diff options
Diffstat (limited to 'src/cpu/kernels/fuse_batch_normalization/generic/impl.h')
-rw-r--r-- | src/cpu/kernels/fuse_batch_normalization/generic/impl.h | 120 |
1 files changed, 117 insertions, 3 deletions
diff --git a/src/cpu/kernels/fuse_batch_normalization/generic/impl.h b/src/cpu/kernels/fuse_batch_normalization/generic/impl.h index 6fa843263a..d807148e37 100644 --- a/src/cpu/kernels/fuse_batch_normalization/generic/impl.h +++ b/src/cpu/kernels/fuse_batch_normalization/generic/impl.h @@ -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_FUSE_BATCH_NORMALIZATION_GENERIC_IMPL_H -#define SRC_CORE_NEON_KERNELS_FUSE_BATCH_NORMALIZATION_GENERIC_IMPL_H +#ifndef ACL_SRC_CPU_KERNELS_FUSE_BATCH_NORMALIZATION_GENERIC_IMPL_H +#define ACL_SRC_CPU_KERNELS_FUSE_BATCH_NORMALIZATION_GENERIC_IMPL_H #include "arm_compute/core/Helpers.h" @@ -144,6 +144,120 @@ void fused_batch_normalization_conv(const ITensor *conv_weights, }, conv_w_in, conv_w_out); } +template <typename T> +void fused_batch_normalization_dwc_nchw(const ITensor *dwc_weights, + const ITensor *dwc_bias, + ITensor *fused_weights, + ITensor *fused_bias, + const ITensor *bn_mean, + const ITensor *bn_var, + const ITensor *bn_beta, + const ITensor *bn_gamma, + float epsilon, + const Window &window) +{ + using ScalarType = T; + const int size = 16 / dwc_weights->info()->element_size(); + using ExactTagType = typename wrapper::traits::neon_bitvector_tag_t<T, wrapper::traits::BitWidth::W128>; + + const bool run_in_place_weights = (fused_weights == nullptr) || (fused_weights == dwc_weights); + const bool run_in_place_bias = (fused_bias == nullptr) || (dwc_bias != nullptr && fused_bias == dwc_bias); + + // Set build options + Window win = window; + win.set(Window::DimX, Window::Dimension(0, 1, 1)); + + const int window_step_x = size; + const auto window_start_x = static_cast<int>(window.x().start()); + const auto window_end_x = static_cast<int>(window.x().end()); + + Iterator dwc_w_in(dwc_weights, win); + Iterator dwc_w_out(run_in_place_weights ? dwc_weights : fused_weights, win); + + const auto dwc_bias_in = + (dwc_bias != nullptr ? reinterpret_cast<ScalarType *>(dwc_bias->ptr_to_element(Coordinates(0, 0))) : nullptr); + auto dwc_bias_out = + (run_in_place_bias ? dwc_bias_in + : reinterpret_cast<ScalarType *>(fused_bias->ptr_to_element(Coordinates(0, 0)))); + + const auto input_mean = reinterpret_cast<const ScalarType *>(bn_mean->ptr_to_element(Coordinates(0, 0))); + const auto input_var = reinterpret_cast<const ScalarType *>(bn_var->ptr_to_element(Coordinates(0, 0))); + const auto input_gamma = (bn_gamma != nullptr) + ? reinterpret_cast<const ScalarType *>(bn_gamma->ptr_to_element(Coordinates(0, 0))) + : nullptr; + const auto input_beta = (bn_beta != nullptr) + ? reinterpret_cast<const ScalarType *>(bn_beta->ptr_to_element(Coordinates(0, 0))) + : nullptr; + + auto mean_vec = wrapper::vdup_n(ScalarType(0), ExactTagType{}); + auto var_vec = wrapper::vdup_n(ScalarType(0), ExactTagType{}); + auto gamma_vec = wrapper::vdup_n(ScalarType(1), ExactTagType{}); + auto beta_vec = wrapper::vdup_n(ScalarType(0), ExactTagType{}); + auto rvar_vec = wrapper::vdup_n(ScalarType(0), ExactTagType{}); + const auto epsilon_vec = wrapper::vdup_n(ScalarType(epsilon), ExactTagType{}); + + auto mean = ScalarType(0.0); + auto var = ScalarType(0.0); + auto gamma = ScalarType(1.0); + auto beta = ScalarType(0.0); + auto dwc_bias_in_scalar = ScalarType(0.0); + execute_window_loop( + win, + [&](const Coordinates &id) + { + var = input_var[id[2]]; + if (input_gamma != nullptr) + { + gamma = input_gamma[id[2]]; + } + + if (id[1] == 0) + { + mean = input_mean[id[2]]; + + // Construct vectors + mean_vec = wrapper::vdup_n(mean, ExactTagType{}); + if (input_beta != nullptr) + { + beta = input_beta[id[2]]; + beta_vec = wrapper::vdup_n(beta, ExactTagType{}); + } + + if (dwc_bias_in != nullptr) + { + dwc_bias_in_scalar = dwc_bias_in[id[2]]; + } + + auto dwc_bias_tmp_scalar = (dwc_bias_in_scalar - mean) / std::sqrt(var + ScalarType(epsilon)); + dwc_bias_out[id[2]] = (dwc_bias_tmp_scalar * gamma) + beta; + } + + int x = window_start_x; + auto dwc_w_in_ptr = reinterpret_cast<const ScalarType *>(dwc_w_in.ptr()); + auto dwc_w_out_ptr = reinterpret_cast<ScalarType *>(dwc_w_out.ptr()); + var_vec = wrapper::vdup_n(var, ExactTagType{}); + gamma_vec = wrapper::vdup_n(gamma, ExactTagType{}); + rvar_vec = wrapper::vinvsqrt(wrapper::vadd(var_vec, epsilon_vec)); + + for (; x <= (window_end_x - window_step_x); x += window_step_x) + { + auto wn = wrapper::vloadq(dwc_w_in_ptr + x); + wn = wrapper::vmul(wn, rvar_vec); + wn = wrapper::vmul(wn, gamma_vec); + + // Store results + wrapper::vstore(dwc_w_out_ptr + x, wn); + } + + // Compute left-over elements + for (; x < window_end_x; ++x) + { + *(dwc_w_out_ptr + x) = *(dwc_w_in_ptr + x) / std::sqrt(var + ScalarType(epsilon)) * gamma; + } + }, + dwc_w_in, dwc_w_out); +} + } // namespace cpu } // namespace arm_compute -#endif //SRC_CORE_NEON_KERNELS_FUSE_BATCH_NORMALIZATION_GENERIC_IMPL_H +#endif // ACL_SRC_CPU_KERNELS_FUSE_BATCH_NORMALIZATION_GENERIC_IMPL_H |