/* * Copyright (c) 2019 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.hpp" #include "input.hpp" namespace winograd { template <> void InputTransform<1, 8, float, float, WinogradRoots::Integers>::transform_tile( const int n_channels, const float* const input_base, const int, // We don't need to stride over rows const int input_col_stride, float* outptr, const int matrix_stride ) { constexpr int inner_tile_cols = 8; // Get pointers into the input tile const float *x_ptrs[inner_tile_cols]; for (int j = 0, xj = 0; j < inner_tile_cols; j++, xj++) { x_ptrs[j] = input_base + xj*input_col_stride; } // Vectors used/computed in this kernel. float x[inner_tile_cols]; float U[inner_tile_cols]; for (int j = 0; j < inner_tile_cols; j++) { x[j] = 0.0f; } // Perform the Winograd input transformation for each channel in the input // tensor. int channels_remaining = n_channels; #ifdef _arm_any_ for (; channels_remaining >= 4; channels_remaining -= 4) { float32x4_t x[inner_tile_cols], U[inner_tile_cols]; for (int j = 0; j < inner_tile_cols; j++) { x[j] = vdupq_n_f32(0.0f); } // Load x for (int j = 0; j < inner_tile_cols; j++) { x[j] = vld1q_f32(x_ptrs[j]); x_ptrs[j] += 4; } // Compute U = x . X U[0] = vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmulq_n_f32(x[6], 1), x[2], 49), x[4], -14), x[0], -36); U[1] = vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmulq_n_f32(x[6], 1), x[2], 36), x[3], 13), x[4], -13), x[1], -36), x[5], -1); U[2] = vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmulq_n_f32(x[6], 1), x[5], 1), x[2], 36), x[1], 36), x[4], -13), x[3], -13); U[3] = vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmulq_n_f32(x[6], 1), x[3], 20), x[2], 9), x[5], -2), x[4], -10), x[1], -18); U[4] = vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmulq_n_f32(x[6], 1), x[1], 18), x[2], 9), x[5], 2), x[4], -10), x[3], -20); U[5] = vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmulq_n_f32(x[6], 1), x[3], 15), x[2], 4), x[5], -3), x[4], -5), x[1], -12); U[6] = vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmulq_n_f32(x[6], 1), x[1], 12), x[2], 4), x[5], 3), x[4], -5), x[3], -15); U[7] = vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmulq_n_f32(x[7], 1), x[3], 49), x[5], -14), x[1], -36); // Store the transformed vector for (int j = 0; j < inner_tile_cols; j++) { vst1q_f32(outptr + j*matrix_stride, U[j]); } outptr += 4; } for (; channels_remaining >= 2; channels_remaining -= 2) { float32x2_t x[inner_tile_cols], U[inner_tile_cols]; for (int j = 0; j < inner_tile_cols; j++) { x[j] = vdup_n_f32(0.0f); } // Load x for (int j = 0; j < inner_tile_cols; j++) { x[j] = vld1_f32(x_ptrs[j]); x_ptrs[j] += 2; } // Compute U = x . X U[0] = vmla_n_f32(vmla_n_f32(vmla_n_f32(vmul_n_f32(x[6], 1), x[2], 49), x[4], -14), x[0], -36); U[1] = vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmul_n_f32(x[6], 1), x[2], 36), x[3], 13), x[4], -13), x[1], -36), x[5], -1); U[2] = vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmul_n_f32(x[6], 1), x[5], 1), x[2], 36), x[1], 36), x[4], -13), x[3], -13); U[3] = vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmul_n_f32(x[6], 1), x[3], 20), x[2], 9), x[5], -2), x[4], -10), x[1], -18); U[4] = vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmul_n_f32(x[6], 1), x[1], 18), x[2], 9), x[5], 2), x[4], -10), x[3], -20); U[5] = vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmul_n_f32(x[6], 1), x[3], 15), x[2], 4), x[5], -3), x[4], -5), x[1], -12); U[6] = vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmul_n_f32(x[6], 1), x[1], 12), x[2], 4), x[5], 3), x[4], -5), x[3], -15); U[7] = vmla_n_f32(vmla_n_f32(vmla_n_f32(vmul_n_f32(x[7], 1), x[3], 49), x[5], -14), x[1], -36); // Store the transformed vector for (int j = 0; j < inner_tile_cols; j++) { vst1_f32(outptr + j*matrix_stride, U[j]); } outptr += 2; } #endif // _arm_any_ for (; channels_remaining; channels_remaining--) { // Load x for (int j = 0; j < inner_tile_cols; j++) { x[j] = *(x_ptrs[j]++); } // Compute U = x . X U[0] = x[0]*-36 + x[4]*-14 + x[2]*49 + x[6]*1; U[1] = x[5]*-1 + x[1]*-36 + x[4]*-13 + x[3]*13 + x[2]*36 + x[6]*1; U[2] = x[3]*-13 + x[4]*-13 + x[1]*36 + x[2]*36 + x[5]*1 + x[6]*1; U[3] = x[1]*-18 + x[4]*-10 + x[5]*-2 + x[2]*9 + x[3]*20 + x[6]*1; U[4] = x[3]*-20 + x[4]*-10 + x[5]*2 + x[2]*9 + x[1]*18 + x[6]*1; U[5] = x[1]*-12 + x[4]*-5 + x[5]*-3 + x[2]*4 + x[3]*15 + x[6]*1; U[6] = x[3]*-15 + x[4]*-5 + x[5]*3 + x[2]*4 + x[1]*12 + x[6]*1; U[7] = x[1]*-36 + x[5]*-14 + x[3]*49 + x[7]*1; // Store the transformed vector for (int j = 0; j < inner_tile_cols; j++) { *(outptr + j*matrix_stride) = U[j]; } outptr++; } } template class InputTransform<1, 8, float, float, WinogradRoots::Integers>; template class InputTransform<8, 1, float, float, WinogradRoots::Integers>; } // namespace winograd