diff options
Diffstat (limited to 'src/cpu/kernels/pool2d/neon/nchw/all.cpp')
| -rw-r--r-- | src/cpu/kernels/pool2d/neon/nchw/all.cpp | 369 |
1 files changed, 210 insertions, 159 deletions
diff --git a/src/cpu/kernels/pool2d/neon/nchw/all.cpp b/src/cpu/kernels/pool2d/neon/nchw/all.cpp index 3ca7701087..109fc1b283 100644 --- a/src/cpu/kernels/pool2d/neon/nchw/all.cpp +++ b/src/cpu/kernels/pool2d/neon/nchw/all.cpp @@ -28,18 +28,55 @@ #include "src/core/NEON/wrapper/intrinsics/intrinsics.h" #include "src/core/helpers/WindowHelpers.h" #include "src/cpu/kernels/pool2d/neon/list.h" +#include <limits> #ifdef ENABLE_NCHW_KERNELS namespace arm_compute { namespace cpu { +#define READ_2_RIGHT_BOUNDARY_AWARE(height, width, pad_left, pad_top, x, y, ptr, fval) \ + (x == width + pad_left - 1) ? vset_lane_f32(*(ptr), vdup_n_f32(fval), 0) : vld1_f32(ptr) +#define READ_2_LEFT_BOUNDARY_AWARE(height, width, pad_left, pad_top, x, y, ptr, fval) \ + (x == pad_left - 1) ? vset_lane_f32(*(1 + ptr), vdup_n_f32(fval), 1) : READ_2_RIGHT_BOUNDARY_AWARE(height, width, pad_left, pad_top, x, y, ptr, fval) +#define READ_2_BOUNDARY_AWARE(height, width, pad_left, pad_top, x, y, ptr, fval) \ + ((y < pad_top) || (x < pad_left - 1) || (y >= height + pad_top) || (x > width + pad_left - 1)) ? vdup_n_f32(fval) : READ_2_LEFT_BOUNDARY_AWARE(height, width, pad_left, pad_top, x, y, ptr, fval) + +#define READ_4_BOUNDARY_AWARE(height, width, pad_left, pad_top, x, y, ptr, fval) \ + vcombine_f32(READ_2_BOUNDARY_AWARE(height, width, pad_left, pad_top, x, y, ptr, fval), \ + READ_2_BOUNDARY_AWARE(height, width, pad_left, pad_top, (x + 2), y, (ptr + 2), fval)) + +float32x4x2_t read_8_boundary_aware(int height, int width, int pad_left, int pad_top, int x, int y, const float *ptr, float fval) +{ + float32x4x2_t vec; + vec.val[0] = READ_4_BOUNDARY_AWARE(height, width, pad_left, pad_top, x, y, ptr, fval); + vec.val[1] = READ_4_BOUNDARY_AWARE(height, width, pad_left, pad_top, (x + 4), y, (ptr + 4), fval); + 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); - ARM_COMPUTE_UNUSED(pool_info.pool_type); - ARM_COMPUTE_UNUSED(pool_info.exclude_padding); Iterator in(src, window_src); Iterator out(dst0, window); @@ -52,19 +89,29 @@ void pooling3_fp16_neon_nchw(const ITensor *src, ITensor *dst0, ITensor *dst1, P 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 upper_bound_w = src->info()->dimension(0) + (pool_info.exclude_padding ? 0 : pool_pad_right); - const int upper_bound_h = src->info()->dimension(1) + (pool_info.exclude_padding ? 0 : pool_pad_bottom); - + 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); + constexpr float16_t fp16_min = -100.0f; + 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) { - float16x4_t top_data = vld1_f16(reinterpret_cast<const float16_t *>(src_top_ptr + in.offset())); - float16x4_t middle_data = vld1_f16(reinterpret_cast<const float16_t *>(src_middle_ptr + in.offset())); - float16x4_t bottom_data = vld1_f16(reinterpret_cast<const float16_t *>(src_bottom_ptr + in.offset())); - float16x4_t res = {}; + 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) @@ -88,7 +135,7 @@ void pooling3_fp16_neon_nchw(const ITensor *src, ITensor *dst0, ITensor *dst1, P else { const float16x4_t max_data = vmax_f16(vmax_f16(top_data, bottom_data), middle_data); - res = vpmax_f16(vset_lane_f16(-std::numeric_limits<float>::max(), max_data, 3), max_data); + res = vpmax_f16(vset_lane_f16(fp16_min, max_data, 3), max_data); res = vpmax_f16(res, res); } @@ -120,6 +167,25 @@ f16_to_f32(float32x2_t 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); @@ -130,16 +196,25 @@ void pooling2_nchw_maxpool_indices(const ITensor *src, ITensor *dst0, ITensor *d 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()); + constexpr T float_min = -100.0f; + const T fill_value = (pool_info.pool_type == PoolingType::MAX) ? float_min : 0.f; execute_window_loop(window, [&](const Coordinates & id) { - auto top_data = wrapper::vload(reinterpret_cast<const T *>(src_top_ptr + in.offset())); - auto bottom_data = wrapper::vload(reinterpret_cast<const 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; + 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); @@ -180,17 +255,29 @@ void pooling2_fp16_neon_nchw(const ITensor *src, ITensor *dst0, ITensor *dst1, P 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 upper_bound_w = src->info()->dimension(0) + (pool_info.exclude_padding ? 0 : pool_pad_right); - const int upper_bound_h = src->info()->dimension(1) + (pool_info.exclude_padding ? 0 : pool_pad_bottom); + 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); + constexpr float16_t fp16_min = -100.0f; + 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) { - float16x4_t top_data = vld1_f16(reinterpret_cast<const float16_t *>(src_top_ptr + in.offset())); - float16x4_t bottom_data = vld1_f16(reinterpret_cast<const float16_t *>(src_bottom_ptr + in.offset())); - float16x4_t res = {}; + 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) @@ -242,48 +329,35 @@ void poolingMxN_fp16_neon_nchw(const ITensor *src, ITensor *dst0, ITensor *dst1, 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 upper_bound_w = src->info()->dimension(0) + (pool_info.exclude_padding ? 0 : pool_pad_right); - const int upper_bound_h = src->info()->dimension(1) + (pool_info.exclude_padding ? 0 : pool_pad_bottom); + 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); + constexpr float16_t fp16_min = -100.0f; + 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; - float16x8_t vres = vdupq_n_f16(0.0f); + float16_t res = 0.0f; if(pool_info.pool_type != PoolingType::MAX) { // Calculate scale - const float scale = calculate_avg_scale(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); + const float16_t scale = calculate_avg_scale(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) { - int x = 0; - for(; x <= (pool_size_x - 8); x += 8) + for(int x = 0; x < pool_size_x; ++x) { - const float16x8_t data = vld1q_f16(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()))); - - // Get power of 2 in case of l2 pooling and accumulate - if(pool_info.pool_type == PoolingType::L2) - { - vres = vaddq_f16(vres, vmulq_f16(data, data)); - } - else - { - vres = vaddq_f16(vres, data); - } - } + 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())); - // Leftover for loop - for(; x < pool_size_x; ++x) - { - float16_t data = *(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; - // Get power of 2 in case of l2 pooling if(pool_info.pool_type == PoolingType::L2) { data *= data; @@ -293,45 +367,26 @@ void poolingMxN_fp16_neon_nchw(const ITensor *src, ITensor *dst0, ITensor *dst1, } } - // Reduction - float16x4_t tmp = vpadd_f16(vget_high_f16(vres), vget_low_f16(vres)); - res += vget_lane_f16(tmp, 0); - res += vget_lane_f16(tmp, 1); - res += vget_lane_f16(tmp, 2); - res += vget_lane_f16(tmp, 3); - // Divide by scale res *= scale; } - else + else // if max pooling { - float16x8_t vres = vdupq_n_f16(std::numeric_limits<float>::lowest()); - res = std::numeric_limits<float>::lowest(); + res = fp16_min; for(int y = 0; y < pool_size_y; ++y) { - int x = 0; - for(; x <= (pool_size_x - 8); x += 8) + for(int x = 0; x < pool_size_x; ++x) { - const float16x8_t data = vld1q_f16(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()))); - vres = vmaxq_f16(vres, data); - } + 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())); - // Leftover for loop - for(; x < pool_size_x; ++x) - { - const float16_t data = *(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()))); - res = std::max(res, data); + 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); } } - - float16x4_t tmp = vpmax_f16(vget_high_f16(vres), vget_low_f16(vres)); - res = std::max(res, vget_lane_f16(tmp, 0)); - res = std::max(res, vget_lane_f16(tmp, 1)); - res = std::max(res, vget_lane_f16(tmp, 2)); - res = std::max(res, vget_lane_f16(tmp, 3)); } // Calculate square-root in case of l2 pooling @@ -362,8 +417,11 @@ void poolingMxN_fp32_neon_nchw(const ITensor *src, ITensor *dst0, ITensor *dst1, 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 upper_bound_w = src->info()->dimension(0) + (pool_info.exclude_padding ? 0 : pool_pad_right); - const int upper_bound_h = src->info()->dimension(1) + (pool_info.exclude_padding ? 0 : pool_pad_bottom); + 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 float fill_value = (pool_info.pool_type == PoolingType::MAX) ? -std::numeric_limits<float>::max() : 0.0f; execute_window_loop(window, [&](const Coordinates & id) { @@ -372,38 +430,21 @@ void poolingMxN_fp32_neon_nchw(const ITensor *src, ITensor *dst0, ITensor *dst1, if(pool_info.pool_type != PoolingType::MAX) { // Calculate scale - const float scale = calculate_avg_scale(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); + const float scale = calculate_avg_scale(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 - float32x4_t vres = vdupq_n_f32(0.0f); - for(int y = 0; y < pool_size_y; ++y) { - int x = 0; - for(; x <= (pool_size_x - 4); x += 4) + for(int x = 0; x < pool_size_x; ++x) { - const float32x4_t data = vld1q_f32(reinterpret_cast<const float *>(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 auto ptr = reinterpret_cast<const float *>(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())); - // Get power of 2 in case of l2 pooling and accumulate - if(pool_info.pool_type == PoolingType::L2) - { - vres = vmlaq_f32(vres, data, data); - } - else - { - vres = vaddq_f32(vres, data); - } - } + const int idx = x + id.x() * pool_stride_x - pool_pad_left; + const int idy = y + id.y() * pool_stride_y - pool_pad_top; + float data = (idx < 0 || idy < 0 || idx >= src_w || idy >= src_h) ? fill_value : *ptr; - // Leftover for loop - for(; x < pool_size_x; ++x) - { - float data = *(reinterpret_cast<const float *>(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()))); - - // Get power of 2 in case of l2 pooling if(pool_info.pool_type == PoolingType::L2) { data *= data; @@ -413,51 +454,26 @@ void poolingMxN_fp32_neon_nchw(const ITensor *src, ITensor *dst0, ITensor *dst1, } } -#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 + else // if max pooling { - float32x4_t vres = vdupq_n_f32(std::numeric_limits<float>::lowest()); - res = std::numeric_limits<float>::lowest(); + res = std::numeric_limits<float>::lowest(); for(int y = 0; y < pool_size_y; ++y) { - int x = 0; - for(; x <= (pool_size_x - 4); x += 4) + for(int x = 0; x < pool_size_x; ++x) { - const float32x4_t data = vld1q_f32(reinterpret_cast<const float *>(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()))); - vres = vmaxq_f32(vres, data); - } + const auto ptr = reinterpret_cast<const float *>(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())); - // Leftover for loop - for(; x < pool_size_x; ++x) - { - const float data = *(reinterpret_cast<const float *>(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()))); - res = std::max(res, data); + const int idx = x + id.x() * pool_stride_x - pool_pad_left; + const int idy = y + id.y() * pool_stride_y - pool_pad_top; + float data = (idx < 0 || idy < 0 || idx >= src_w || idy >= src_h) ? fill_value : *ptr; + 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 @@ -490,20 +506,28 @@ void pooling2_fp32_neon_nchw(const ITensor *src, ITensor *dst0, ITensor *dst1, P 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 upper_bound_w = src->info()->dimension(0) + (pool_info.exclude_padding ? 0 : pool_pad_right); - const int upper_bound_h = src->info()->dimension(1) + (pool_info.exclude_padding ? 0 : pool_pad_bottom); + 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 float fill_value = (pool_info.pool_type == PoolingType::MAX) ? -std::numeric_limits<float>::max() : 0.0f; 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)); execute_window_loop(window, [&](const Coordinates & id) { - const auto in_top_ptr = reinterpret_cast<const float *>(src_top_ptr + in.offset()); - const auto in_bottom_ptr = reinterpret_cast<const float *>(src_bottom_ptr + in.offset()); - float32x2_t top_data = vld1_f32(in_top_ptr); - float32x2_t bottom_data = vld1_f32(in_bottom_ptr); - float32x2_t res = {}; - float final_res = 0; + const auto in_top_ptr = reinterpret_cast<const float *>(src_top_ptr + in.offset()); + const auto in_bottom_ptr = reinterpret_cast<const float *>(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; + auto top_data = READ_2_BOUNDARY_AWARE(src_h, src_w, pool_pad_left, pool_pad_top, x_val, y_val_0, in_top_ptr, fill_value); + auto bottom_data = READ_2_BOUNDARY_AWARE(src_h, src_w, pool_pad_left, pool_pad_top, x_val, y_val_1, in_bottom_ptr, fill_value); + float32x2_t res = {}; + float final_res = 0; + // Get power of 2 in case of l2 pooling if(pool_info.pool_type == PoolingType::L2) { @@ -556,8 +580,11 @@ void pooling3_fp32_neon_nchw(const ITensor *src, ITensor *dst0, ITensor *dst1, P 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 upper_bound_w = src->info()->dimension(0) + (pool_info.exclude_padding ? 0 : pool_pad_right); - const int upper_bound_h = src->info()->dimension(1) + (pool_info.exclude_padding ? 0 : pool_pad_bottom); + 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 float fill_value = (pool_info.pool_type == PoolingType::MAX) ? -std::numeric_limits<float>::max() : 0.0f; 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_middle_ptr = src->ptr_to_element(Coordinates(-static_cast<int>(pool_pad_left), -static_cast<int>(pool_pad_top) + 1)); @@ -565,11 +592,20 @@ void pooling3_fp32_neon_nchw(const ITensor *src, ITensor *dst0, ITensor *dst1, P execute_window_loop(window, [&](const Coordinates & id) { - float32x4_t top_data = vld1q_f32(reinterpret_cast<const float *>(src_top_ptr + in.offset())); - float32x4_t middle_data = vld1q_f32(reinterpret_cast<const float *>(src_middle_ptr + in.offset())); - float32x4_t bottom_data = vld1q_f32(reinterpret_cast<const float *>(src_bottom_ptr + in.offset())); - float32x2_t res = {}; - float final_res = 0; + const auto in_top_ptr = reinterpret_cast<const float *>(src_top_ptr + in.offset()); + const auto in_middle_ptr = reinterpret_cast<const float *>(src_middle_ptr + in.offset()); + const auto in_bottom_ptr = reinterpret_cast<const float *>(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; + const auto y_val_2 = (id.y() * pool_stride_y) + 2; + auto top_data = READ_4_BOUNDARY_AWARE(src_h, src_w, pool_pad_left, pool_pad_top, x_val, y_val_0, in_top_ptr, fill_value); + auto middle_data = READ_4_BOUNDARY_AWARE(src_h, src_w, pool_pad_left, pool_pad_top, x_val, y_val_1, in_middle_ptr, fill_value); + auto bottom_data = READ_4_BOUNDARY_AWARE(src_h, src_w, pool_pad_left, pool_pad_top, x_val, y_val_2, in_bottom_ptr, fill_value); + + float32x2_t res = {}; + float final_res = 0; // Get power of 2 in case of l2 pooling if(pool_info.pool_type == PoolingType::L2) @@ -625,8 +661,11 @@ void pooling7_fp32_neon_nchw(const ITensor *src, ITensor *dst0, ITensor *dst1, P 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 upper_bound_w = src->info()->dimension(0) + (pool_info.exclude_padding ? 0 : pool_pad_right); - const int upper_bound_h = src->info()->dimension(1) + (pool_info.exclude_padding ? 0 : pool_pad_bottom); + 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 float fill_value = (pool_info.pool_type == PoolingType::MAX) ? -std::numeric_limits<float>::max() : 0.0f; std::array<const uint8_t *, pool_size> src_ptrs{ {} }; for(int i = 0; i < pool_size; ++i) @@ -636,8 +675,15 @@ void pooling7_fp32_neon_nchw(const ITensor *src, ITensor *dst0, ITensor *dst1, P execute_window_loop(window, [&](const Coordinates & id) { + auto in_ptr = reinterpret_cast<const float *>(src_ptrs[0] + in.offset()); + + auto x_val = id.x() * pool_stride_x; + auto y_val = id.y() * pool_stride_y; + float32x4x2_t data = read_8_boundary_aware(src_h, src_w, pool_pad_left, pool_pad_top, x_val, y_val, in_ptr, fill_value); + float32x2_t res = {}; float final_res = 0.f; + if(pool_info.pool_type != PoolingType::MAX) { // Calculate scale @@ -645,8 +691,6 @@ void pooling7_fp32_neon_nchw(const ITensor *src, ITensor *dst0, ITensor *dst1, P pool_stride_y); const float32x2_t scale_v = vdup_n_f32(scale); - // Perform pooling - float32x4x2_t data = vld2q_f32(reinterpret_cast<const float *>(src_ptrs[0] + in.offset())); // Get power of 2 in case of l2 pooling if(pool_info.pool_type == PoolingType::L2) { @@ -656,7 +700,11 @@ void pooling7_fp32_neon_nchw(const ITensor *src, ITensor *dst0, ITensor *dst1, P float32x4_t sum_data = vaddq_f32(data.val[0], vsetq_lane_f32(0.f, data.val[1], 3)); for(int i = 1; i < pool_size; ++i) { - data = vld2q_f32(reinterpret_cast<const float *>(src_ptrs[i] + in.offset())); + in_ptr = reinterpret_cast<const float *>(src_ptrs[i] + in.offset()); + + x_val = id.x() * pool_stride_x; + y_val = (id.y() * pool_stride_y) + i; + data = read_8_boundary_aware(src_h, src_w, pool_pad_left, pool_pad_top, x_val, y_val, in_ptr, fill_value); // Get power of 2 in case of l2 pooling if(pool_info.pool_type == PoolingType::L2) { @@ -671,14 +719,17 @@ void pooling7_fp32_neon_nchw(const ITensor *src, ITensor *dst0, ITensor *dst1, P } else { - float32x4x2_t max_data = vld2q_f32(reinterpret_cast<const float *>(src_ptrs[0] + in.offset())); for(int i = 1; i < pool_size; ++i) { - const float32x4x2_t data = vld2q_f32(reinterpret_cast<const float *>(src_ptrs[i] + in.offset())); - max_data = vmax2q_f32(max_data, data); + in_ptr = reinterpret_cast<const float *>(src_ptrs[i] + in.offset()); + + x_val = id.x() * pool_stride_x; + y_val = (id.y() * pool_stride_y) + i; + float32x4x2_t temp = read_8_boundary_aware(src_h, src_w, pool_pad_left, pool_pad_top, x_val, y_val, in_ptr, fill_value); + data = vmax2q_f32(data, temp); } - res = vpmax_f32(vget_high_f32(vsetq_lane_f32(-std::numeric_limits<float>::max(), max_data.val[1], 3)), vget_low_f32(max_data.val[1])); - res = vpmax_f32(res, vpmax_f32(vget_high_f32(max_data.val[0]), vget_low_f32(max_data.val[0]))); + res = vpmax_f32(vget_high_f32(vsetq_lane_f32(-std::numeric_limits<float>::max(), data.val[1], 3)), vget_low_f32(data.val[1])); + res = vpmax_f32(res, vpmax_f32(vget_high_f32(data.val[0]), vget_low_f32(data.val[0]))); res = vpmax_f32(res, res); } final_res = vget_lane_f32(res, 0); |