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-rw-r--r--src/core/NEON/kernels/NELocallyConnectedMatrixMultiplyKernel.cpp389
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diff --git a/src/core/NEON/kernels/NELocallyConnectedMatrixMultiplyKernel.cpp b/src/core/NEON/kernels/NELocallyConnectedMatrixMultiplyKernel.cpp
deleted file mode 100644
index 467546a5d3..0000000000
--- a/src/core/NEON/kernels/NELocallyConnectedMatrixMultiplyKernel.cpp
+++ /dev/null
@@ -1,389 +0,0 @@
-/*
- * Copyright (c) 2017-2019 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_compute/core/NEON/kernels/NELocallyConnectedMatrixMultiplyKernel.h"
-
-#include "arm_compute/core/CPP/Validate.h"
-#include "arm_compute/core/Error.h"
-#include "arm_compute/core/Helpers.h"
-#include "arm_compute/core/IAccessWindow.h"
-#include "arm_compute/core/ITensor.h"
-#include "arm_compute/core/NEON/NEFixedPoint.h"
-#include "arm_compute/core/TensorInfo.h"
-#include "arm_compute/core/Types.h"
-#include "arm_compute/core/Utils.h"
-#include "arm_compute/core/Validate.h"
-#include "arm_compute/core/Window.h"
-
-#include <arm_neon.h>
-#include <cstddef>
-#include <cstdint>
-#include <tuple>
-
-namespace arm_compute
-{
-class Coordinates;
-
-namespace
-{
-void vector_matrix_multiply_f16(const ITensor *input0, const ITensor *input1, ITensor *output, const Window &window, const ThreadInfo &info)
-{
-#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
- const auto width_matrix_b = static_cast<int>(output->info()->dimension(0));
- const auto in_b_stride = static_cast<int>(input1->info()->strides_in_bytes()[1] / data_size_from_type(input1->info()->data_type()));
- const auto num_elems_vec_a = static_cast<int>(input0->info()->dimension(0));
-
- // The implementation computes 16 elements per iteration
- const int window_start_x = 16 * info.thread_id;
- const int window_step_x = 16 * info.num_threads;
- // Make sure (window_end_x - window_start_x) is a multiple of window_step_x
- const int window_end_x = ceil_to_multiple(width_matrix_b - window_start_x, window_step_x) + window_start_x;
-
- Window win_out(window);
- win_out.set(Window::DimX, Window::Dimension(window_start_x, window_end_x, window_step_x));
-
- Window win_a(window);
- win_a.set(Window::DimX, Window::Dimension(0, 1, 1));
-
- Iterator ina(input0, win_a);
- Iterator out(output, win_out);
-
- execute_window_loop(win_out, [&](const Coordinates & id)
- {
- if(id.x() > width_matrix_b)
- {
- return;
- }
-
- float16x8_t acc0 = vdupq_n_f16(0.f);
- float16x8_t acc1 = vdupq_n_f16(0.f);
- float16x8_t acc2 = vdupq_n_f16(0.f);
- float16x8_t acc3 = vdupq_n_f16(0.f);
-
- auto vec_a = reinterpret_cast<const float16_t *>(ina.ptr());
- auto matrix_b = reinterpret_cast<const float16_t *>(input1->ptr_to_element(Coordinates(id[0], 0, id[1])));
-
- const float16_t *vec_a_end_addr = vec_a + num_elems_vec_a;
-
- for(; vec_a <= (vec_a_end_addr - 4);)
- {
- const float16x4_t a0l = vld1_f16(vec_a);
-
- float16x8_t b00 = vld1q_f16(matrix_b);
- float16x8_t b01 = vld1q_f16(matrix_b + 8 + 0 * in_b_stride);
- float16x8_t b02 = vld1q_f16(matrix_b + 16 + 0 * in_b_stride);
- float16x8_t b03 = vld1q_f16(matrix_b + 24 + 0 * in_b_stride);
-
- float16x8_t b10 = vld1q_f16(matrix_b + 0 + 1 * in_b_stride);
- float16x8_t b11 = vld1q_f16(matrix_b + 8 + 1 * in_b_stride);
- float16x8_t b12 = vld1q_f16(matrix_b + 16 + 1 * in_b_stride);
- float16x8_t b13 = vld1q_f16(matrix_b + 24 + 1 * in_b_stride);
-
- acc0 = vaddq_f16(acc0, vmulq_lane_f16(b00, a0l, 0));
- acc1 = vaddq_f16(acc1, vmulq_lane_f16(b01, a0l, 0));
- acc2 = vaddq_f16(acc2, vmulq_lane_f16(b02, a0l, 0));
- acc3 = vaddq_f16(acc3, vmulq_lane_f16(b03, a0l, 0));
- acc0 = vaddq_f16(acc0, vmulq_lane_f16(b10, a0l, 1));
- acc1 = vaddq_f16(acc1, vmulq_lane_f16(b11, a0l, 1));
- acc2 = vaddq_f16(acc2, vmulq_lane_f16(b12, a0l, 1));
- acc3 = vaddq_f16(acc3, vmulq_lane_f16(b13, a0l, 1));
-
- matrix_b += 2 * in_b_stride;
-
- b00 = vld1q_f16(matrix_b);
- b01 = vld1q_f16(matrix_b + 8 + 0 * in_b_stride);
- b02 = vld1q_f16(matrix_b + 16 + 0 * in_b_stride);
- b03 = vld1q_f16(matrix_b + 24 + 0 * in_b_stride);
- b10 = vld1q_f16(matrix_b + 0 + 1 * in_b_stride);
- b11 = vld1q_f16(matrix_b + 8 + 1 * in_b_stride);
- b12 = vld1q_f16(matrix_b + 16 + 1 * in_b_stride);
- b13 = vld1q_f16(matrix_b + 24 + 1 * in_b_stride);
-
- acc0 = vaddq_f16(acc0, vmulq_lane_f16(b00, a0l, 2));
- acc1 = vaddq_f16(acc1, vmulq_lane_f16(b01, a0l, 2));
- acc2 = vaddq_f16(acc2, vmulq_lane_f16(b02, a0l, 2));
- acc3 = vaddq_f16(acc3, vmulq_lane_f16(b03, a0l, 2));
- acc0 = vaddq_f16(acc0, vmulq_lane_f16(b10, a0l, 3));
- acc1 = vaddq_f16(acc1, vmulq_lane_f16(b11, a0l, 3));
- acc2 = vaddq_f16(acc2, vmulq_lane_f16(b12, a0l, 3));
- acc3 = vaddq_f16(acc3, vmulq_lane_f16(b13, a0l, 3));
-
- vec_a += 4;
- matrix_b += 2 * in_b_stride;
- }
-
- for(; vec_a < vec_a_end_addr;)
- {
- const float16_t a0 = *vec_a;
- const float16x8_t b00 = vld1q_f16(matrix_b);
- const float16x8_t b01 = vld1q_f16(matrix_b + 8 + 0 * in_b_stride);
- const float16x8_t b02 = vld1q_f16(matrix_b + 16 + 0 * in_b_stride);
- const float16x8_t b03 = vld1q_f16(matrix_b + 24 + 0 * in_b_stride);
-
- acc0 = vaddq_f16(acc0, vmulq_n_f16(b00, a0));
- acc1 = vaddq_f16(acc1, vmulq_n_f16(b01, a0));
- acc2 = vaddq_f16(acc2, vmulq_n_f16(b02, a0));
- acc3 = vaddq_f16(acc3, vmulq_n_f16(b03, a0));
-
- vec_a += 1;
- matrix_b += in_b_stride;
- }
-
- const auto vec_out = reinterpret_cast<float16_t *>(out.ptr());
-
- vst1q_f16(vec_out + 0, acc0);
- vst1q_f16(vec_out + 8, acc1);
- vst1q_f16(vec_out + 16, acc2);
- vst1q_f16(vec_out + 24, acc3);
- },
- ina, out);
-#else /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
- ARM_COMPUTE_UNUSED(input0);
- ARM_COMPUTE_UNUSED(input1);
- ARM_COMPUTE_UNUSED(output);
- ARM_COMPUTE_UNUSED(window);
- ARM_COMPUTE_UNUSED(info);
- ARM_COMPUTE_ERROR("Not supported, recompile with -march=armv8.2-a+fp16+simd.");
-#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
-}
-
-void vector_matrix_multiply_f32(const ITensor *input0, const ITensor *input1, ITensor *output, const Window &window, const ThreadInfo &info)
-{
- const auto width_matrix_b = static_cast<int>(output->info()->dimension(0));
- const auto in_b_stride = static_cast<int>(input1->info()->strides_in_bytes()[1] / data_size_from_type(input1->info()->data_type()));
- const auto num_elems_vec_a = static_cast<int>(input0->info()->dimension(0));
-
- // The implementation computes 16 elements per iteration
- const int window_start_x = 16 * info.thread_id;
- const int window_step_x = 16 * info.num_threads;
- // Make sure (window_end_x - window_start_x) is a multiple of window_step_x
- const int window_end_x = ceil_to_multiple(width_matrix_b - window_start_x, window_step_x) + window_start_x;
-
- Window win_out(window);
- win_out.set(Window::DimX, Window::Dimension(window_start_x, window_end_x, window_step_x));
-
- Window win_a(window);
- win_a.set(Window::DimX, Window::Dimension(0, 0, 0));
-
- Iterator ina(input0, win_a);
- Iterator out(output, win_out);
-
- execute_window_loop(win_out, [&](const Coordinates & id)
- {
- if(id.x() > width_matrix_b)
- {
- return;
- }
-
- float32x4_t acc0 = vdupq_n_f32(0.f);
- float32x4_t acc1 = vdupq_n_f32(0.f);
- float32x4_t acc2 = vdupq_n_f32(0.f);
- float32x4_t acc3 = vdupq_n_f32(0.f);
-
- auto vec_a = reinterpret_cast<const float *>(ina.ptr());
- auto matrix_b = reinterpret_cast<const float *>(input1->ptr_to_element(Coordinates(id[0], 0, id[1])));
-
-#if __arm__
- asm volatile("PLD [%0, #128*4]" ::"r"(reinterpret_cast<const uint8_t *>(vec_a)));
- asm volatile("PLD [%0, #128*4]" ::"r"(reinterpret_cast<const uint8_t *>(matrix_b)));
- asm volatile("PLD [%0, #128*4]" ::"r"(reinterpret_cast<const uint8_t *>(matrix_b + in_b_stride)));
-#endif /* __arm__ */
-
- const float *vec_a_end_addr = vec_a + num_elems_vec_a;
-
- for(; vec_a <= (vec_a_end_addr - 4);)
- {
- float32x2_t a0l = vld1_f32(vec_a);
-
- float32x4_t b00 = vld1q_f32(matrix_b + 0 + 0 * in_b_stride);
- float32x4_t b01 = vld1q_f32(matrix_b + 4 + 0 * in_b_stride);
- float32x4_t b02 = vld1q_f32(matrix_b + 8 + 0 * in_b_stride);
- float32x4_t b03 = vld1q_f32(matrix_b + 12 + 0 * in_b_stride);
-
- float32x4_t b10 = vld1q_f32(matrix_b + 0 + 1 * in_b_stride);
- float32x4_t b11 = vld1q_f32(matrix_b + 4 + 1 * in_b_stride);
- float32x4_t b12 = vld1q_f32(matrix_b + 8 + 1 * in_b_stride);
- float32x4_t b13 = vld1q_f32(matrix_b + 12 + 1 * in_b_stride);
-
-#if __arm__
- asm volatile("PLD [%0, #128*4]" ::"r"(reinterpret_cast<const uint8_t *>(vec_a)));
- asm volatile("PLD [%0, #128*1]" ::"r"(reinterpret_cast<const uint8_t *>(matrix_b + 1 * in_b_stride)));
- asm volatile("PLD [%0, #128*1]" ::"r"(reinterpret_cast<const uint8_t *>(matrix_b + 2 * in_b_stride)));
- asm volatile("PLD [%0, #128*1]" ::"r"(reinterpret_cast<const uint8_t *>(matrix_b + 3 * in_b_stride)));
- asm volatile("PLD [%0, #128*1]" ::"r"(reinterpret_cast<const uint8_t *>(matrix_b + 4 * in_b_stride)));
-#endif /* __arm__ */
-
- acc0 = vmlaq_lane_f32(acc0, b00, a0l, 0);
- acc1 = vmlaq_lane_f32(acc1, b01, a0l, 0);
- acc2 = vmlaq_lane_f32(acc2, b02, a0l, 0);
- acc3 = vmlaq_lane_f32(acc3, b03, a0l, 0);
-
- acc0 = vmlaq_lane_f32(acc0, b10, a0l, 1);
- acc1 = vmlaq_lane_f32(acc1, b11, a0l, 1);
- acc2 = vmlaq_lane_f32(acc2, b12, a0l, 1);
- acc3 = vmlaq_lane_f32(acc3, b13, a0l, 1);
-
- vec_a += 2;
- matrix_b += 2 * in_b_stride;
-
- a0l = vld1_f32(vec_a);
-
- b00 = vld1q_f32(matrix_b + 0 + 0 * in_b_stride);
- b01 = vld1q_f32(matrix_b + 4 + 0 * in_b_stride);
- b02 = vld1q_f32(matrix_b + 8 + 0 * in_b_stride);
- b03 = vld1q_f32(matrix_b + 12 + 0 * in_b_stride);
-
- b10 = vld1q_f32(matrix_b + 0 + 1 * in_b_stride);
- b11 = vld1q_f32(matrix_b + 4 + 1 * in_b_stride);
- b12 = vld1q_f32(matrix_b + 8 + 1 * in_b_stride);
- b13 = vld1q_f32(matrix_b + 12 + 1 * in_b_stride);
-
- acc0 = vmlaq_lane_f32(acc0, b00, a0l, 0);
- acc1 = vmlaq_lane_f32(acc1, b01, a0l, 0);
- acc2 = vmlaq_lane_f32(acc2, b02, a0l, 0);
- acc3 = vmlaq_lane_f32(acc3, b03, a0l, 0);
-
- acc0 = vmlaq_lane_f32(acc0, b10, a0l, 1);
- acc1 = vmlaq_lane_f32(acc1, b11, a0l, 1);
- acc2 = vmlaq_lane_f32(acc2, b12, a0l, 1);
- acc3 = vmlaq_lane_f32(acc3, b13, a0l, 1);
-
- vec_a += 2;
- matrix_b += 2 * in_b_stride;
- }
-
- for(; vec_a < vec_a_end_addr;)
- {
- const float a0 = *vec_a;
-
- const float32x4_t b00 = vld1q_f32(matrix_b + 0 + 0 * in_b_stride);
- const float32x4_t b01 = vld1q_f32(matrix_b + 4 + 0 * in_b_stride);
- const float32x4_t b02 = vld1q_f32(matrix_b + 8 + 0 * in_b_stride);
- const float32x4_t b03 = vld1q_f32(matrix_b + 12 + 0 * in_b_stride);
-
- acc0 = vmlaq_n_f32(acc0, b00, a0);
- acc1 = vmlaq_n_f32(acc1, b01, a0);
- acc2 = vmlaq_n_f32(acc2, b02, a0);
- acc3 = vmlaq_n_f32(acc3, b03, a0);
-
- vec_a += 1;
- matrix_b += in_b_stride;
- }
-
- const auto vec_out = reinterpret_cast<float *>(out.ptr());
-
- vst1q_f32(vec_out + 0, acc0);
- vst1q_f32(vec_out + 4, acc1);
- vst1q_f32(vec_out + 8, acc2);
- vst1q_f32(vec_out + 12, acc3);
- },
- ina, out);
-}
-
-Status validate_arguments(const ITensorInfo *input0, const ITensorInfo *input1, const ITensorInfo *output)
-{
- ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(input0);
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input0, 1, DataType::F16, DataType::F32);
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input1, 1, DataType::F16, DataType::F32);
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::F16, DataType::F32);
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input0, input1, output);
- ARM_COMPUTE_RETURN_ERROR_ON(input0->dimension(0) != input1->dimension(1));
-
- return Status{};
-}
-
-std::tuple<Status, Window> validate_and_configure_window(ITensorInfo *input0, ITensorInfo *input1, ITensorInfo *output)
-{
- constexpr unsigned int num_elems_processed_per_iteration_x = 16;
-
- Window win = calculate_max_window(*output, Steps(num_elems_processed_per_iteration_x));
-
- AccessWindowHorizontal input0_access(input0, 0, num_elems_processed_per_iteration_x);
- AccessWindowHorizontal input1_access(input1, 0, num_elems_processed_per_iteration_x);
- AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration_x);
-
- bool window_changed = update_window_and_padding(win, input0_access, input1_access, output_access);
-
- output_access.set_valid_region(win, ValidRegion(Coordinates(), output->tensor_shape()));
-
- Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
-
- return std::make_tuple(err, win);
-}
-} // namespace
-
-NELocallyConnectedMatrixMultiplyKernel::NELocallyConnectedMatrixMultiplyKernel()
- : _input0(nullptr), _input1(nullptr), _output(nullptr)
-{
-}
-
-void NELocallyConnectedMatrixMultiplyKernel::configure(const ITensor *input0, const ITensor *input1, ITensor *output)
-{
- ARM_COMPUTE_ERROR_ON_NULLPTR(input0, input1, output);
- ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input0->info(), input1->info(), output->info()));
-
- _input0 = input0;
- _input1 = input1;
- _output = output;
-
- // Configure kernel window
- auto win_config = validate_and_configure_window(input0->info(), input1->info(), output->info());
-
- ARM_COMPUTE_ERROR_THROW_ON(std::get<0>(win_config));
-
- INEKernel::configure(std::get<1>(win_config));
-}
-
-Status NELocallyConnectedMatrixMultiplyKernel::validate(const ITensorInfo *input0, const ITensorInfo *input1, const ITensorInfo *output)
-{
- ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input0, input1, output));
- ARM_COMPUTE_RETURN_ON_ERROR(std::get<0>(validate_and_configure_window(input0->clone().get(), input1->clone().get(), output->clone().get())));
-
- return Status{};
-}
-
-void NELocallyConnectedMatrixMultiplyKernel::run(const Window &window, const ThreadInfo &info)
-{
- ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
- ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window);
-
- switch(_input0->info()->data_type())
- {
- case DataType::F16:
- {
- vector_matrix_multiply_f16(_input0, _input1, _output, window, info);
- break;
- }
- case DataType::F32:
- {
- vector_matrix_multiply_f32(_input0, _input1, _output, window, info);
- break;
- }
- default:
- {
- ARM_COMPUTE_ERROR("Data type not supported");
- break;
- }
- }
-}
-} // namespace arm_compute
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