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Diffstat (limited to 'src/cpu/kernels/pool3d/neon/impl.cpp')
| -rw-r--r-- | src/cpu/kernels/pool3d/neon/impl.cpp | 462 |
1 files changed, 0 insertions, 462 deletions
diff --git a/src/cpu/kernels/pool3d/neon/impl.cpp b/src/cpu/kernels/pool3d/neon/impl.cpp deleted file mode 100644 index 2b089f3079..0000000000 --- a/src/cpu/kernels/pool3d/neon/impl.cpp +++ /dev/null @@ -1,462 +0,0 @@ -/* - * Copyright (c) 2022 Arm Limited. - * - * SPDX-License-Identifier: MIT - * - * Permission is hereby granted, free of charge, to any person obtaining a copy - * of this software and associated documentation files (the "Software"), to - * deal in the Software without restriction, including without limitation the - * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or - * sell copies of the Software, and to permit persons to whom the Software is - * furnished to do so, subject to the following conditions: - * - * The above copyright notice and this permission notice shall be included in all - * copies or substantial portions of the Software. - * - * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR - * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, - * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE - * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER - * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, - * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE - * SOFTWARE. - */ -#include "arm_compute/core/Helpers.h" -#include "src/core/NEON/wrapper/intrinsics/intrinsics.h" -#include "src/core/helpers/PoolingHelpers.h" -#include "src/core/helpers/WindowHelpers.h" -#include "src/cpu/kernels/pool3d/neon/quantized.h" - -#include "src/cpu/kernels/pool3d/neon/impl.h" - -namespace arm_compute -{ -namespace cpu -{ -namespace -{ -template <typename T> -void max_poolingMxNxD_fp_neon_ndhwc(const ITensor *src, ITensor *dst0, Pooling3dLayerInfo &pool_info, const Window &window_out, - const int window_start_x, const int window_end_x, const int window_step_x) - -{ - using vtype = wrapper::traits::neon_bitvector<T, wrapper::traits::BitWidth::W128>; - using vector_type = typename vtype::type; - using tag_type = typename vtype::tag_type; - - int pool_stride_x = static_cast<int>(pool_info.stride.width); - int pool_stride_y = static_cast<int>(pool_info.stride.height); - int pool_stride_z = static_cast<int>(pool_info.stride.depth); - - const int pool_size_x = pool_info.is_global_pooling ? src->info()->tensor_shape().y() : pool_info.pool_size.width; - const int pool_size_y = pool_info.is_global_pooling ? src->info()->tensor_shape().z() : pool_info.pool_size.height; - const int pool_size_z = pool_info.is_global_pooling ? src->info()->tensor_shape()[3] : pool_info.pool_size.depth; - - const int pool_pad_top = static_cast<int>(pool_info.padding.top); - const int pool_pad_left = static_cast<int>(pool_info.padding.left); - const int pool_pad_front = static_cast<int>(pool_info.padding.front); - - const int input_dim_w = src->info()->dimension(1); - const int input_dim_h = src->info()->dimension(2); - const int input_dim_d = src->info()->dimension(3); - - const int y_stride = static_cast<int>(src->info()->strides_in_bytes().y()); - const int z_stride = static_cast<int>(src->info()->strides_in_bytes().z()); - const int w_stride = static_cast<int>(src->info()->strides_in_bytes()[3]); - const int n_stride = static_cast<int>(src->info()->strides_in_bytes()[4]); - - const uint8_t *in_ptr_start = src->buffer() + src->info()->offset_first_element_in_bytes(); - - Iterator out(dst0, window_out); - - vector_type vres; - execute_window_loop(window_out, [&](const Coordinates & id) - { - // Computing the theoretical input starting/ending points - const int in_idx_width = static_cast<int>(id.y()) * pool_stride_x - pool_pad_left; - const int in_idx_height = static_cast<int>(id.z()) * pool_stride_y - pool_pad_top; - const int in_idx_depth = static_cast<int>(id[3]) * pool_stride_z - pool_pad_front; - - const int pool_start_x = std::max(0, -in_idx_width); - const int pool_end_x_t = std::min(input_dim_w + pool_pad_left - in_idx_width, pool_size_x); - const int pool_start_y = std::max(0, -in_idx_height); - const int pool_end_y_t = std::min(input_dim_h + pool_pad_top - in_idx_height, pool_size_y); - - const int pool_start_z = std::max(0, -in_idx_depth); - const int pool_end_z_t = std::min(input_dim_d + pool_pad_front - in_idx_depth, pool_size_z); - - // The end of width to consider in calculation should exclude PAD_X, PAD_Y and PAD_Z - const int pool_end_x = std::min(pool_end_x_t, input_dim_w - in_idx_width); - const int pool_end_y = std::min(pool_end_y_t, input_dim_h - in_idx_height); - const int pool_end_z = std::min(pool_end_z_t, input_dim_d - in_idx_depth); - - const uint8_t *in_ptr_n = in_ptr_start + id[4] * n_stride; - - int x_off = window_start_x; - - for(; x_off <= (window_end_x - window_step_x); x_off += window_step_x) // C - { - vres = wrapper::vdup_n(static_cast<T>(-std::numeric_limits<float>::infinity()), tag_type()); - for(int z = pool_start_z; z < pool_end_z; ++z) - { - const uint8_t *in_ptr_z = in_ptr_n + (z + in_idx_depth) * w_stride; - for(int y = pool_start_y; y < pool_end_y; ++y) - { - const uint8_t *in_ptr_y = in_ptr_z + (y + in_idx_height) * z_stride; - for(int x = pool_start_x; x < pool_end_x; ++x) - { - const uint8_t *in_ptr_x = in_ptr_y + (x + in_idx_width) * y_stride; - const vector_type data = wrapper::vloadq(reinterpret_cast<const T *>(in_ptr_x) + x_off); - vres = wrapper::vmax(vres, data); - } - } - } - // Store result - wrapper::vstore(reinterpret_cast<T *>(out.ptr()) + x_off, vres); - } - - // Left-overs loop - for(; x_off < window_end_x; ++x_off) - { - T res(0); - res = -std::numeric_limits<float>::infinity(); - for(int z = pool_start_z; z < pool_end_z; ++z) - { - const uint8_t *in_ptr_z = in_ptr_n + (z + in_idx_depth) * w_stride; - for(int y = pool_start_y; y < pool_end_y; ++y) - { - const uint8_t *in_ptr_y = in_ptr_z + (y + in_idx_height) * z_stride; - for(int x = pool_start_x; x < pool_end_x; ++x) - { - const uint8_t *in_ptr_x = in_ptr_y + (x + in_idx_width) * y_stride; - const T data = *(reinterpret_cast<const T *>(in_ptr_x) + x_off); - res = std::max(res, data); - } - } - } - // Store result - *(reinterpret_cast<T *>(out.ptr()) + x_off) = res; - } - }, - out); -} - -template <typename T> -void avg_poolingMxNxD_fp_neon_ndhwc(const ITensor *src, ITensor *dst0, Pooling3dLayerInfo &pool_info, - const Window &window_out, const int window_start_x, const int window_end_x, const int window_step_x) -{ - using vtype = wrapper::traits::neon_bitvector<T, wrapper::traits::BitWidth::W128>; - using vector_type = typename vtype::type; - using tag_type = typename vtype::tag_type; - - int pool_stride_x = static_cast<int>(pool_info.stride.width); - int pool_stride_y = static_cast<int>(pool_info.stride.height); - int pool_stride_z = static_cast<int>(pool_info.stride.depth); - - const int pool_size_x = pool_info.is_global_pooling ? src->info()->tensor_shape().y() : pool_info.pool_size.width; - const int pool_size_y = pool_info.is_global_pooling ? src->info()->tensor_shape().z() : pool_info.pool_size.height; - const int pool_size_z = pool_info.is_global_pooling ? src->info()->tensor_shape()[3] : pool_info.pool_size.depth; - - const int pool_pad_top = static_cast<int>(pool_info.padding.top); - const int pool_pad_bottom = static_cast<int>(pool_info.padding.bottom); - const int pool_pad_left = static_cast<int>(pool_info.padding.left); - const int pool_pad_right = static_cast<int>(pool_info.padding.right); - const int pool_pad_front = static_cast<int>(pool_info.padding.front); - const int pool_pad_back = static_cast<int>(pool_info.padding.back); - - const int upper_bound_w = src->info()->dimension(1) + (pool_info.exclude_padding ? 0 : pool_pad_right); - const int upper_bound_h = src->info()->dimension(2) + (pool_info.exclude_padding ? 0 : pool_pad_bottom); - const int upper_bound_d = src->info()->dimension(3) + (pool_info.exclude_padding ? 0 : pool_pad_back); - - const int input_dim_w = src->info()->dimension(1); - const int input_dim_h = src->info()->dimension(2); - const int input_dim_d = src->info()->dimension(3); - - const int y_stride = static_cast<int>(src->info()->strides_in_bytes().y()); - const int z_stride = static_cast<int>(src->info()->strides_in_bytes().z()); - const int w_stride = static_cast<int>(src->info()->strides_in_bytes()[3]); - const int n_stride = static_cast<int>(src->info()->strides_in_bytes()[4]); - - const uint8_t *in_ptr_start = src->buffer() + src->info()->offset_first_element_in_bytes(); - - Iterator out(dst0, window_out); - - vector_type vres; - execute_window_loop(window_out, [&](const Coordinates & id) - { - // Computing the theoretical input starting/ending points - const int in_idx_width = static_cast<int>(id.y()) * pool_stride_x - pool_pad_left; - const int in_idx_height = static_cast<int>(id.z()) * pool_stride_y - pool_pad_top; - const int in_idx_depth = static_cast<int>(id[3]) * pool_stride_z - pool_pad_front; - - const int pool_start_x = std::max(0, -in_idx_width); - const int pool_end_x_t = std::min(input_dim_w + pool_pad_left - in_idx_width, pool_size_x); - const int pool_start_y = std::max(0, -in_idx_height); - const int pool_end_y_t = std::min(input_dim_h + pool_pad_top - in_idx_height, pool_size_y); - - const int pool_start_z = std::max(0, -in_idx_depth); - const int pool_end_z_t = std::min(input_dim_d + pool_pad_front - in_idx_depth, pool_size_z); - - // The end of width to consider in calculation should exclude PAD_X, PAD_Y and PAD_Z - const int pool_end_x = std::min(pool_end_x_t, input_dim_w - in_idx_width); - const int pool_end_y = std::min(pool_end_y_t, input_dim_h - in_idx_height); - const int pool_end_z = std::min(pool_end_z_t, input_dim_d - in_idx_depth); - - const uint8_t *in_ptr_n = in_ptr_start + id[4] * n_stride; - - // Calculate scale - const float scale = calculate_avg_scale_pool3d(pool_info.exclude_padding, id, pool_size_x, pool_size_y, pool_size_z, upper_bound_w, upper_bound_h, upper_bound_d, pool_pad_left, - pool_pad_top, pool_pad_front, pool_stride_x, - pool_stride_y, pool_stride_z); - const vector_type scale_v = wrapper::vdup_n(static_cast<T>(scale), tag_type()); - - int x_off = window_start_x; - - for(; x_off <= (window_end_x - window_step_x); x_off += window_step_x) // C - { - // Perform pooling - vres = wrapper::vdup_n(static_cast<T>(0.0f), tag_type()); - for(int z = pool_start_z; z < pool_end_z; ++z) - { - const uint8_t *in_ptr_z = in_ptr_n + (z + in_idx_depth) * w_stride; - for(int y = pool_start_y; y < pool_end_y; ++y) - { - const uint8_t *in_ptr_y = in_ptr_z + (y + in_idx_height) * z_stride; - for(int x = pool_start_x; x < pool_end_x; ++x) - { - const uint8_t *in_ptr_x = in_ptr_y + (x + in_idx_width) * y_stride; - const vector_type data = wrapper::vloadq(reinterpret_cast<const T *>(in_ptr_x) + x_off); - vres = wrapper::vadd(vres, data); - } - } - } - - // Divide by scale - vres = wrapper::vmul(vres, scale_v); - - // Store result - wrapper::vstore(reinterpret_cast<T *>(out.ptr()) + x_off, vres); - } - - // Left-overs loop - for(; x_off < window_end_x; ++x_off) - { - T res(0); - - for(int z = pool_start_z; z < pool_end_z; ++z) - { - const uint8_t *in_ptr_z = in_ptr_n + (z + in_idx_depth) * w_stride; - for(int y = pool_start_y; y < pool_end_y; ++y) - { - const uint8_t *in_ptr_y = in_ptr_z + (y + in_idx_height) * z_stride; - for(int x = pool_start_x; x < pool_end_x; ++x) - { - const uint8_t *in_ptr_x = in_ptr_y + (x + in_idx_width) * y_stride; - const T data = *(reinterpret_cast<const T *>(in_ptr_x) + x_off); - res += data; - } - } - } - - // Divide by scale - res *= scale; - - // Store result - *(reinterpret_cast<T *>(out.ptr()) + x_off) = res; - } - }, - out); -} - -template <typename T> -void l2_poolingMxNxD_fp_neon_ndhwc(const ITensor *src, ITensor *dst0, Pooling3dLayerInfo &pool_info, - const Window &window_out, const int window_start_x, const int window_end_x, const int window_step_x) -{ - using vtype = wrapper::traits::neon_bitvector<T, wrapper::traits::BitWidth::W128>; - using vector_type = typename vtype::type; - using tag_type = typename vtype::tag_type; - - int pool_stride_x = static_cast<int>(pool_info.stride.width); - int pool_stride_y = static_cast<int>(pool_info.stride.height); - int pool_stride_z = static_cast<int>(pool_info.stride.depth); - - const int pool_size_x = pool_info.is_global_pooling ? src->info()->tensor_shape().y() : pool_info.pool_size.width; - const int pool_size_y = pool_info.is_global_pooling ? src->info()->tensor_shape().z() : pool_info.pool_size.height; - const int pool_size_z = pool_info.is_global_pooling ? src->info()->tensor_shape()[3] : pool_info.pool_size.depth; - - const int pool_pad_top = static_cast<int>(pool_info.padding.top); - const int pool_pad_bottom = static_cast<int>(pool_info.padding.bottom); - const int pool_pad_left = static_cast<int>(pool_info.padding.left); - const int pool_pad_right = static_cast<int>(pool_info.padding.right); - const int pool_pad_front = static_cast<int>(pool_info.padding.front); - const int pool_pad_back = static_cast<int>(pool_info.padding.back); - - const int upper_bound_w = src->info()->dimension(1) + (pool_info.exclude_padding ? 0 : pool_pad_right); - const int upper_bound_h = src->info()->dimension(2) + (pool_info.exclude_padding ? 0 : pool_pad_bottom); - const int upper_bound_d = src->info()->dimension(3) + (pool_info.exclude_padding ? 0 : pool_pad_back); - - const int input_dim_w = src->info()->dimension(1); - const int input_dim_h = src->info()->dimension(2); - const int input_dim_d = src->info()->dimension(3); - - const int y_stride = static_cast<int>(src->info()->strides_in_bytes().y()); - const int z_stride = static_cast<int>(src->info()->strides_in_bytes().z()); - const int w_stride = static_cast<int>(src->info()->strides_in_bytes()[3]); - const int n_stride = static_cast<int>(src->info()->strides_in_bytes()[4]); - - const uint8_t *in_ptr_start = src->buffer() + src->info()->offset_first_element_in_bytes(); - - Iterator out(dst0, window_out); - - vector_type vres; - execute_window_loop(window_out, [&](const Coordinates & id) - { - // Computing the theoretical input starting/ending points - const int in_idx_width = static_cast<int>(id.y()) * pool_stride_x - pool_pad_left; - const int in_idx_height = static_cast<int>(id.z()) * pool_stride_y - pool_pad_top; - const int in_idx_depth = static_cast<int>(id[3]) * pool_stride_z - pool_pad_front; - - const int pool_start_x = std::max(0, -in_idx_width); - const int pool_end_x_t = std::min(input_dim_w + pool_pad_left - in_idx_width, pool_size_x); - const int pool_start_y = std::max(0, -in_idx_height); - const int pool_end_y_t = std::min(input_dim_h + pool_pad_top - in_idx_height, pool_size_y); - - const int pool_start_z = std::max(0, -in_idx_depth); - const int pool_end_z_t = std::min(input_dim_d + pool_pad_front - in_idx_depth, pool_size_z); - - // The end of width to consider in calculation should exclude PAD_X, PAD_Y and PAD_Z - const int pool_end_x = std::min(pool_end_x_t, input_dim_w - in_idx_width); - const int pool_end_y = std::min(pool_end_y_t, input_dim_h - in_idx_height); - const int pool_end_z = std::min(pool_end_z_t, input_dim_d - in_idx_depth); - - const uint8_t *in_ptr_n = in_ptr_start + id[4] * n_stride; - - // Calculate scale - const float scale = calculate_avg_scale_pool3d(pool_info.exclude_padding, id, pool_size_x, pool_size_y, pool_size_z, upper_bound_w, upper_bound_h, upper_bound_d, pool_pad_left, - pool_pad_top, pool_pad_front, pool_stride_x, - pool_stride_y, pool_stride_z); - - int x_off = window_start_x; - - for(; x_off <= (window_end_x - window_step_x); x_off += window_step_x) // C - { - // Perform pooling - vres = wrapper::vdup_n(static_cast<T>(0.0f), tag_type()); - for(int z = pool_start_z; z < pool_end_z; ++z) - { - const uint8_t *in_ptr_z = in_ptr_n + (z + in_idx_depth) * w_stride; - for(int y = pool_start_y; y < pool_end_y; ++y) - { - const uint8_t *in_ptr_y = in_ptr_z + (y + in_idx_height) * z_stride; - for(int x = pool_start_x; x < pool_end_x; ++x) - { - const uint8_t *in_ptr_x = in_ptr_y + (x + in_idx_width) * y_stride; - const vector_type data = wrapper::vloadq(reinterpret_cast<const T *>(in_ptr_x) + x_off); - vres = wrapper::vmla(vres, data, data); - } - } - } - - const vector_type scale_v = wrapper::vdup_n(static_cast<T>(scale), tag_type()); - - // Divide by scale - vres = wrapper::vmul(vres, scale_v); - - // Calculate square-root - vres = wrapper::vinv(wrapper::vinvsqrt(vres)); - - // Store result - wrapper::vstore(reinterpret_cast<T *>(out.ptr()) + x_off, vres); - } - - // Left-overs loop - for(; x_off < window_end_x; ++x_off) - { - T res(0); - - for(int z = pool_start_z; z < pool_end_z; ++z) - { - const uint8_t *in_ptr_z = in_ptr_n + (z + in_idx_depth) * w_stride; - for(int y = pool_start_y; y < pool_end_y; ++y) - { - const uint8_t *in_ptr_y = in_ptr_z + (y + in_idx_height) * z_stride; - for(int x = pool_start_x; x < pool_end_x; ++x) - { - const uint8_t *in_ptr_x = in_ptr_y + (x + in_idx_width) * y_stride; - const T data = *(reinterpret_cast<const T *>(in_ptr_x) + x_off); - res += data * data; - } - } - } - - // Divide by scale - res *= scale; - - // Square root - res = std::sqrt(res); - - // Store result - *(reinterpret_cast<T *>(out.ptr()) + x_off) = res; - } - }, - out); -} -} // namespace - -template <typename T> -void poolingMxNxD_fp_neon_ndhwc(const ITensor *src, ITensor *dst0, Pooling3dLayerInfo &pool_info, const Window &window) -{ - const int window_start_x = window.x().start(); - const int window_end_x = window.x().end(); - constexpr int window_step_x = 16 / sizeof(T); - Window window_out = window; - - // Needed to handle loop left-over - window_out.set(Window::DimX, Window::Dimension(0, 1, 1)); - - switch(pool_info.pool_type) - { - case PoolingType::MAX: - max_poolingMxNxD_fp_neon_ndhwc<T>(src, dst0, pool_info, window_out, window_start_x, window_end_x, window_step_x); - break; - case PoolingType::AVG: - avg_poolingMxNxD_fp_neon_ndhwc<T>(src, dst0, pool_info, window_out, window_start_x, window_end_x, window_step_x); - break; - case PoolingType::L2: - l2_poolingMxNxD_fp_neon_ndhwc<T>(src, dst0, pool_info, window_out, window_start_x, window_end_x, window_step_x); - break; - default: - ARM_COMPUTE_ERROR("Pool operation not supported"); - } -} - -template <typename T> -void poolingMxNxD_q8_neon_ndhwc(const ITensor *src, ITensor *dst0, Pooling3dLayerInfo &pool_info, const Window &window) -{ - constexpr int window_step_x = 16; - Window window_out = window; - - // Needed to handle loop left-over - window_out.set(Window::DimX, Window::Dimension(0, 1, 1)); - - switch(pool_info.pool_type) - { - case PoolingType::MAX: - max_poolingMxNxD_q8_neon_ndhwc<T>(src, dst0, pool_info, window_out, window_step_x); - break; - case PoolingType::AVG: - avg_poolingMxNxD_q8_neon_ndhwc<T>(src, dst0, pool_info, window_out, window_step_x); - break; - default: - ARM_COMPUTE_ERROR("Pool operation not supported"); - } -} - -template void poolingMxNxD_fp_neon_ndhwc<float>(const ITensor *src, ITensor *dst0, Pooling3dLayerInfo &pool_info, const Window &window); -#if defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) && defined(ENABLE_FP16_KERNELS) -template void poolingMxNxD_fp_neon_ndhwc<float16_t>(const ITensor *src, ITensor *dst0, Pooling3dLayerInfo &pool_info, const Window &window); -#endif /* defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) && defined(ENABLE_FP16_KERNELS) */ -template void poolingMxNxD_q8_neon_ndhwc<uint8_t>(const ITensor *src, ITensor *dst0, Pooling3dLayerInfo &pool_info, const Window &window); -template void poolingMxNxD_q8_neon_ndhwc<int8_t>(const ITensor *src, ITensor *dst0, Pooling3dLayerInfo &pool_info, const Window &window); -} // namespace cpu -} // namespace arm_compute |