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, 69 insertions, 51 deletions
diff --git a/src/cpu/kernels/fuse_batch_normalization/generic/impl.h b/src/cpu/kernels/fuse_batch_normalization/generic/impl.h index b9017600d6..6fa843263a 100644 --- a/src/cpu/kernels/fuse_batch_normalization/generic/impl.h +++ b/src/cpu/kernels/fuse_batch_normalization/generic/impl.h @@ -25,6 +25,7 @@ #define SRC_CORE_NEON_KERNELS_FUSE_BATCH_NORMALIZATION_GENERIC_IMPL_H #include "arm_compute/core/Helpers.h" + #include "src/core/NEON/wrapper/wrapper.h" namespace arm_compute @@ -32,8 +33,16 @@ namespace arm_compute namespace cpu { template <typename T> -void fused_batch_normalization_conv(const ITensor *conv_weights, const ITensor *conv_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) +void fused_batch_normalization_conv(const ITensor *conv_weights, + const ITensor *conv_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 / conv_weights->info()->element_size(); @@ -53,13 +62,20 @@ void fused_batch_normalization_conv(const ITensor *conv_weights, const ITensor * Iterator conv_w_in(conv_weights, win); Iterator conv_w_out(run_in_place_weights ? conv_weights : fused_weights, win); - const auto conv_bias_in = (conv_bias != nullptr ? reinterpret_cast<ScalarType *>(conv_bias->ptr_to_element(Coordinates(0, 0))) : nullptr); - auto conv_bias_out = (run_in_place_bias ? conv_bias_in : reinterpret_cast<ScalarType *>(fused_bias->ptr_to_element(Coordinates(0, 0)))); + const auto conv_bias_in = + (conv_bias != nullptr ? reinterpret_cast<ScalarType *>(conv_bias->ptr_to_element(Coordinates(0, 0))) : nullptr); + auto conv_bias_out = + (run_in_place_bias ? conv_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; + 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{}); @@ -73,59 +89,61 @@ void fused_batch_normalization_conv(const ITensor *conv_weights, const ITensor * auto gamma = ScalarType(1.0); auto beta = ScalarType(0.0); auto conv_bias_in_scalar = ScalarType(0.0); - execute_window_loop(win, [&](const Coordinates & id) - { - var = input_var[id[3]]; - if(input_gamma != nullptr) + execute_window_loop( + win, + [&](const Coordinates &id) { - gamma = input_gamma[id[3]]; - } + var = input_var[id[3]]; + if (input_gamma != nullptr) + { + gamma = input_gamma[id[3]]; + } - if((id[0] == 0) && (id[1] == 0) && (id[2] == 0)) - { - if(input_beta != nullptr) + if ((id[0] == 0) && (id[1] == 0) && (id[2] == 0)) { - beta = input_beta[id[3]]; - beta_vec = wrapper::vdup_n(beta, ExactTagType{}); + if (input_beta != nullptr) + { + beta = input_beta[id[3]]; + beta_vec = wrapper::vdup_n(beta, ExactTagType{}); + } + + // Construct vectors + mean = input_mean[id[3]]; + mean_vec = wrapper::vdup_n(mean, ExactTagType{}); + + if (conv_bias_in != nullptr) + { + conv_bias_in_scalar = conv_bias_in[id[3]]; + } + auto conv_bias_tmp_scalar = (conv_bias_in_scalar - mean) / std::sqrt(var + ScalarType(epsilon)); + conv_bias_out[id[3]] = (conv_bias_tmp_scalar * gamma) + beta; } - // Construct vectors - mean = input_mean[id[3]]; - mean_vec = wrapper::vdup_n(mean, ExactTagType{}); + int x = window_start_x; + auto conv_w_in_ptr = reinterpret_cast<const ScalarType *>(conv_w_in.ptr()); + auto conv_w_out_ptr = reinterpret_cast<ScalarType *>(conv_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)); - if(conv_bias_in != nullptr) + for (; x <= (window_end_x - window_step_x); x += window_step_x) { - conv_bias_in_scalar = conv_bias_in[id[3]]; - } - auto conv_bias_tmp_scalar = (conv_bias_in_scalar - mean) / std::sqrt(var + ScalarType(epsilon)); - conv_bias_out[id[3]] = (conv_bias_tmp_scalar * gamma) + beta; - } - - int x = window_start_x; - auto conv_w_in_ptr = reinterpret_cast<const ScalarType *>(conv_w_in.ptr()); - auto conv_w_out_ptr = reinterpret_cast<ScalarType *>(conv_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(conv_w_in_ptr + x); - wn = wrapper::vmul(wn, rvar_vec); - wn = wrapper::vmul(wn, gamma_vec); + auto wn = wrapper::vloadq(conv_w_in_ptr + x); + wn = wrapper::vmul(wn, rvar_vec); + wn = wrapper::vmul(wn, gamma_vec); - // Store results - wrapper::vstore(conv_w_out_ptr + x, wn); - } + // Store results + wrapper::vstore(conv_w_out_ptr + x, wn); + } - // Compute left-over elements - for(; x < window_end_x; ++x) - { - *(conv_w_out_ptr + x) = *(conv_w_in_ptr + x) / std::sqrt(var + ScalarType(epsilon)) * gamma; - } - }, - conv_w_in, conv_w_out); -} -} + // Compute left-over elements + for (; x < window_end_x; ++x) + { + *(conv_w_out_ptr + x) = *(conv_w_in_ptr + x) / std::sqrt(var + ScalarType(epsilon)) * gamma; + } + }, + conv_w_in, conv_w_out); } +} // namespace cpu +} // namespace arm_compute #endif //SRC_CORE_NEON_KERNELS_FUSE_BATCH_NORMALIZATION_GENERIC_IMPL_H |