From 8af2dd6eb230f2205070dce50c2a22bdf2d55e46 Mon Sep 17 00:00:00 2001 From: Michele Di Giorgio Date: Mon, 19 Jun 2017 15:19:29 +0100 Subject: COMPMID-403: Add 7x7 NEON Pooling support. Change-Id: I2f1e808884f215b9cf79e1f2015ef901e66b3e5f Reviewed-on: http://mpd-gerrit.cambridge.arm.com/78146 Reviewed-by: Georgios Pinitas Tested-by: Kaizen --- src/core/NEON/kernels/NEPoolingLayerKernel.cpp | 125 ++++++++++++++++++++++--- 1 file changed, 111 insertions(+), 14 deletions(-) (limited to 'src/core/NEON/kernels/NEPoolingLayerKernel.cpp') diff --git a/src/core/NEON/kernels/NEPoolingLayerKernel.cpp b/src/core/NEON/kernels/NEPoolingLayerKernel.cpp index 30b67b64b9..8991e9b9ee 100644 --- a/src/core/NEON/kernels/NEPoolingLayerKernel.cpp +++ b/src/core/NEON/kernels/NEPoolingLayerKernel.cpp @@ -37,6 +37,7 @@ #include #include #include +#include #include #include @@ -93,11 +94,15 @@ 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 supported_pool_sizes = { 2, 3, 7 }; + ARM_COMPUTE_UNUSED(supported_pool_sizes); + ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QS8, DataType::F32); ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::QS8, DataType::F32); ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); ARM_COMPUTE_ERROR_ON_MISMATCHING_FIXED_POINT(input, output); - ARM_COMPUTE_ERROR_ON(2 != pool_size && 3 != pool_size); + 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(pool_pad_x >= pool_size || pool_pad_y >= pool_size); ARM_COMPUTE_ERROR_ON(input->info()->data_type() == DataType::QS8 && pool_type == PoolingType::AVG && input->info()->fixed_point_position() > 6); ARM_COMPUTE_ERROR_ON(input->info()->data_type() == DataType::QS8 && pool_stride_x > 2); @@ -118,12 +123,35 @@ void NEPoolingLayerKernel::configure(const ITensor *input, ITensor *output, cons switch(input->info()->data_type()) { case DataType::QS8: - num_elems_read_per_iteration = 16; - num_elems_processed_per_iteration = (pool_size == 2) ? 8 : 7; - num_elems_horizontal_window = 8; + num_elems_read_per_iteration = 16; + switch(pool_size) + { + case 2: + num_elems_processed_per_iteration = 8; + break; + case 3: + num_elems_processed_per_iteration = 7; + break; + default: + ARM_COMPUTE_ERROR("Pooling size not supported"); + } + num_elems_horizontal_window = 8; break; case DataType::F32: - num_elems_read_per_iteration = (pool_size == 2) ? 2 : 4; // We use vload4 for pooling3 + switch(pool_size) + { + case 2: + num_elems_read_per_iteration = 2; + break; + case 3: + num_elems_read_per_iteration = 4; // We use vload4 for pooling3 + break; + case 7: + num_elems_read_per_iteration = 8; // We use vload8 for pooling7 + break; + default: + ARM_COMPUTE_ERROR("Pooling size not supported"); + } num_elems_processed_per_iteration = 1; num_elems_horizontal_window = 1; break; @@ -169,6 +197,9 @@ void NEPoolingLayerKernel::configure(const ITensor *input, ITensor *output, cons _func = (PoolingType::AVG == pool_type) ? &NEPoolingLayerKernel::pooling3_f32 : &NEPoolingLayerKernel::pooling3_f32; } break; + case 7: + _func = (PoolingType::AVG == pool_type) ? &NEPoolingLayerKernel::pooling7_f32 : &NEPoolingLayerKernel::pooling7_f32; + break; default: ARM_COMPUTE_ERROR("Unsupported pooling size"); break; @@ -234,15 +265,18 @@ void NEPoolingLayerKernel::pooling2_f32(const Window &window_input, const Window Iterator input(_input, window_input); Iterator output(_output, window); - constexpr int pool_size = 2; - int pool_pad_x, pool_pad_y, pool_stride_x, pool_stride_y = 0; + constexpr int pool_size = 2; + 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; - const unsigned char *const input_top_ptr = _input->ptr_to_element(Coordinates(-static_cast(pool_pad_x), -static_cast(pool_pad_y))); - const unsigned char *const input_bottom_ptr = _input->ptr_to_element(Coordinates(-static_cast(pool_pad_x), -static_cast(pool_pad_y) + 1)); + const uint8_t *const input_top_ptr = _input->ptr_to_element(Coordinates(-static_cast(pool_pad_x), -static_cast(pool_pad_y))); + const uint8_t *const input_bottom_ptr = _input->ptr_to_element(Coordinates(-static_cast(pool_pad_x), -static_cast(pool_pad_y) + 1)); execute_window_loop(window, [&](const Coordinates & id) { @@ -348,16 +382,19 @@ void NEPoolingLayerKernel::pooling3_f32(const Window &window_input, const Window Iterator input(_input, window_input); Iterator output(_output, window); - constexpr const int pool_size = 3; - int pool_pad_x, pool_pad_y, pool_stride_x, pool_stride_y = 0; + constexpr const int pool_size = 3; + 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; - const unsigned char *const input_top_ptr = _input->ptr_to_element(Coordinates(-static_cast(pool_pad_x), -static_cast(pool_pad_y))); - const unsigned char *const input_middle_ptr = _input->ptr_to_element(Coordinates(-static_cast(pool_pad_x), -static_cast(pool_pad_y) + 1)); - const unsigned char *const input_bottom_ptr = _input->ptr_to_element(Coordinates(-static_cast(pool_pad_x), -static_cast(pool_pad_y) + 2)); + const uint8_t *const input_top_ptr = _input->ptr_to_element(Coordinates(-static_cast(pool_pad_x), -static_cast(pool_pad_y))); + const uint8_t *const input_middle_ptr = _input->ptr_to_element(Coordinates(-static_cast(pool_pad_x), -static_cast(pool_pad_y) + 1)); + const uint8_t *const input_bottom_ptr = _input->ptr_to_element(Coordinates(-static_cast(pool_pad_x), -static_cast(pool_pad_y) + 2)); execute_window_loop(window, [&](const Coordinates & id) { @@ -387,6 +424,66 @@ void NEPoolingLayerKernel::pooling3_f32(const Window &window_input, const Window input, output); } +template +void NEPoolingLayerKernel::pooling7_f32(const Window &window_input, const Window &window) +{ + Iterator input(_input, window_input); + Iterator output(_output, window); + + constexpr const int pool_size = 7; + 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; + + std::array input_ptrs{ {} }; + for(int i = 0; i < pool_size; ++i) + { + input_ptrs[i] = _input->ptr_to_element(Coordinates(-static_cast(pool_pad_x), -static_cast(pool_pad_y) + i)); + } + + execute_window_loop(window, [&](const Coordinates & id) + { + float32x2_t res = {}; + if(pooling_type == PoolingType::AVG) + { + // 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); + const float32x2_t scale_v = vdup_n_f32(scale); + + // Perform pooling + float32x4x2_t data = vld2q_f32(reinterpret_cast(input_ptrs[0] + input.offset())); + 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(input_ptrs[i] + input.offset())); + sum_data = vaddq_f32(sum_data, data.val[0]); + sum_data = vaddq_f32(sum_data, vsetq_lane_f32(0.f, data.val[1], 3)); + } + res = vpadd_f32(vget_high_f32(sum_data), vget_low_f32(sum_data)); + res = vmul_f32(vpadd_f32(res, res), scale_v); + } + else + { + float32x4x2_t max_data = vld2q_f32(reinterpret_cast(input_ptrs[0] + input.offset())); + for(int i = 1; i < pool_size; ++i) + { + const float32x4x2_t data = vld2q_f32(reinterpret_cast(input_ptrs[i] + input.offset())); + max_data = vmax2q_f32(max_data, data); + } + res = vpmax_f32(vget_high_f32(vsetq_lane_f32(-std::numeric_limits::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(res, res); + } + *(reinterpret_cast(output.ptr())) = vget_lane_f32(res, 0); + }, + input, output); +} + void NEPoolingLayerKernel::run(const Window &window) { ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); -- cgit v1.2.1