| /* |
| * Copyright (c) 2020-2021 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 "arm_compute/core/ITensorPack.h" |
| #include "arm_compute/core/Window.h" |
| #include "src/core/NEON/NEMath.h" |
| #include "src/core/NEON/kernels/detail/NEActivationFunctionDetail.h" |
| #include "src/core/NEON/wrapper/wrapper.h" |
| |
| #include <arm_neon.h> |
| #include <cmath> |
| #include <cstddef> |
| |
| #if defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) && defined(ENABLE_FP16_KERNELS) |
| namespace arm_compute |
| { |
| namespace |
| { |
| using BatchNomalizationPtr = void (*)(ITensor *src, ITensor *dst, const ITensor *mean, const ITensor *var, const ITensor *beta, const ITensor *gamma, |
| float epsilon, ActivationLayerInfo &act_info, const Window &window); |
| |
| template <typename T> |
| void batch_normalization(ITensor *src, ITensor *dst, const ITensor *mean, const ITensor *var, const ITensor *beta, const ITensor *gamma, |
| float epsilon, ActivationLayerInfo &act_info, const Window &window) |
| { |
| /** SIMD vector tag type. */ |
| using ExactTagType = typename wrapper::traits::neon_bitvector_tag_t<float16_t, wrapper::traits::BitWidth::W128>; |
| |
| const int window_step_x = 8; |
| const auto window_start_x = static_cast<int>(window.x().start()); |
| const auto window_end_x = static_cast<int>(window.x().end()); |
| |
| Window win_collapsed = window.collapse_if_possible(window, Window::DimZ); |
| win_collapsed.set(Window::DimX, Window::Dimension(0, 1, 1)); |
| |
| Iterator input(src, win_collapsed); |
| Iterator output(dst, win_collapsed); |
| |
| const auto input_mean = reinterpret_cast<const float16_t *>(mean->ptr_to_element(Coordinates(0, 0))); |
| const auto input_var = reinterpret_cast<const float16_t *>(var->ptr_to_element(Coordinates(0, 0))); |
| const auto input_gamma = (gamma != nullptr) ? reinterpret_cast<const float16_t *>(gamma->ptr_to_element(Coordinates(0, 0))) : nullptr; |
| const auto input_beta = (beta != nullptr) ? reinterpret_cast<const float16_t *>(beta->ptr_to_element(Coordinates(0, 0))) : nullptr; |
| |
| T activation_functor(act_info); |
| |
| const auto epsilon_vec = wrapper::vdup_n(static_cast<float16_t>(epsilon), ExactTagType{}); |
| execute_window_loop(win_collapsed, [&](const Coordinates &) |
| { |
| const auto input_ptr = reinterpret_cast<const float16_t *>(input.ptr()); |
| const auto output_ptr = reinterpret_cast<float16_t *>(output.ptr()); |
| |
| // Perform core calculations using vector operations |
| int x = window_start_x; |
| for(; x <= (window_end_x - window_step_x); x += window_step_x) |
| { |
| // Conctruct vectors |
| const auto mean_vec = wrapper::vloadq(input_mean + x); |
| const auto var_vec = wrapper::vloadq(input_var + x); |
| const auto gamma_vec = (input_gamma != nullptr) ? wrapper::vloadq(input_gamma + x) : wrapper::vdup_n(static_cast<float16_t>(1.f), ExactTagType{}); |
| const auto beta_vec = (input_beta != nullptr) ? wrapper::vloadq(input_beta + x) : wrapper::vdup_n(static_cast<float16_t>(0.f), ExactTagType{}); |
| |
| // Calculate denominator |
| const auto denominator = wrapper::vinvsqrt(wrapper::vadd(var_vec, epsilon_vec)); |
| |
| // Calculate x bar |
| const auto numerator = wrapper::vsub(wrapper::vloadq(input_ptr + x), mean_vec); |
| const auto x_bar = wrapper::vmul(numerator, denominator); |
| auto res = wrapper::vmla(beta_vec, x_bar, gamma_vec); |
| |
| // Perform fused activation |
| if(act_info.enabled()) |
| { |
| activation_functor(res); |
| } |
| |
| // Store results |
| wrapper::vstore(output_ptr + x, res); |
| } |
| |
| // Compute left-over elements |
| for(; x < window_end_x; ++x) |
| { |
| // Conctruct vectors |
| const float16_t gamma = (input_gamma != nullptr) ? input_gamma[x] : 1.f; |
| const float16_t beta = (input_beta != nullptr) ? input_beta[x] : 0.f; |
| |
| const float16_t denominator = sqrt(input_var[x] + epsilon); |
| const float16_t numerator = input_ptr[x] - input_mean[x]; |
| const float16_t x_bar = numerator / denominator; |
| float16_t res = beta + x_bar * gamma; |
| |
| // Perform fused activation |
| if(act_info.enabled()) |
| { |
| activation_functor(res); |
| } |
| |
| // Store results |
| *reinterpret_cast<float16_t *>(output_ptr + x) = res; |
| } |
| }, |
| input, output); |
| } |
| |
| // Fused Batched Normalization with activation functions |
| static std::map<ActivationLayerInfo::ActivationFunction, BatchNomalizationPtr> fused_map = |
| { |
| { ActivationLayerInfo::ActivationFunction::RELU, &batch_normalization<detail::relu<float16_t, 8>> }, |
| { ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, &batch_normalization<detail::brelu<float16_t, 8>> }, |
| { ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, &batch_normalization<detail::lubrelu<float16_t, 8>> } |
| }; |
| } |
| namespace cpu |
| { |
| void fp16_neon_batch_normalization(ITensor *src, ITensor *dst, const ITensor *mean, const ITensor *var, const ITensor *beta, const ITensor *gamma, |
| float epsilon, ActivationLayerInfo &act_info, const Window &window) |
| { |
| if(act_info.enabled()) |
| { |
| fused_map[act_info.activation()](src, dst, mean, var, beta, gamma, epsilon, act_info, window); |
| } |
| else |
| { |
| batch_normalization<detail::dummy<float16_t, 8>>(src, dst, mean, var, beta, gamma, epsilon, act_info, window); |
| } |
| } |
| } // namespace cpu |
| } // namespace arm_compute |
| |
| #endif /* defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) && defined(ENABLE_FP16_KERNELS) */ |