diff options
Diffstat (limited to 'src/cpu/kernels/directconv2d/nchw/all.cpp')
| -rw-r--r-- | src/cpu/kernels/directconv2d/nchw/all.cpp | 220 |
1 files changed, 88 insertions, 132 deletions
diff --git a/src/cpu/kernels/directconv2d/nchw/all.cpp b/src/cpu/kernels/directconv2d/nchw/all.cpp index 218a4b7ee4..84f5eeff5a 100644 --- a/src/cpu/kernels/directconv2d/nchw/all.cpp +++ b/src/cpu/kernels/directconv2d/nchw/all.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2022 Arm Limited. + * Copyright (c) 2022-2023 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -32,6 +32,9 @@ #include "src/core/helpers/WindowHelpers.h" #include "src/core/NEON/kernels/detail/NEDirectConvolutionDetail.h" #include "src/core/NEON/wrapper/wrapper.h" +#include "src/cpu/kernels/directconv2d/impl.h" +#include "src/cpu/kernels/directconv2d/list.h" +#include "src/cpu/kernels/directconv2d/nchw/impl.h" #include "src/cpu/kernels/directconv2d/nhwc/neon/impl.h" #include <algorithm> @@ -42,149 +45,102 @@ namespace cpu { namespace kernels { -template <typename T> -void convolve_nchw( - const Window &window, const ITensor *src, const ITensor *weights, ITensor *dst, const PadStrideInfo &conv_info); - -#if defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) && defined(ENABLE_FP16_KERNELS) -void neon_fp16_nchw_directconv2d( - const Window &window, const ITensor *src, const ITensor *weights, ITensor *dst, const PadStrideInfo &conv_info) -{ - convolve_nchw<float16_t>(window, src, weights, dst, conv_info); -} -#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ - void neon_fp32_nchw_directconv2d( const Window &window, const ITensor *src, const ITensor *weights, ITensor *dst, const PadStrideInfo &conv_info) { convolve_nchw<float>(window, src, weights, dst, conv_info); } -template <typename T> -void convolve_nchw( - const Window &window, const ITensor *src, const ITensor *weights, ITensor *dst, const PadStrideInfo &conv_info) +void run_im2col_fp32_nchw_pad(const ITensor *src, + ITensor *dst, + const Window &window, + DataLayout data_layout, + const PadStrideInfo &conv_info, + std::pair<unsigned int, unsigned int> convolved_dims, + const Size2D &kernel_dims, + const Size2D &dilation, + uint32_t input_pad_right, + bool has_bias) { - ARM_COMPUTE_UNUSED(conv_info); - - // Declare useful types - using vtype = wrapper::traits::neon_bitvector<T, wrapper::traits::BitWidth::W128>; - using vector_type = typename vtype::type; - using tag_type = typename vtype::tag_type; - - // Scalar quantities - const int element_size = src->info()->element_size(); - const int input_stride_w = src->info()->strides_in_bytes()[0] / element_size; - const int input_stride_h = src->info()->strides_in_bytes()[1] / element_size; - const int input_stride_c = src->info()->strides_in_bytes()[2] / element_size; - const int input_stride_n = src->info()->strides_in_bytes()[3] / element_size; - - const int input_dim_w = src->info()->dimension(0); - const int input_dim_h = src->info()->dimension(1); - - const int output_stride_c = dst->info()->strides_in_bytes()[2]; - - const unsigned int kernel_stride_w = weights->info()->strides_in_bytes().x() / element_size; - const unsigned int kernel_stride_h = weights->info()->strides_in_bytes().y() / element_size; - const unsigned int kernel_stride_c = weights->info()->strides_in_bytes().z() / element_size; - - const int kernel_dim_w = weights->info()->dimension(0); - const int kernel_dim_h = weights->info()->dimension(1); - - const int conv_pad_top = conv_info.pad_top(); - const int conv_pad_left = conv_info.pad_left(); - const int conv_stride_w = std::get<0>(conv_info.stride()); - const int conv_stride_h = std::get<1>(conv_info.stride()); - - // Setup input window for the output iterator - Window window_out = window; - window_out.set(Window::DimZ, Window::Dimension(0, 1, 1)); - - // Setup input window for the weights iterator - Window window_w = calculate_max_window(*weights->info(), Steps()); - window_w.set(Window::DimX, Window::Dimension(0, 1, 1)); - window_w.set(Window::DimY, Window::Dimension(0, 1, 1)); - window_w.set(Window::DimZ, Window::Dimension(0, 1, 1)); - - Iterator out(dst, window_out); - Iterator wei(weights, window_w); - - constexpr int num_elems_read_per_iteration = 16 / sizeof(T); - - execute_window_loop( - window_out, - [&](const Coordinates &id) - { - // We are computing the theoretical starting input starting points - const int in_w_start_t = static_cast<int>(id.x()) * conv_stride_w - conv_pad_left; - const int in_h_start_t = static_cast<int>(id.y()) * conv_stride_h - conv_pad_top; - const int in_w_end_t = in_w_start_t + kernel_dim_w; - const int in_h_end_t = in_h_start_t + kernel_dim_h; - - // We are computing the valid initial and ending input points by checking the borders - const int in_w_start = std::max(in_w_start_t, 0); - const int in_h_start = std::max(in_h_start_t, 0); - const int in_w_end = std::min(in_w_end_t, input_dim_w); - const int in_h_end = std::min(in_h_end_t, input_dim_h); - - // We use the input points to select the valid weight points to use - const int wei_w_start = in_w_start - in_w_start_t; - const int wei_h_start = in_h_start - in_h_start_t; - const int wei_h_end = kernel_dim_h - (in_h_end_t - in_h_end); + arm_compute::cpu::kernels::run_im2col<float, true, true>(src, dst, window, data_layout, conv_info, convolved_dims, + kernel_dims, dilation, input_pad_right, has_bias); +} - const int index_c_end = weights->info()->dimension(2); - const T *const in_ptr_start = - reinterpret_cast<const T *>(src->buffer() + src->info()->offset_first_element_in_bytes()) + - id[3] * input_stride_n; - execute_window_loop( - window_w, - [&](const Coordinates &id_w) - { - const T *const weights_ptr_start = reinterpret_cast<const T *>(wei.ptr()); - uint8_t *out_ptr = out.ptr() + id_w[3] * output_stride_c; - T out_temp = static_cast<T>(0); +void run_im2col_fp32_nchw_nopad(const ITensor *src, + ITensor *dst, + const Window &window, + DataLayout data_layout, + const PadStrideInfo &conv_info, + std::pair<unsigned int, unsigned int> convolved_dims, + const Size2D &kernel_dims, + const Size2D &dilation, + uint32_t input_pad_right, + bool has_bias) +{ + arm_compute::cpu::kernels::run_im2col<float, false, true>(src, dst, window, data_layout, conv_info, convolved_dims, + kernel_dims, dilation, input_pad_right, has_bias); +} - for (int index_wei_c = 0, index_in_c = 0; index_wei_c < index_c_end; ++index_wei_c, ++index_in_c) - { - const T *const in_ptr_row_0 = in_ptr_start + index_in_c * input_stride_c; - const T *const weights_ptr_row_0 = weights_ptr_start + index_wei_c * kernel_stride_c; - for (int index_wei_h = wei_h_start, index_in_h = in_h_start; index_wei_h < wei_h_end; - ++index_wei_h, ++index_in_h) - { - const T *in_ptr_row = in_ptr_row_0 + index_in_h * input_stride_h; - const T *weights_ptr_row = weights_ptr_row_0 + index_wei_h * kernel_stride_h; - int index_w = in_w_start; - int index_wei_w = wei_w_start; - vector_type out_temp_vec = wrapper::vdup_n(static_cast<T>(0), tag_type()); - for (; index_w <= ((in_w_end - num_elems_read_per_iteration)); - index_w += num_elems_read_per_iteration, index_wei_w += num_elems_read_per_iteration) - { - const auto src_vec = wrapper::vloadq(in_ptr_row + index_w * input_stride_w); - const auto w_vec = wrapper::vloadq(weights_ptr_row + index_wei_w * kernel_stride_w); - out_temp_vec = wrapper::vmla(out_temp_vec, w_vec, src_vec); - } - out_temp += vreduce(out_temp_vec); - for (; index_w < in_w_end; ++index_w, ++index_wei_w) - { - const auto src_val = *(in_ptr_row + index_w * input_stride_w); - const auto w_val = *(weights_ptr_row + index_wei_w * kernel_stride_w); - out_temp += src_val * w_val; - } - } - } - *(reinterpret_cast<T *>(out_ptr)) = out_temp; - }, - wei); - }, - out); +void run_im2col_qasymm8_nchw_pad(const ITensor *src, + ITensor *dst, + const Window &window, + DataLayout data_layout, + const PadStrideInfo &conv_info, + std::pair<unsigned int, unsigned int> convolved_dims, + const Size2D &kernel_dims, + const Size2D &dilation, + uint32_t input_pad_right, + bool has_bias) +{ + arm_compute::cpu::kernels::run_im2col<qasymm8_t, true, true>( + src, dst, window, data_layout, conv_info, convolved_dims, kernel_dims, dilation, input_pad_right, has_bias); } -#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC -template void convolve_nchw<float16_t>( - const Window &window, const ITensor *src, const ITensor *weights, ITensor *dst, const PadStrideInfo &conv_info); -#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ +void run_im2col_qasymm8_nchw_nopad(const ITensor *src, + ITensor *dst, + const Window &window, + DataLayout data_layout, + const PadStrideInfo &conv_info, + std::pair<unsigned int, unsigned int> convolved_dims, + const Size2D &kernel_dims, + const Size2D &dilation, + uint32_t input_pad_right, + bool has_bias) +{ + arm_compute::cpu::kernels::run_im2col<qasymm8_t, false, true>( + src, dst, window, data_layout, conv_info, convolved_dims, kernel_dims, dilation, input_pad_right, has_bias); +} +#if defined(ARM_COMPUTE_ENABLE_BF16) +void run_im2col_bf16_nchw_pad(const ITensor *src, + ITensor *dst, + const Window &window, + DataLayout data_layout, + const PadStrideInfo &conv_info, + std::pair<unsigned int, unsigned int> convolved_dims, + const Size2D &kernel_dims, + const Size2D &dilation, + uint32_t input_pad_right, + bool has_bias) +{ + arm_compute::cpu::kernels::run_im2col<bfloat16, true, true>( + src, dst, window, data_layout, conv_info, convolved_dims, kernel_dims, dilation, input_pad_right, has_bias); +} -template void convolve_nchw<float>( - const Window &window, const ITensor *src, const ITensor *weights, ITensor *dst, const PadStrideInfo &conv_info); +void run_im2col_bf16_nchw_nopad(const ITensor *src, + ITensor *dst, + const Window &window, + DataLayout data_layout, + const PadStrideInfo &conv_info, + std::pair<unsigned int, unsigned int> convolved_dims, + const Size2D &kernel_dims, + const Size2D &dilation, + uint32_t input_pad_right, + bool has_bias) +{ + arm_compute::cpu::kernels::run_im2col<bfloat16, false, true>( + src, dst, window, data_layout, conv_info, convolved_dims, kernel_dims, dilation, input_pad_right, has_bias); +} +#endif /* defined(ARM_COMPUTE_ENABLE_BF16) */ } // namespace kernels } // namespace cpu |