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-rw-r--r--src/cpu/kernels/pool2d/neon/nchw/all.cpp396
1 files changed, 1 insertions, 395 deletions
diff --git a/src/cpu/kernels/pool2d/neon/nchw/all.cpp b/src/cpu/kernels/pool2d/neon/nchw/all.cpp
index ee4a67b0fb..0602bea667 100644
--- a/src/cpu/kernels/pool2d/neon/nchw/all.cpp
+++ b/src/cpu/kernels/pool2d/neon/nchw/all.cpp
@@ -28,6 +28,7 @@
#include "src/core/helpers/WindowHelpers.h"
#include "src/core/NEON/wrapper/intrinsics/intrinsics.h"
+#include "src/cpu/kernels/pool2d/neon/impl.h"
#include "src/cpu/kernels/pool2d/neon/list.h"
#include <limits>
@@ -60,401 +61,6 @@ read_8_boundary_aware(int height, int width, int pad_left, int pad_top, int x, i
return vec;
}
-#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
-
-float16x4_t
-read_4_boundary_aware_fp16(int srcw, int srch, int pad_l, int pad_t, int x, int y, const float16_t *ptr, float16_t fval)
-{
- float16_t vec[4];
- const bool row_in_bounds((y >= pad_t) && (y < (srch + pad_t)));
- for (int i = 0; i < 4; i++)
- {
- if (row_in_bounds && (x + i >= pad_l) && (x + i < (srcw + pad_l)))
- {
- vec[i] = *(ptr + i);
- }
- else
- {
- vec[i] = fval;
- }
- }
- return wrapper::vload(vec);
-}
-
-void pooling3_fp16_neon_nchw(const ITensor *src,
- ITensor *dst0,
- ITensor *dst1,
- PoolingLayerInfo &pool_info,
- const Window &window_src,
- const Window &window)
-{
- ARM_COMPUTE_UNUSED(dst1);
-
- Iterator in(src, window_src);
- Iterator out(dst0, window);
-
- constexpr const int pool_size = 3;
- const int pool_pad_right = pool_info.pad_stride_info.pad_right();
- const int pool_pad_top = pool_info.pad_stride_info.pad_top();
- const int pool_pad_left = pool_info.pad_stride_info.pad_left();
- const int pool_pad_bottom = pool_info.pad_stride_info.pad_bottom();
- int pool_stride_x = 0;
- int pool_stride_y = 0;
- std::tie(pool_stride_x, pool_stride_y) = pool_info.pad_stride_info.stride();
- const int src_w = src->info()->dimension(0);
- const int src_h = src->info()->dimension(1);
- const int upper_bound_w = src_w + (pool_info.exclude_padding ? 0 : pool_pad_right);
- const int upper_bound_h = src_h + (pool_info.exclude_padding ? 0 : pool_pad_bottom);
- const float16_t fp16_min = get_initial_min<half_float::half>(pool_info.use_inf_as_limit);
- const float16_t fill_value = (pool_info.pool_type == PoolingType::MAX) ? fp16_min : 0.f;
- const unsigned char *const src_top_ptr =
- src->ptr_to_element(Coordinates(-static_cast<int>(pool_pad_left), -static_cast<int>(pool_pad_top)));
- const unsigned char *const src_middle_ptr =
- src->ptr_to_element(Coordinates(-static_cast<int>(pool_pad_left), -static_cast<int>(pool_pad_top) + 1));
- const unsigned char *const src_bottom_ptr =
- src->ptr_to_element(Coordinates(-static_cast<int>(pool_pad_left), -static_cast<int>(pool_pad_top) + 2));
-
- execute_window_loop(
- window,
- [&](const Coordinates &id)
- {
- const auto x_val = id.x() * pool_stride_x;
- const auto y_val_0 = id.y() * pool_stride_y;
- const auto y_val_1 = (id.y() * pool_stride_y) + 1;
- const auto y_val_2 = (id.y() * pool_stride_y) + 2;
- float16x4_t top_data =
- read_4_boundary_aware_fp16(src_w, src_h, pool_pad_left, pool_pad_top, x_val, y_val_0,
- reinterpret_cast<const float16_t *>(src_top_ptr + in.offset()), fill_value);
- float16x4_t middle_data = read_4_boundary_aware_fp16(
- src_w, src_h, pool_pad_left, pool_pad_top, x_val, y_val_1,
- reinterpret_cast<const float16_t *>(src_middle_ptr + in.offset()), fill_value);
- float16x4_t bottom_data = read_4_boundary_aware_fp16(
- src_w, src_h, pool_pad_left, pool_pad_top, x_val, y_val_2,
- reinterpret_cast<const float16_t *>(src_bottom_ptr + in.offset()), fill_value);
- float16x4_t res = {};
-
- // Get power of 2 in case of l2 pooling
- if (pool_info.pool_type == PoolingType::L2)
- {
- top_data = vmul_f16(top_data, top_data);
- middle_data = vmul_f16(middle_data, middle_data);
- bottom_data = vmul_f16(bottom_data, bottom_data);
- }
-
- if (pool_info.pool_type != PoolingType::MAX)
- {
- // Calculate scale
- const float scale = calculate_avg_scale_pool2d(
- pool_info.exclude_padding, DataLayout::NCHW, id, pool_size, pool_size, upper_bound_w, upper_bound_h,
- pool_pad_left, pool_pad_top, 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);
- res = vpadd_f16(vset_lane_f16(0.f, sum_data, 3), sum_data);
- res = vmul_f16(vpadd_f16(res, res), scale_v);
- }
- else
- {
- const float16x4_t max_data = vmax_f16(vmax_f16(top_data, bottom_data), middle_data);
- res = vpmax_f16(vset_lane_f16(fp16_min, max_data, 3), max_data);
- res = vpmax_f16(res, res);
- }
-
- // Calculate square-root in case of l2 pooling
- if (pool_info.pool_type == PoolingType::L2)
- {
- res = vsqrt_f16(res);
- }
-
- *(reinterpret_cast<float16_t *>(out.ptr())) = vget_lane_f16(res, 0);
- },
- in, out);
-}
-
-template <typename T>
-inline typename std::enable_if<std::is_same<T, float16_t>::value, float32x2_t>::type f16_to_f32(float16x4_t in)
-{
- float32x2_t out = {static_cast<float>(vget_lane_f16(in, 0)), static_cast<float>(vget_lane_f16(in, 1))};
- return out;
-}
-#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
-
-template <typename T>
-inline typename std::enable_if<std::is_same<T, float>::value, float32x2_t>::type f16_to_f32(float32x2_t in)
-{
- return in;
-}
-
-template <typename T>
-auto read_2_boundary_aware(int srcw, int srch, int pad_l, int pad_t, int x, int y, const T *ptr, T fval)
-{
- T vec[2];
- const bool row_in_bounds((y >= pad_t) && (y < (srch + pad_t)));
- for (int i = 0; i < 2; i++)
- {
- if (row_in_bounds && (x + i >= pad_l) && (x + i < (srcw + pad_l)))
- {
- vec[i] = *(ptr + i);
- }
- else
- {
- vec[i] = fval;
- }
- }
- return wrapper::vload(vec);
-}
-
-template <typename T>
-void pooling2_nchw_maxpool_indices(const ITensor *src,
- ITensor *dst0,
- ITensor *dst1,
- PoolingLayerInfo &pool_info,
- const Window &window_src,
- const Window &window)
-{
- Iterator in(src, window_src);
- Iterator out(dst0, window);
- Iterator indices(dst1, window);
- const int pool_pad_top = pool_info.pad_stride_info.pad_top();
- const int pool_pad_left = pool_info.pad_stride_info.pad_left();
- int pool_stride_x = 0;
- int pool_stride_y = 0;
- std::tie(pool_stride_x, pool_stride_y) = pool_info.pad_stride_info.stride();
- const int src_w = src->info()->dimension(0);
- const int src_h = src->info()->dimension(1);
- const uint8_t *const src_top_ptr =
- src->ptr_to_element(Coordinates(-static_cast<int>(pool_pad_left), -static_cast<int>(pool_pad_top)));
- const uint8_t *const src_bottom_ptr =
- src->ptr_to_element(Coordinates(-static_cast<int>(pool_pad_left), -static_cast<int>(pool_pad_top) + 1));
- const int pad_left = src->info()->padding().left;
- const int pad_right = src->info()->padding().right;
- const int in_stride_y = static_cast<int>(src->info()->strides_in_bytes().y());
- const T float_min = get_initial_min<T>(pool_info.use_inf_as_limit);
- const T fill_value = (pool_info.pool_type == PoolingType::MAX) ? float_min : 0.f;
-
- execute_window_loop(
- window,
- [&](const Coordinates &id)
- {
- const auto x_val = id.x() * pool_stride_x;
- const auto y_val_0 = id.y() * pool_stride_y;
- const auto y_val_1 = (id.y() * pool_stride_y) + 1;
- auto top_data = read_2_boundary_aware(src_w, src_h, pool_pad_left, pool_pad_top, x_val, y_val_0,
- reinterpret_cast<const T *>(src_top_ptr + in.offset()), fill_value);
- auto bottom_data =
- read_2_boundary_aware(src_w, src_h, pool_pad_left, pool_pad_top, x_val, y_val_1,
- reinterpret_cast<const T *>(src_bottom_ptr + in.offset()), fill_value);
- float32x2_t top_data_f32 = f16_to_f32<T>(top_data);
- float32x2_t bottom_data_f32 = f16_to_f32<T>(bottom_data);
-
- // Calculate max data, compare top first, then bottom, to make sue the first max is recorded.
- const float32x2_t max_data_top = vpmax_f32(top_data_f32, top_data_f32);
- const float32x2_t max_data_bottom = vpmax_f32(bottom_data_f32, bottom_data_f32);
- const float32x2_t max_data = vmax_f32(max_data_top, max_data_bottom);
- *(reinterpret_cast<T *>(out.ptr())) = static_cast<T>(vget_lane_f32(max_data, 0));
-
- // Calculate max data indice, which will be used in max unpool.
- const uint32_t offset_base =
- offset_no_padding<T>(in.offset(), id, *src->info(), pool_stride_x, pool_stride_y, DataLayout::NCHW);
- const uint32_t offset_top = (uint32_t)(offset_base / sizeof(T));
- const uint32_t offset_bottom = offset_top + in_stride_y / sizeof(T) - pad_right - pad_left;
- const uint32x2_t voffset_top = {offset_top, offset_top + 1u};
- const uint32x2_t voffset_bottom = {offset_bottom, offset_bottom + 1u};
- const uint32x2_t tmp_indices_top =
- vbsl_u32(vcge_f32(top_data_f32, vrev64_f32(top_data_f32)), voffset_top, vrev64_u32(voffset_top));
- const uint32x2_t tmp_indices_bottom = vbsl_u32(vcge_f32(bottom_data_f32, vrev64_f32(bottom_data_f32)),
- voffset_bottom, vrev64_u32(voffset_bottom));
- *(reinterpret_cast<int *>(indices.ptr())) = vget_lane_u32(
- vbsl_u32(vcge_f32(max_data_top, max_data_bottom), tmp_indices_top, tmp_indices_bottom), 0);
- },
- in, out, indices);
-}
-
-#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
-void pooling2_fp16_neon_nchw(const ITensor *src,
- ITensor *dst0,
- ITensor *dst1,
- PoolingLayerInfo &pool_info,
- const Window &window_src,
- const Window &window)
-{
- if (pool_info.pool_type == PoolingType::MAX && dst1)
- {
- pooling2_nchw_maxpool_indices<float16_t>(src, dst0, dst1, pool_info, window_src, window);
- }
- else
- {
- Iterator in(src, window_src);
- Iterator out(dst0, window);
- constexpr int pool_size = 2;
- const int pool_pad_right = pool_info.pad_stride_info.pad_right();
- const int pool_pad_top = pool_info.pad_stride_info.pad_top();
- const int pool_pad_left = pool_info.pad_stride_info.pad_left();
- const int pool_pad_bottom = pool_info.pad_stride_info.pad_bottom();
- int pool_stride_x, pool_stride_y = 0;
- std::tie(pool_stride_x, pool_stride_y) = pool_info.pad_stride_info.stride();
- const int src_w = src->info()->dimension(0);
- const int src_h = src->info()->dimension(1);
- const int upper_bound_w = src_w + (pool_info.exclude_padding ? 0 : pool_pad_right);
- const int upper_bound_h = src_h + (pool_info.exclude_padding ? 0 : pool_pad_bottom);
- const float16_t fp16_min = get_initial_min<half_float::half>(pool_info.use_inf_as_limit);
- const float16_t fill_value = (pool_info.pool_type == PoolingType::MAX) ? fp16_min : 0.0f;
-
- const unsigned char *const src_top_ptr =
- src->ptr_to_element(Coordinates(-static_cast<int>(pool_pad_left), -static_cast<int>(pool_pad_top)));
- const unsigned char *const src_bottom_ptr =
- src->ptr_to_element(Coordinates(-static_cast<int>(pool_pad_left), -static_cast<int>(pool_pad_top) + 1));
-
- execute_window_loop(
- window,
- [&](const Coordinates &id)
- {
- const auto in_top_ptr = reinterpret_cast<const float16_t *>(src_top_ptr + in.offset());
- const auto in_bottom_ptr = reinterpret_cast<const float16_t *>(src_bottom_ptr + in.offset());
-
- const auto x_val = id.x() * pool_stride_x;
- const auto y_val_0 = id.y() * pool_stride_y;
- const auto y_val_1 = (id.y() * pool_stride_y) + 1;
- float16x4_t top_data = read_4_boundary_aware_fp16(src_w, src_h, pool_pad_left, pool_pad_top, x_val,
- y_val_0, in_top_ptr, fill_value);
- float16x4_t bottom_data = read_4_boundary_aware_fp16(src_w, src_h, pool_pad_left, pool_pad_top, x_val,
- y_val_1, in_bottom_ptr, fill_value);
- float16x4_t res = {};
-
- // Get power of 2 in case of l2 pooling
- if (pool_info.pool_type == PoolingType::L2)
- {
- top_data = vmul_f16(top_data, top_data);
- bottom_data = vmul_f16(bottom_data, bottom_data);
- }
-
- if (pool_info.pool_type != PoolingType::MAX)
- {
- const float scale = calculate_avg_scale_pool2d(
- pool_info.exclude_padding, DataLayout::NCHW, id, pool_size, pool_size, upper_bound_w,
- upper_bound_h, pool_pad_left, pool_pad_top, pool_stride_x, pool_stride_y);
- const float16x4_t scale_v = vdup_n_f16(scale);
-
- const float16x4_t sum_data = vadd_f16(top_data, bottom_data);
- res = vmul_f16(vpadd_f16(sum_data, sum_data), scale_v);
- }
- else
- {
- const float16x4_t max_data = vmax_f16(top_data, bottom_data);
- res = vpmax_f16(max_data, max_data);
- }
-
- // Calculate square-root in case of l2 pooling
- if (pool_info.pool_type == PoolingType::L2)
- {
- res = vsqrt_f16(res);
- }
-
- // Store result
- *(reinterpret_cast<float16_t *>(out.ptr())) = vget_lane_f16(res, 0);
- },
- in, out);
- }
-}
-
-void poolingMxN_fp16_neon_nchw(const ITensor *src,
- ITensor *dst0,
- ITensor *dst1,
- PoolingLayerInfo &pool_info,
- const Window &window_src,
- const Window &window)
-{
- ARM_COMPUTE_UNUSED(dst1);
- Iterator in(src, window_src);
- Iterator out(dst0, window);
-
- const int pool_size_x = pool_info.is_global_pooling ? src->info()->tensor_shape().x() : pool_info.pool_size.width;
- const int pool_size_y = pool_info.is_global_pooling ? src->info()->tensor_shape().y() : pool_info.pool_size.height;
- const int pool_pad_right = pool_info.pad_stride_info.pad_right();
- const int pool_pad_top = pool_info.pad_stride_info.pad_top();
- const int pool_pad_left = pool_info.pad_stride_info.pad_left();
- const int pool_pad_bottom = pool_info.pad_stride_info.pad_bottom();
- int pool_stride_x = 0;
- int pool_stride_y = 0;
- std::tie(pool_stride_x, pool_stride_y) = pool_info.pad_stride_info.stride();
- const int src_w = src->info()->dimension(0);
- const int src_h = src->info()->dimension(1);
- const int upper_bound_w = src_w + (pool_info.exclude_padding ? 0 : pool_pad_right);
- const int upper_bound_h = src_h + (pool_info.exclude_padding ? 0 : pool_pad_bottom);
- const float16_t fp16_min = get_initial_min<half_float::half>(pool_info.use_inf_as_limit);
- const float16_t fill_value = (pool_info.pool_type == PoolingType::MAX) ? fp16_min : 0.0f;
-
- execute_window_loop(
- window,
- [&](const Coordinates &id)
- {
- float16_t res = 0.0f;
-
- if (pool_info.pool_type != PoolingType::MAX)
- {
- // Calculate scale
- const float16_t scale = calculate_avg_scale_pool2d(
- pool_info.exclude_padding, DataLayout::NCHW, id, pool_size_x, pool_size_y, upper_bound_w,
- upper_bound_h, pool_pad_left, pool_pad_top, pool_stride_x, pool_stride_y);
-
- // Perform pooling
- for (int y = 0; y < pool_size_y; ++y)
- {
- for (int x = 0; x < pool_size_x; ++x)
- {
- const auto ptr = reinterpret_cast<const float16_t *>(
- in.ptr() + (x - pool_pad_left) * static_cast<int>(src->info()->strides_in_bytes().x()) +
- (y - pool_pad_top) * static_cast<int>(src->info()->strides_in_bytes().y()));
-
- const int idx = x + id.x() * pool_stride_x - pool_pad_left;
- const int idy = y + id.y() * pool_stride_y - pool_pad_top;
- float16_t data = (idx < 0 || idy < 0 || idx >= src_w || idy >= src_h) ? fill_value : *ptr;
-
- if (pool_info.pool_type == PoolingType::L2)
- {
- data *= data;
- }
-
- res += data;
- }
- }
-
- // Divide by scale
- res *= scale;
- }
- else // if max pooling
- {
- res = fp16_min;
-
- for (int y = 0; y < pool_size_y; ++y)
- {
- for (int x = 0; x < pool_size_x; ++x)
- {
- const auto ptr = reinterpret_cast<const float16_t *>(
- in.ptr() + (x - pool_pad_left) * static_cast<int>(src->info()->strides_in_bytes().x()) +
- (y - pool_pad_top) * static_cast<int>(src->info()->strides_in_bytes().y()));
-
- const int idx = x + id.x() * pool_stride_x - pool_pad_left;
- const int idy = y + id.y() * pool_stride_y - pool_pad_top;
- float16_t data = (idx < 0 || idy < 0 || idx >= src_w || idy >= src_h) ? fill_value : *ptr;
- res = std::max(res, data);
- }
- }
- }
-
- // Calculate square-root in case of l2 pooling
- if (pool_info.pool_type == PoolingType::L2)
- {
- res = std::sqrt(res);
- }
-
- // Store result
- *(reinterpret_cast<float16_t *>(out.ptr())) = res;
- },
- in, out);
-}
-#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
-
void poolingMxN_fp32_neon_nchw(const ITensor *src,
ITensor *dst0,
ITensor *dst1,
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-20 19:12:22 +0000