exclude_padding) ? &NEPoolingLayerKernel::pooling3_f32<PoolingType::L2, true> : &NEPoolingLayerKernel::pooling3_f32<PoolingType::L2, false>;
break;
case PoolingType::MAX:
- _func = &NEPoolingLayerKernel::pooling3_f32<PoolingType::MAX>;
+ _func = &NEPoolingLayerKernel::pooling3_f32<PoolingType::MAX, false>;
break;
default:
ARM_COMPUTE_ERROR("Unsupported pooling type!");
@@ -366,13 +374,13 @@
switch(pool_type)
{
case PoolingType::AVG:
- _func = &NEPoolingLayerKernel::pooling7_f32<PoolingType::AVG>;
+ _func = (exclude_padding) ? &NEPoolingLayerKernel::pooling7_f32<PoolingType::AVG, true> : &NEPoolingLayerKernel::pooling7_f32<PoolingType::AVG, false>;
break;
case PoolingType::L2:
- _func = &NEPoolingLayerKernel::pooling7_f32<PoolingType::L2>;
+ _func = (exclude_padding) ? &NEPoolingLayerKernel::pooling7_f32<PoolingType::L2, true> : &NEPoolingLayerKernel::pooling7_f32<PoolingType::L2, false>;
break;
case PoolingType::MAX:
- _func = &NEPoolingLayerKernel::pooling7_f32<PoolingType::MAX>;
+ _func = &NEPoolingLayerKernel::pooling7_f32<PoolingType::MAX, false>;
break;
default:
ARM_COMPUTE_ERROR("Unsupported pooling type!");
@@ -382,13 +390,13 @@
switch(pool_type)
{
case PoolingType::AVG:
- _func = &NEPoolingLayerKernel::poolingN_f32<PoolingType::AVG>;
+ _func = (exclude_padding) ? &NEPoolingLayerKernel::poolingN_f32<PoolingType::AVG, true> : &NEPoolingLayerKernel::poolingN_f32<PoolingType::AVG, false>;
break;
case PoolingType::L2:
- _func = &NEPoolingLayerKernel::poolingN_f32<PoolingType::L2>;
+ _func = (exclude_padding) ? &NEPoolingLayerKernel::poolingN_f32<PoolingType::L2, true> : &NEPoolingLayerKernel::poolingN_f32<PoolingType::L2, false>;
break;
case PoolingType::MAX:
- _func = &NEPoolingLayerKernel::poolingN_f32<PoolingType::MAX>;
+ _func = &NEPoolingLayerKernel::poolingN_f32<PoolingType::MAX, false>;
break;
default:
ARM_COMPUTE_ERROR("Unsupported pooling type!");
@@ -533,7 +541,7 @@
input, output);
}
-template <PoolingType pooling_type>
+template <PoolingType pooling_type, bool exclude_padding>
void NEPoolingLayerKernel::pooling3_f16(const Window &window_input, const Window &window)
{
#ifdef ARM_COMPUTE_AARCH64_V8_2
@@ -547,8 +555,8 @@
int pool_stride_y = 0;
std::tie(pool_pad_x, pool_pad_y) = _pool_info.pad_stride_info().pad();
std::tie(pool_stride_x, pool_stride_y) = _pool_info.pad_stride_info().stride();
- const int upper_bound_w = _input->info()->dimension(0) + pool_pad_x;
- const int upper_bound_h = _input->info()->dimension(1) + pool_pad_y;
+ const int upper_bound_w = _input->info()->dimension(0) + (exclude_padding ? 0 : pool_pad_x);
+ const int upper_bound_h = _input->info()->dimension(1) + (exclude_padding ? 0 : pool_pad_y);
const unsigned char *const input_top_ptr = _input->ptr_to_element(Coordinates(-static_cast<int>(pool_pad_x), -static_cast<int>(pool_pad_y)));
const unsigned char *const input_middle_ptr = _input->ptr_to_element(Coordinates(-static_cast<int>(pool_pad_x), -static_cast<int>(pool_pad_y) + 1));
@@ -572,7 +580,7 @@
if(pooling_type != PoolingType::MAX)
{
// Calculate scale
- const float scale = calculate_avg_scale(id, pool_size, upper_bound_w, upper_bound_h, pool_pad_x, pool_pad_y, pool_stride_x, pool_stride_y);
+ const float scale = calculate_avg_scale<exclude_padding>(id, pool_size, upper_bound_w, upper_bound_h, pool_pad_x, pool_pad_y, pool_stride_x, pool_stride_y);
const float16x4_t scale_v = vdup_n_f16(scale);
// Perform pooling
const float16x4_t sum_data = vadd_f16(vadd_f16(top_data, bottom_data), middle_data);
@@ -602,7 +610,7 @@
#endif /* ARM_COMPUTE_AARCH64_V8_2 */
}
-template <PoolingType pooling_type>
+template <PoolingType pooling_type, bool exclude_padding>
void NEPoolingLayerKernel::pooling2_f16(const Window &window_input, const Window &window)
{
#ifdef ARM_COMPUTE_AARCH64_V8_2
@@ -612,8 +620,8 @@
int pool_pad_x, pool_pad_y, pool_stride_x, pool_stride_y = 0;
std::tie(pool_pad_x, pool_pad_y) = _pool_info.pad_stride_info().pad();
std::tie(pool_stride_x, pool_stride_y) = _pool_info.pad_stride_info().stride();
- const int upper_bound_w = _input->info()->dimension(0) + pool_pad_x;
- const int upper_bound_h = _input->info()->dimension(1) + pool_pad_y;
+ const int upper_bound_w = _input->info()->dimension(0) + (exclude_padding ? 0 : pool_pad_x);
+ const int upper_bound_h = _input->info()->dimension(1) + (exclude_padding ? 0 : pool_pad_y);
const unsigned char *const input_top_ptr = _input->ptr_to_element(Coordinates(-static_cast<int>(pool_pad_x), -static_cast<int>(pool_pad_y)));
const unsigned char *const input_bottom_ptr = _input->ptr_to_element(Coordinates(-static_cast<int>(pool_pad_x), -static_cast<int>(pool_pad_y) + 1));
@@ -635,7 +643,7 @@
if(pooling_type != PoolingType::MAX)
{
- const float scale = calculate_avg_scale(id, pool_size, upper_bound_w, upper_bound_h, pool_pad_x, pool_pad_y, pool_stride_x, pool_stride_y);
+ const float scale = calculate_avg_scale<exclude_padding>(id, pool_size, upper_bound_w, upper_bound_h, pool_pad_x, pool_pad_y, pool_stride_x, pool_stride_y);
const float16x8_t scale_v = vdupq_n_f16(scale);
res = vmulq_f16(scale_v, vaddq_f16(bottom_data.val[1], vaddq_f16(bottom_data.val[0], vaddq_f16(top_data.val[0], top_data.val[1]))));
}
@@ -661,7 +669,7 @@
#endif /* ARM_COMPUTE_AARCH64_V8_2 */
}
-template <PoolingType pooling_type>
+template <PoolingType pooling_type, bool exclude_padding>
void NEPoolingLayerKernel::pooling2_f32(const Window &window_input, const Window &window)
{
Iterator input(_input, window_input);
@@ -674,8 +682,8 @@
int pool_stride_y = 0;
std::tie(pool_pad_x, pool_pad_y) = _pool_info.pad_stride_info().pad();
std::tie(pool_stride_x, pool_stride_y) = _pool_info.pad_stride_info().stride();
- const int upper_bound_w = _input->info()->dimension(0) + pool_pad_x;
- const int upper_bound_h = _input->info()->dimension(1) + pool_pad_y;
+ const int upper_bound_w = _input->info()->dimension(0) + (exclude_padding ? 0 : pool_pad_x);
+ const int upper_bound_h = _input->info()->dimension(1) + (exclude_padding ? 0 : pool_pad_y);
const uint8_t *const input_top_ptr = _input->ptr_to_element(Coordinates(-static_cast<int>(pool_pad_x), -static_cast<int>(pool_pad_y)));
const uint8_t *const input_bottom_ptr = _input->ptr_to_element(Coordinates(-static_cast<int>(pool_pad_x), -static_cast<int>(pool_pad_y) + 1));
@@ -697,7 +705,7 @@
if(pooling_type != PoolingType::MAX)
{
// Calculate scale
- float scale = calculate_avg_scale(id, pool_size, upper_bound_w, upper_bound_h, pool_pad_x, pool_pad_y, pool_stride_x, pool_stride_y);
+ float scale = calculate_avg_scale<exclude_padding>(id, pool_size, upper_bound_w, upper_bound_h, pool_pad_x, pool_pad_y, pool_stride_x, pool_stride_y);
const float32x2_t scale_v = vdup_n_f32(scale);
// Perform pooling
@@ -868,7 +876,7 @@
input, output);
}
-template <PoolingType pooling_type>
+template <PoolingType pooling_type, bool exclude_padding>
void NEPoolingLayerKernel::pooling3_f32(const Window &window_input, const Window &window)
{
Iterator input(_input, window_input);
@@ -881,8 +889,8 @@
int pool_stride_y = 0;
std::tie(pool_pad_x, pool_pad_y) = _pool_info.pad_stride_info().pad();
std::tie(pool_stride_x, pool_stride_y) = _pool_info.pad_stride_info().stride();
- const int upper_bound_w = _input->info()->dimension(0) + pool_pad_x;
- const int upper_bound_h = _input->info()->dimension(1) + pool_pad_y;
+ const int upper_bound_w = _input->info()->dimension(0) + (exclude_padding ? 0 : pool_pad_x);
+ const int upper_bound_h = _input->info()->dimension(1) + (exclude_padding ? 0 : pool_pad_y);
const uint8_t *const input_top_ptr = _input->ptr_to_element(Coordinates(-static_cast<int>(pool_pad_x), -static_cast<int>(pool_pad_y)));
const uint8_t *const input_middle_ptr = _input->ptr_to_element(Coordinates(-static_cast<int>(pool_pad_x), -static_cast<int>(pool_pad_y) + 1));
@@ -907,7 +915,7 @@
if(pooling_type != PoolingType::MAX)
{
// Calculate scale
- float scale = calculate_avg_scale(id, pool_size, upper_bound_w, upper_bound_h, pool_pad_x, pool_pad_y, pool_stride_x, pool_stride_y);
+ float scale = calculate_avg_scale<exclude_padding>(id, pool_size, upper_bound_w, upper_bound_h, pool_pad_x, pool_pad_y, pool_stride_x, pool_stride_y);
const float32x2_t scale_v = vdup_n_f32(scale);
// Perform pooling
@@ -935,7 +943,7 @@
input, output);
}
-template <PoolingType pooling_type>
+template <PoolingType pooling_type, bool exclude_padding>
void NEPoolingLayerKernel::pooling7_f32(const Window &window_input, const Window &window)
{
Iterator input(_input, window_input);
@@ -948,8 +956,8 @@
int pool_stride_y = 0;
std::tie(pool_pad_x, pool_pad_y) = _pool_info.pad_stride_info().pad();
std::tie(pool_stride_x, pool_stride_y) = _pool_info.pad_stride_info().stride();
- const int upper_bound_w = _input->info()->dimension(0) + pool_pad_x;
- const int upper_bound_h = _input->info()->dimension(1) + pool_pad_y;
+ const int upper_bound_w = _input->info()->dimension(0) + (exclude_padding ? 0 : pool_pad_x);
+ const int upper_bound_h = _input->info()->dimension(1) + (exclude_padding ? 0 : pool_pad_y);
std::array<const uint8_t *, pool_size> input_ptrs{ {} };
for(int i = 0; i < pool_size; ++i)
@@ -964,7 +972,7 @@
if(pooling_type != PoolingType::MAX)
{
// Calculate scale
- float scale = calculate_avg_scale(id, pool_size, upper_bound_w, upper_bound_h, pool_pad_x, pool_pad_y, pool_stride_x, pool_stride_y);
+ float scale = calculate_avg_scale<exclude_padding>(id, pool_size, upper_bound_w, upper_bound_h, pool_pad_x, pool_pad_y, pool_stride_x, pool_stride_y);
const float32x2_t scale_v = vdup_n_f32(scale);
// Perform pooling
@@ -1017,7 +1025,7 @@
input, output);
}
-template <PoolingType pooling_type>
+template <PoolingType pooling_type, bool exclude_padding>
void NEPoolingLayerKernel::poolingN_f32(const Window &window_input, const Window &window)
{
Iterator input(_input, window_input);
@@ -1030,8 +1038,8 @@
int pool_stride_y = 0;
std::tie(pool_pad_x, pool_pad_y) = _pool_info.pad_stride_info().pad();
std::tie(pool_stride_x, pool_stride_y) = _pool_info.pad_stride_info().stride();
- const int upper_bound_w = _input->info()->dimension(0) + pool_pad_x;
- const int upper_bound_h = _input->info()->dimension(1) + pool_pad_y;
+ const int upper_bound_w = _input->info()->dimension(0) + (exclude_padding ? 0 : pool_pad_x);
+ const int upper_bound_h = _input->info()->dimension(1) + (exclude_padding ? 0 : pool_pad_y);
execute_window_loop(window, [&](const Coordinates & id)
{
@@ -1040,7 +1048,7 @@
if(pooling_type != PoolingType::MAX)
{
// Calculate scale
- const float scale = calculate_avg_scale(id, pool_size, upper_bound_w, upper_bound_h, pool_pad_x, pool_pad_y, pool_stride_x, pool_stride_y);
+ const float scale = calculate_avg_scale<exclude_padding>(id, pool_size, upper_bound_w, upper_bound_h, pool_pad_x, pool_pad_y, pool_stride_x, pool_stride_y);
// Perform pooling
float32x4_t vres = vdupq_n_f32(0.0f);