From 8d4cdd43a74574e0f99f83f1adb1d391c0c85abe Mon Sep 17 00:00:00 2001 From: Pablo Marquez Tello Date: Tue, 21 Nov 2023 10:10:01 +0000 Subject: BatchNorm changes to enable fp16 in armv8a multi_isa builds * Moved NCHW kernels fp16 and fp32 to their corresponding files src/cpu/kernels/fuse_batch_normalization/nchw/neon/fp16.cpp and src/cpu/kernels/fuse_batch_normalization/nchw/neon/fp32.cpp * Changes in filelist.json to include the new fp16 and fp32 files * Moved the template batch_normalization_nchw to impl.h as we need to instantiate it from fp16.cpp and fp32.cpp * Pooling layer: removed the guard __ARM_FEATURE_FP16_VECTOR_ARITHMETIC that prevented the FP16 kernel execution. * Partially resolves MLCE-1102 Change-Id: Ia8c85e9ffb76c9e387f9ae2685e5df5e52c8dc27 Signed-off-by: Pablo Marquez Tello Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10777 Reviewed-by: Viet-Hoa Do Comments-Addressed: Arm Jenkins Tested-by: Arm Jenkins Benchmark: Arm Jenkins --- .../kernels/NEBatchNormalizationLayerKernel.cpp | 138 ++------------------- .../NEON/kernels/NEBatchNormalizationLayerKernel.h | 36 ++---- .../NEON/kernels/batchnormalization/impl/list.h | 25 +++- 3 files changed, 43 insertions(+), 156 deletions(-) (limited to 'src/core/NEON/kernels') diff --git a/src/core/NEON/kernels/NEBatchNormalizationLayerKernel.cpp b/src/core/NEON/kernels/NEBatchNormalizationLayerKernel.cpp index deb89996a9..717fd11485 100644 --- a/src/core/NEON/kernels/NEBatchNormalizationLayerKernel.cpp +++ b/src/core/NEON/kernels/NEBatchNormalizationLayerKernel.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2021 Arm Limited. + * Copyright (c) 2017-2021, 2023 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -151,128 +151,15 @@ Status validate_arguments(const ITensorInfo *input, } } //namespace -template -void NEBatchNormalizationLayerKernel::batch_normalization_nchw(const Window &window) -{ - /** SIMD vector tag type. */ - using ExactTagType = typename wrapper::traits::neon_bitvector_tag_t; - - const int window_step_x = 16 / sizeof(T); - const auto window_start_x = static_cast(window.x().start()); - const auto window_end_x = static_cast(window.x().end()); - - Window win_to_use = window; - win_to_use.set(Window::DimX, Window::Dimension(0, 1, 1)); - - Iterator input(_input, win_to_use); - Iterator output(_output, win_to_use); - - F activation_functor(_act_info); - - // Hold information about the current feature map we are iterating. - // Only compute denominator and constants once per feature map. - int slice = -1; - - const auto input_mean = reinterpret_cast(_mean->ptr_to_element(Coordinates(0, 0))); - const auto input_var = reinterpret_cast(_var->ptr_to_element(Coordinates(0, 0))); - const auto input_gamma = - (_gamma != nullptr) ? reinterpret_cast(_gamma->ptr_to_element(Coordinates(0, 0))) : nullptr; - const auto input_beta = - (_beta != nullptr) ? reinterpret_cast(_beta->ptr_to_element(Coordinates(0, 0))) : nullptr; - - T mean = static_cast(0); - T var = static_cast(0); - T gamma = static_cast(1); - T beta = static_cast(0); - T denominator = static_cast(0); - - auto mean_vec = wrapper::vdup_n(mean, ExactTagType{}); - auto var_vec = wrapper::vdup_n(var, ExactTagType{}); - auto gamma_vec = wrapper::vdup_n(gamma, ExactTagType{}); - auto beta_vec = wrapper::vdup_n(beta, ExactTagType{}); - auto denominator_vec = wrapper::vdup_n(denominator, ExactTagType{}); - const auto epsilon_vec = wrapper::vdup_n(static_cast(_epsilon), ExactTagType{}); - execute_window_loop( - win_to_use, - [&](const Coordinates &id) - { - const auto input_ptr = reinterpret_cast(input.ptr()); - const auto output_ptr = reinterpret_cast(output.ptr()); - - if (slice != id.z()) - { - mean = input_mean[id.z()]; - var = input_var[id.z()]; - mean_vec = wrapper::vdup_n(mean, ExactTagType{}); - var_vec = wrapper::vdup_n(var, ExactTagType{}); - if (input_gamma != nullptr) - { - gamma = input_gamma[id.z()]; - gamma_vec = wrapper::vdup_n(gamma, ExactTagType{}); - } - if (input_beta != nullptr) - { - beta = input_beta[id.z()]; - beta_vec = wrapper::vdup_n(beta, ExactTagType{}); - } - - // Calculate denominator - denominator_vec = wrapper::vinvsqrt(wrapper::vadd(var_vec, epsilon_vec)); - denominator = wrapper::vgetlane(denominator_vec, 0); - slice = id.z(); - } - - // Perform core calculations using vector operations - int x = window_start_x; - for (; x <= (window_end_x - window_step_x); x += window_step_x) - { - // Calculate x bar - const auto numerator = wrapper::vsub(wrapper::vloadq(input_ptr + x), mean_vec); - const auto x_bar = wrapper::vmul(numerator, denominator_vec); - auto res = wrapper::vmla(beta_vec, x_bar, gamma_vec); - - // Perform fused activation - if (fused_activation) - { - activation_functor(res); - } - - // Store results - wrapper::vstore(output_ptr + x, res); - } - - // Compute left-over elements - for (; x < window_end_x; ++x) - { - const T numerator = input_ptr[x] - mean; - const T x_bar = numerator * denominator; - T res = beta + x_bar * gamma; - - // Perform fused activation - if (fused_activation) - { - activation_functor(res); - } - - // Store results - *(output_ptr + x) = res; - } - }, - input, output); -} - void NEBatchNormalizationLayerKernel::configure_non_fused() { switch (_input->info()->data_type()) { -#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC case DataType::F16: - _func = &NEBatchNormalizationLayerKernel::batch_normalization_nchw>; + _func = REGISTER_FP16_NEON(cpu::fp16_batch_normalization_nchw_non_fused); break; -#endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC case DataType::F32: - _func = &NEBatchNormalizationLayerKernel::batch_normalization_nchw>; + _func = REGISTER_FP32_NEON(cpu::fp32_batch_normalization_nchw_non_fused); break; default: ARM_COMPUTE_ERROR("Element size not supported"); @@ -285,29 +172,26 @@ void NEBatchNormalizationLayerKernel::configure_fused() // NCHW Fused Batched Normalization with activation functions : FP32 static std::map bn_fused_map_f32_nchw = { {ActivationLayerInfo::ActivationFunction::RELU, - &NEBatchNormalizationLayerKernel::batch_normalization_nchw>}, + REGISTER_FP32_NEON(cpu::fp32_batch_normalization_nchw_non_fused_relu)}, {ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, - &NEBatchNormalizationLayerKernel::batch_normalization_nchw>}, + REGISTER_FP32_NEON(cpu::fp32_batch_normalization_nchw_non_fused_brelu)}, {ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, - &NEBatchNormalizationLayerKernel::batch_normalization_nchw>}}; -#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC + REGISTER_FP32_NEON(cpu::fp32_batch_normalization_nchw_non_fused_lubrelu)}}; + // NCHW Fused Batched Normalization with activation functions : FP16 static std::map bn_fused_map_f16_nchw = { {ActivationLayerInfo::ActivationFunction::RELU, - &NEBatchNormalizationLayerKernel::batch_normalization_nchw>}, + REGISTER_FP16_NEON(cpu::fp16_batch_normalization_nchw_non_fused_relu)}, {ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, - &NEBatchNormalizationLayerKernel::batch_normalization_nchw>}, + REGISTER_FP16_NEON(cpu::fp16_batch_normalization_nchw_non_fused_brelu)}, {ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, - &NEBatchNormalizationLayerKernel::batch_normalization_nchw>}}; -#endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC + REGISTER_FP16_NEON(cpu::fp16_batch_normalization_nchw_non_fused_lubrelu)}}; switch (_input->info()->data_type()) { -#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC case DataType::F16: _func = bn_fused_map_f16_nchw[_act_info.activation()]; break; -#endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC case DataType::F32: _func = bn_fused_map_f32_nchw[_act_info.activation()]; break; @@ -409,7 +293,7 @@ void NEBatchNormalizationLayerKernel::run(const Window &window, const ThreadInfo const bool is_nchw = _input->info()->data_layout() == DataLayout::NCHW; if (is_nchw) { - (this->*_func)(window); + (*_func)(window, _input, _output, _mean, _var, _beta, _gamma, _epsilon, _act_info); } else { diff --git a/src/core/NEON/kernels/NEBatchNormalizationLayerKernel.h b/src/core/NEON/kernels/NEBatchNormalizationLayerKernel.h index 2e8ff0dc9a..679ade0fae 100644 --- a/src/core/NEON/kernels/NEBatchNormalizationLayerKernel.h +++ b/src/core/NEON/kernels/NEBatchNormalizationLayerKernel.h @@ -21,8 +21,8 @@ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE * SOFTWARE. */ -#ifndef ARM_COMPUTE_NEBATCHNORMALIZATIONLAYERKERNEL_H -#define ARM_COMPUTE_NEBATCHNORMALIZATIONLAYERKERNEL_H +#ifndef ACL_SRC_CORE_NEON_KERNELS_NEBATCHNORMALIZATIONLAYERKERNEL_H +#define ACL_SRC_CORE_NEON_KERNELS_NEBATCHNORMALIZATIONLAYERKERNEL_H #include "arm_compute/function_info/ActivationLayerInfo.h" @@ -110,31 +110,19 @@ private: /** Configure execution function in case of fused activation **/ void configure_fused(); - /** Template function to run batch normalization on fp32 - * - * @tparam T Specialization data type - * @tparam fused_activation Boolean that flags if its a fused activation or not - * @tparam F Activation function functor to run - * - * @param[in] window Region on which to execute the kernel. (Must be a valid region of the window returned by window()). - */ - template - void batch_normalization_nchw(const Window &window); - /** Template function to run batch normalization on fp32 on tensors with NHWC format - * - * @tparam T Specialization data type - * @tparam fused_activation Boolean that flags if its a fused activation or not - * @tparam F Activation function functor to run - * - * @param[in] window Region on which to execute the kernel. (Must be a valid region of the window returned by window()). - */ - template - void batch_normalization_nhwc(const Window &window); /** Common signature for all the batch normalization functions * * @param[in] window Region on which to execute the kernel. */ - using BatchNormFunctionPtr = void (NEBatchNormalizationLayerKernel::*)(const Window &window); + using BatchNormFunctionPtr = void (*)(const Window &window, + ITensor *input, + ITensor *output, + const ITensor *mean, + const ITensor *var, + const ITensor *beta, + const ITensor *gamma, + float epsilon, + ActivationLayerInfo act_info); private: BatchNormFunctionPtr _func; @@ -148,4 +136,4 @@ private: ActivationLayerInfo _act_info; }; } // namespace arm_compute -#endif /*ARM_COMPUTE_NEBATCHNORMALIZATIONLAYERKERNEL_H */ +#endif // ACL_SRC_CORE_NEON_KERNELS_NEBATCHNORMALIZATIONLAYERKERNEL_H diff --git a/src/core/NEON/kernels/batchnormalization/impl/list.h b/src/core/NEON/kernels/batchnormalization/impl/list.h index cbf540bd71..c619788125 100644 --- a/src/core/NEON/kernels/batchnormalization/impl/list.h +++ b/src/core/NEON/kernels/batchnormalization/impl/list.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2020 Arm Limited. + * Copyright (c) 2020, 2023 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -21,8 +21,8 @@ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE * SOFTWARE. */ -#ifndef SRC_CORE_NEON_KERNELS_BATCH_NORMALIZATION_LIST_H -#define SRC_CORE_NEON_KERNELS_BATCH_NORMALIZATION_LIST_H +#ifndef ACL_SRC_CORE_NEON_KERNELS_BATCHNORMALIZATION_IMPL_LIST_H +#define ACL_SRC_CORE_NEON_KERNELS_BATCHNORMALIZATION_IMPL_LIST_H namespace arm_compute { @@ -37,8 +37,23 @@ DECLARE_BATCH_NORMALIZATION_KERNEL(fp16_sve_batch_normalization); DECLARE_BATCH_NORMALIZATION_KERNEL(fp32_neon_batch_normalization); DECLARE_BATCH_NORMALIZATION_KERNEL(fp32_sve_batch_normalization); -#undef DECLARE_ACTIVATION_KERNEL +#define DECLARE_BATCH_NORMALIZATION_NCHW_KERNEL(func_name) \ + void func_name(const Window &window, ITensor *input, ITensor *output, const ITensor *mean, const ITensor *var, \ + const ITensor *beta, const ITensor *gamma, float epsilon, ActivationLayerInfo act_info) + +DECLARE_BATCH_NORMALIZATION_NCHW_KERNEL(fp16_batch_normalization_nchw_non_fused); +DECLARE_BATCH_NORMALIZATION_NCHW_KERNEL(fp32_batch_normalization_nchw_non_fused); +DECLARE_BATCH_NORMALIZATION_NCHW_KERNEL(fp16_batch_normalization_nchw_non_fused_relu); +DECLARE_BATCH_NORMALIZATION_NCHW_KERNEL(fp16_batch_normalization_nchw_non_fused_brelu); +DECLARE_BATCH_NORMALIZATION_NCHW_KERNEL(fp16_batch_normalization_nchw_non_fused_lubrelu); +DECLARE_BATCH_NORMALIZATION_NCHW_KERNEL(fp32_batch_normalization_nchw_non_fused_relu); +DECLARE_BATCH_NORMALIZATION_NCHW_KERNEL(fp32_batch_normalization_nchw_non_fused_brelu); +DECLARE_BATCH_NORMALIZATION_NCHW_KERNEL(fp32_batch_normalization_nchw_non_fused_lubrelu); + +#undef DECLARE_BATCH_NORMALIZATION_KERNEL +#undef DECLARE_BATCH_NORMALIZATION_NCHW_KERNEL + } // namespace cpu } // namespace arm_compute -#endif /* SRC_CORE_NEON_KERNELS_BATCH_NORMALIZATION_LIST_H */ +#endif // ACL_SRC_CORE_NEON_KERNELS_BATCHNORMALIZATION_IMPL_LIST_H -- cgit v1.2.1