COMPMID-3871: Create BatchNormalization SVE/SVE2
1. Decouple data type for NHWC
2. Add NHWC SVE support for BachNormalization
Signed-off-by: Sheri Zhang <sheri.zhang@arm.com>
Change-Id: I0383b969b555b429d9acebb4efa17ecba9429ea7
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/4755
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michalis Spyrou <michalis.spyrou@arm.com>
diff --git a/src/core/NEON/kernels/batchnormalization/impl/SVE/fp32.cpp b/src/core/NEON/kernels/batchnormalization/impl/SVE/fp32.cpp
new file mode 100644
index 0000000..317befd
--- /dev/null
+++ b/src/core/NEON/kernels/batchnormalization/impl/SVE/fp32.cpp
@@ -0,0 +1,119 @@
+/*
+ * Copyright (c) 2020 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/SVEMath.h"
+#include "src/core/common/StdTypes.h"
+#include "src/core/common/Validate.h"
+
+#include <cmath>
+#include <cstddef>
+
+#if defined(__ARM_FEATURE_SVE)
+#include <arm_sve.h>
+
+namespace arm_compute
+{
+namespace cpu
+{
+void fp32_sve_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)
+{
+ 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 float *>(mean->ptr_to_element(Coordinates(0, 0)));
+ const auto input_var = reinterpret_cast<const float *>(var->ptr_to_element(Coordinates(0, 0)));
+ const auto input_gamma = (gamma != nullptr) ? reinterpret_cast<const float *>(gamma->ptr_to_element(Coordinates(0, 0))) : nullptr;
+ const auto input_beta = (beta != nullptr) ? reinterpret_cast<const float *>(beta->ptr_to_element(Coordinates(0, 0))) : nullptr;
+
+ const auto epsilon_vec = svdup_n_f32(epsilon);
+ const auto const_1 = svdup_n_f32(1.f);
+ const auto const_0 = svdup_n_f32(0.f);
+ const auto va = svdup_n_f32(act_info.a());
+ const auto vb = svdup_n_f32(act_info.b());
+ execute_window_loop(win_collapsed, [&](const Coordinates &)
+ {
+ const auto input_ptr = reinterpret_cast<const float *>(input.ptr());
+ const auto output_ptr = reinterpret_cast<float *>(output.ptr());
+
+ // Compute S elements per iteration
+ int x = window_start_x;
+ svbool_t pg = svwhilelt_b32(x, window_end_x);
+ do
+ {
+ // Conctruct vectors
+ const auto mean_vec = svld1_f32(pg, input_mean + x);
+ const auto var_vec = svld1_f32(pg, input_var + x);
+ const auto gamma_vec = (input_gamma != nullptr) ? svld1_f32(pg, input_gamma + x) : const_1;
+ const auto beta_vec = (input_beta != nullptr) ? svld1_f32(pg, input_beta + x) : const_0;
+
+ // Calculate denominator
+ const auto tmp = svadd_f32_z(pg, var_vec, epsilon_vec);
+ auto denominator = svrsqrte_f32(tmp);
+ denominator = svmul_f32_z(pg, svrsqrts_f32(svmul_f32_z(pg, tmp, denominator), denominator), denominator);
+ denominator = svmul_f32_z(pg, svrsqrts_f32(svmul_f32_z(pg, tmp, denominator), denominator), denominator);
+
+ // Calculate x bar
+ const auto numerator = svsub_f32_z(pg, svld1_f32(pg, input_ptr + x), mean_vec);
+ const auto x_bar = svmul_f32_z(pg, numerator, denominator);
+ auto res = svmla_f32_z(pg, beta_vec, x_bar, gamma_vec);
+
+ // Perform fused activation
+ if(act_info.enabled())
+ {
+ if(act_info.activation() == ActivationLayerInfo::ActivationFunction::RELU)
+ {
+ res = svmax_f32_z(pg, const_0, res);
+ }
+ else if(act_info.activation() == ActivationLayerInfo::ActivationFunction::BOUNDED_RELU)
+ {
+ res = svmin_f32_z(pg, va, svmax_f32_z(pg, const_0, res));
+ }
+ else if(act_info.activation() == ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU)
+ {
+ res = svmin_f32_z(pg, va, svmax_f32_z(pg, vb, res));
+ }
+ }
+
+ // Store results
+ svst1_f32(pg, output_ptr + x, res);
+
+ x += svcntw();
+ pg = svwhilelt_b32(x, window_end_x);
+ }
+ while(svptest_any(svptrue_b32(), pg));
+ },
+ input, output);
+}
+} // namespace cpu
+} // namespace arm_compute
+#endif // __ARM_FEATURE_SVE