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authorGian Marco Iodice <gianmarco.iodice@arm.com>2017-09-28 15:41:37 +0100
committerAnthony Barbier <anthony.barbier@arm.com>2018-11-02 16:35:24 +0000
commit1682430e220eb609752c650f85c0f96e375b6d6a (patch)
tree88db2cf1ad95df696c4477f06b30bac62fccf111 /src
parente1f8f9b976cec4af84e5beee1109912f36096f5c (diff)
downloadComputeLibrary-1682430e220eb609752c650f85c0f96e375b6d6a.tar.gz
COMPMID-463 - Extended Pooling Layer on NEON to support Global Pooling
Change-Id: I8ae44187624deeab3d40d878e7b34ff651f1dad0 Reviewed-on: http://mpd-gerrit.cambridge.arm.com/89834 Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com> Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>
Diffstat (limited to 'src')
-rw-r--r--src/core/NEON/kernels/NEPoolingLayerKernel.cpp143
-rw-r--r--src/runtime/NEON/functions/NEPoolingLayer.cpp27
2 files changed, 160 insertions, 10 deletions
diff --git a/src/core/NEON/kernels/NEPoolingLayerKernel.cpp b/src/core/NEON/kernels/NEPoolingLayerKernel.cpp
index b97564e77b..8d4e46500f 100644
--- a/src/core/NEON/kernels/NEPoolingLayerKernel.cpp
+++ b/src/core/NEON/kernels/NEPoolingLayerKernel.cpp
@@ -108,14 +108,13 @@ void NEPoolingLayerKernel::configure(const ITensor *input, ITensor *output, cons
std::tie(pool_pad_x, pool_pad_y) = pad_stride_info.pad();
std::tie(pool_stride_x, pool_stride_y) = pad_stride_info.stride();
- static const std::set<int> supported_pool_sizes = { 2, 3, 7 };
+ static const std::set<int> supported_pool_sizes = { 2, 3 };
ARM_COMPUTE_UNUSED(supported_pool_sizes);
ARM_COMPUTE_ERROR_ON_NULLPTR(output);
ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QS8, DataType::QS16, DataType::F16, DataType::F32);
ARM_COMPUTE_ERROR_ON(pool_type == PoolingType::L2 && is_data_type_fixed_point(input->info()->data_type()));
- ARM_COMPUTE_ERROR_ON(supported_pool_sizes.find(pool_size) == supported_pool_sizes.end());
- ARM_COMPUTE_ERROR_ON(7 == pool_size && input->info()->data_type() != DataType::F32);
+ 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);
@@ -207,7 +206,7 @@ void NEPoolingLayerKernel::configure(const ITensor *input, ITensor *output, cons
num_elems_read_per_iteration = 8; // We use vload8 for pooling7
break;
default:
- ARM_COMPUTE_ERROR("Pooling size not supported");
+ num_elems_read_per_iteration = 1; // We use vload4 for poolingN but with a leftover for loop
break;
}
num_elems_processed_per_iteration = 1;
@@ -380,7 +379,20 @@ void NEPoolingLayerKernel::configure(const ITensor *input, ITensor *output, cons
}
break;
default:
- ARM_COMPUTE_ERROR("Unsupported pooling size");
+ switch(pool_type)
+ {
+ case PoolingType::AVG:
+ _func = &NEPoolingLayerKernel::poolingN_f32<PoolingType::AVG>;
+ break;
+ case PoolingType::L2:
+ _func = &NEPoolingLayerKernel::poolingN_f32<PoolingType::L2>;
+ break;
+ case PoolingType::MAX:
+ _func = &NEPoolingLayerKernel::poolingN_f32<PoolingType::MAX>;
+ break;
+ default:
+ ARM_COMPUTE_ERROR("Unsupported pooling type!");
+ }
break;
}
@@ -1005,6 +1017,127 @@ void NEPoolingLayerKernel::pooling7_f32(const Window &window_input, const Window
input, output);
}
+template <PoolingType pooling_type>
+void NEPoolingLayerKernel::poolingN_f32(const Window &window_input, const Window &window)
+{
+ Iterator input(_input, window_input);
+ Iterator output(_output, window);
+
+ const int pool_size = _pool_info.pool_size();
+ int pool_pad_x = 0;
+ int pool_pad_y = 0;
+ int pool_stride_x = 0;
+ 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;
+
+ execute_window_loop(window, [&](const Coordinates & id)
+ {
+ float res = 0.0f;
+
+ 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);
+
+ // Perform pooling
+ float32x4_t vres = vdupq_n_f32(0.0f);
+
+ for(int y = 0; y < pool_size; ++y)
+ {
+ int x = 0;
+ for(; x <= (pool_size - 4); x += 4)
+ {
+ const float32x4_t data = vld1q_f32(reinterpret_cast<const float *>(input.ptr() + (x - pool_pad_x) * _input->info()->strides_in_bytes().x() +
+ (y - pool_pad_y) * _input->info()->strides_in_bytes().y()));
+
+ // Get power of 2 in case of l2 pooling and accumulate
+ if(pooling_type == PoolingType::L2)
+ {
+ vres = vmlaq_f32(vres, data, data);
+ }
+ else
+ {
+ vres = vaddq_f32(vres, data);
+ }
+ }
+
+ // Leftover for loop
+ for(; x < pool_size; ++x)
+ {
+ float data = *(reinterpret_cast<const float *>(input.ptr() + (x - pool_pad_x) * _input->info()->strides_in_bytes().x() + (y - pool_pad_y) * _input->info()->strides_in_bytes().y()));
+
+ // Get power of 2 in case of l2 pooling
+ if(pooling_type == PoolingType::L2)
+ {
+ data *= data;
+ }
+
+ res += data;
+ }
+ }
+
+#if defined(__aarch64__)
+ // Reduction operation available on 64 bit architectures only
+ res += vaddvq_f32(vres);
+#else // __aarch64__
+ // Reduction
+ float32x2_t tmp = vpadd_f32(vget_high_f32(vres), vget_low_f32(vres));
+ tmp = vpadd_f32(tmp, tmp);
+
+ res += vget_lane_f32(tmp, 0);
+#endif // __aarch64__
+ // Divide by scale
+ res *= scale;
+ }
+ else
+ {
+ float32x4_t vres = vdupq_n_f32(std::numeric_limits<float>::min());
+ res = std::numeric_limits<float>::min();
+
+ for(int y = 0; y < pool_size; ++y)
+ {
+ int x = 0;
+ for(; x <= (pool_size - 4); x += 4)
+ {
+ const float32x4_t data = vld1q_f32(reinterpret_cast<const float *>(input.ptr() + (x - pool_pad_x) * _input->info()->strides_in_bytes().x() +
+ (y - pool_pad_y) * _input->info()->strides_in_bytes().y()));
+ vres = vmaxq_f32(vres, data);
+ }
+
+ // Leftover for loop
+ for(; x < pool_size; ++x)
+ {
+ const float data = *(reinterpret_cast<const float *>(input.ptr() + (x - pool_pad_x) * _input->info()->strides_in_bytes().x() + (y - pool_pad_y) * _input->info()->strides_in_bytes().y()));
+ res = std::max(res, data);
+ }
+ }
+
+#if defined(__aarch64__)
+ // Reduction operation available on 64 bit architectures only
+ res = std::max(vmaxvq_f32(vres), res);
+#else // __aarch64__
+ float32x2_t tmp = vpmax_f32(vget_high_f32(vres), vget_low_f32(vres));
+ tmp = vpmax_f32(tmp, tmp);
+
+ res = std::max(res, vget_lane_f32(tmp, 0));
+#endif // __aarch64__
+ }
+
+ // Calculate square-root in case of l2 pooling
+ if(pooling_type == PoolingType::L2)
+ {
+ res = std::sqrt(res);
+ }
+
+ // Store result
+ *(reinterpret_cast<float *>(output.ptr())) = res;
+ },
+ input, output);
+}
+
void NEPoolingLayerKernel::run(const Window &window, const ThreadInfo &info)
{
ARM_COMPUTE_UNUSED(info);
diff --git a/src/runtime/NEON/functions/NEPoolingLayer.cpp b/src/runtime/NEON/functions/NEPoolingLayer.cpp
index de04f36961..f8a85b9897 100644
--- a/src/runtime/NEON/functions/NEPoolingLayer.cpp
+++ b/src/runtime/NEON/functions/NEPoolingLayer.cpp
@@ -23,19 +23,36 @@
*/
#include "arm_compute/runtime/NEON/functions/NEPoolingLayer.h"
-#include "arm_compute/core/NEON/kernels/NEPoolingLayerKernel.h"
+#include "arm_compute/core/ITensor.h"
+#include "arm_compute/runtime/NEON/NEScheduler.h"
+
#include "support/ToolchainSupport.h"
using namespace arm_compute;
+NEPoolingLayer::NEPoolingLayer()
+ : _pooling_layer_kernel(), _border_handler(), _is_global_pooling_layer(false)
+{
+}
+
void NEPoolingLayer::configure(ITensor *input, ITensor *output, const PoolingLayerInfo &pool_info)
{
+ // Check if we have Global Pooling Layer
+ _is_global_pooling_layer = (input->info()->dimension(0) == pool_info.pool_size()) && (input->info()->dimension(1) == pool_info.pool_size());
+
// Configure pooling kernel
- auto k = arm_compute::support::cpp14::make_unique<NEPoolingLayerKernel>();
- k->configure(input, output, pool_info);
- _kernel = std::move(k);
+ _pooling_layer_kernel.configure(input, output, pool_info);
// Configure border depending on operation required
BorderMode border_mode = (pool_info.pool_type() == PoolingType::MAX) ? BorderMode::REPLICATE : BorderMode::CONSTANT;
- _border_handler.configure(input, _kernel->border_size(), border_mode, PixelValue(static_cast<float>(0.f)));
+ _border_handler.configure(input, _pooling_layer_kernel.border_size(), border_mode, PixelValue(static_cast<float>(0.f)));
}
+
+void NEPoolingLayer::run()
+{
+ // Fill border
+ NEScheduler::get().schedule(&_border_handler, Window::DimY);
+
+ // Run pooling layer
+ NEScheduler::get().schedule(&_pooling_layer_kernel, _is_global_pooling_layer ? Window::DimZ : Window::DimY);
+} \ No newline at end of file