Decouple NEL2NormalizeLayerKernel
Resolves: COMPMID-4615
Signed-off-by: Yair Schwarzbaum <yair.schwarzbaum@arm.com>
Change-Id: Iadbfb3e45831a5072962b5b9f61e8ae2e674ccc4
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/7016
Reviewed-by: Giorgio Arena <giorgio.arena@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
diff --git a/Android.bp b/Android.bp
index 957c8e2..950192c 100644
--- a/Android.bp
+++ b/Android.bp
@@ -468,6 +468,9 @@
"src/cpu/kernels/instancenorm/generic/neon/impl.cpp",
"src/cpu/kernels/internal/CpuDepthwiseConv2dAssemblyWrapperKernel.cpp",
"src/cpu/kernels/internal/CpuPool2dAssemblyWrapperKernel.cpp",
+ "src/cpu/kernels/l2normlayer/generic/neon/fp16.cpp",
+ "src/cpu/kernels/l2normlayer/generic/neon/fp32.cpp",
+ "src/cpu/kernels/l2normlayer/generic/neon/impl.cpp",
"src/cpu/kernels/maxunpool/generic/neon/fp16.cpp",
"src/cpu/kernels/maxunpool/generic/neon/fp32.cpp",
"src/cpu/kernels/maxunpool/generic/neon/impl.cpp",
diff --git a/filelist.json b/filelist.json
index 88d98ae..6e28635 100644
--- a/filelist.json
+++ b/filelist.json
@@ -1578,7 +1578,12 @@
"common": [
"src/core/NEON/kernels/NEL2NormalizeLayerKernel.cpp",
"src/runtime/NEON/functions/NEL2NormalizeLayer.cpp"
- ]
+ ],
+ "neon":{
+ "common":["src/cpu/kernels/l2normlayer/generic/neon/impl.cpp"],
+ "fp32":["src/cpu/kernels/l2normlayer/generic/neon/fp32.cpp"],
+ "fp16":["src/cpu/kernels/l2normlayer/generic/neon/fp16.cpp"]
+ }
}
},
"Logical": {
diff --git a/src/core/NEON/kernels/NEL2NormalizeLayerKernel.cpp b/src/core/NEON/kernels/NEL2NormalizeLayerKernel.cpp
index 9bda82d..8ab0288 100644
--- a/src/core/NEON/kernels/NEL2NormalizeLayerKernel.cpp
+++ b/src/core/NEON/kernels/NEL2NormalizeLayerKernel.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2021 Arm Limited.
+ * Copyright (c) 2017-2022 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -30,11 +30,13 @@
#include "arm_compute/core/Utils.h"
#include "arm_compute/core/Validate.h"
#include "arm_compute/core/Window.h"
+#include "src/common/cpuinfo/CpuIsaInfo.h"
#include "src/core/NEON/NEMath.h"
+#include "src/core/common/Registrars.h"
#include "src/core/helpers/AutoConfiguration.h"
#include "src/core/helpers/WindowHelpers.h"
+#include "src/cpu/kernels/l2normlayer/list.h"
-#include "src/core/NEON/wrapper/wrapper.h"
#include <arm_neon.h>
#include <cmath>
@@ -44,90 +46,64 @@
{
constexpr int max_input_tensor_dim = 3;
-template <typename T, int S>
-void l2_normalize_X(const ITensor *in, const ITensor *sum, ITensor *out, float epsilon, const Window &window)
+struct L2NormalizeLayerSelectorData
{
- using ExactTagType = typename wrapper::traits::neon_vector<T, S>::tag_type;
+ DataType dt;
+ unsigned int actual_axis;
+ cpuinfo::CpuIsaInfo isa;
+};
- const int window_step_x = 16 / data_size_from_type(in->info()->data_type());
- const auto window_start_x = static_cast<int>(window.x().start());
- const auto window_end_x = static_cast<int>(window.x().end());
+using L2NormalizeLayerKernelSelctorPtr = std::add_pointer<bool(const L2NormalizeLayerSelectorData &data)>::type;
- Window win_collapsed = window.collapse_if_possible(window, Window::DimZ);
- win_collapsed.set(Window::DimX, Window::Dimension(0, 1, 1));
+using L2NormalizeLayerPtr = std::add_pointer<void(const ITensor *in, const ITensor *sum, ITensor *out, float epsilon, const Window &window, size_t axis)>::type;
- Iterator input_it(in, win_collapsed);
- Iterator sum_it(sum, win_collapsed);
- Iterator output_it(out, win_collapsed);
-
- execute_window_loop(win_collapsed, [&](const Coordinates &)
- {
- const auto in_ptr = reinterpret_cast<const T *>(input_it.ptr());
- const auto out_ptr = reinterpret_cast<T *>(output_it.ptr());
-
- const T sum_value = *reinterpret_cast<const T *>(sum_it.ptr());
- const T norm_value = static_cast<T>(1.f) / std::sqrt(std::max(sum_value, static_cast<T>(epsilon)));
- const auto vec_norm_value = wrapper::vdup_n(norm_value, ExactTagType{});
-
- // Compute elements over vector steps
- int x = window_start_x;
- for(; x <= (window_end_x - window_step_x); x += window_step_x)
- {
- wrapper::vstore(out_ptr + x, wrapper::vmul(wrapper::vloadq(in_ptr + x), vec_norm_value));
- }
-
- // Compute left-over elements
- for(; x < window_end_x; ++x)
- {
- out_ptr[x] = in_ptr[x] * norm_value;
- }
- },
- input_it, sum_it, output_it);
-}
-
-template <typename T, int S>
-void l2_normalize_YZ(const ITensor *in, const ITensor *sum, ITensor *out, float epsilon, const Window &window, size_t axis)
+struct L2NormalizeLayerKernel
{
- using ExactTagType = typename wrapper::traits::neon_vector<T, S>::tag_type;
+ const char *name;
+ const L2NormalizeLayerKernelSelctorPtr is_selected;
+ L2NormalizeLayerPtr ukernel;
+};
- const int window_step_x = 16 / data_size_from_type(in->info()->data_type());
- const auto window_start_x = static_cast<int>(window.x().start());
- const auto window_end_x = static_cast<int>(window.x().end());
-
- Window win = window;
- win.set(Window::DimX, Window::Dimension(0, 1, 1));
-
- Window window_sum(win);
- window_sum.set(axis, Window::Dimension(0, 0, 0));
-
- Iterator input_it(in, win);
- Iterator sum_it(sum, window_sum);
- Iterator output_it(out, win);
-
- const auto vec_eps = wrapper::vdup_n(static_cast<T>(epsilon), ExactTagType{});
-
- execute_window_loop(win, [&](const Coordinates &)
+static const L2NormalizeLayerKernel available_kernels[] =
+{
{
- const auto in_ptr = reinterpret_cast<const T *>(input_it.ptr());
- const auto sum_ptr = reinterpret_cast<const T *>(sum_it.ptr());
- const auto out_ptr = reinterpret_cast<T *>(output_it.ptr());
-
- // Compute elements over vector steps
- int x = window_start_x;
- for(; x <= (window_end_x - window_step_x); x += window_step_x)
- {
- const auto vec_norm_value = wrapper::vinvsqrt(wrapper::vmax(wrapper::vloadq(sum_ptr + x), vec_eps));
- wrapper::vstore(out_ptr + x, wrapper::vmul(wrapper::vloadq(in_ptr + x), vec_norm_value));
- }
-
- // Compute left-over elements
- for(; x < window_end_x; ++x)
- {
- const T norm_value = static_cast<T>(1.f) / std::sqrt(std::max(sum_ptr[x], static_cast<T>(epsilon)));
- out_ptr[x] = in_ptr[x] * norm_value;
- }
+ "fp32_neon_l2normalize_x",
+ [](const L2NormalizeLayerSelectorData & data) { return data.dt == DataType::F32 && data.actual_axis == Window::DimX; },
+ REGISTER_FP32_NEON(arm_compute::cpu::neon_fp32_l2_normalize_x)
},
- input_it, sum_it, output_it);
+ {
+ "fp32_neon_l2normalize_yz",
+ [](const L2NormalizeLayerSelectorData & data) { return data.dt == DataType::F32 && data.actual_axis != Window::DimX; },
+ REGISTER_FP32_NEON(arm_compute::cpu::neon_fp32_l2_normalize_yz)
+ },
+ {
+ "fp16_neon_l2normalize_x",
+ [](const L2NormalizeLayerSelectorData & data) { return data.dt == DataType::F16 && data.isa.fp16 && data.actual_axis == Window::DimX; },
+ REGISTER_FP16_NEON(arm_compute::cpu::neon_fp16_l2_normalize_x),
+ },
+ {
+ "fp16_neon_l2normalize_yz",
+ [](const L2NormalizeLayerSelectorData & data) { return data.dt == DataType::F16 && data.isa.fp16 && data.actual_axis != Window::DimX; },
+ REGISTER_FP16_NEON(arm_compute::cpu::neon_fp16_l2_normalize_yz),
+ },
+};
+
+/** Micro-kernel selector
+ *
+ * @param[in] data Selection data passed to help pick the appropriate micro-kernel
+ *
+ * @return A matching micro-kernel else nullptr
+ */
+const L2NormalizeLayerKernel *get_implementation(const L2NormalizeLayerSelectorData &data)
+{
+ for(const auto &uk : available_kernels)
+ {
+ if(uk.is_selected(data))
+ {
+ return &uk;
+ }
+ }
+ return nullptr;
}
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *sum, const ITensorInfo *output, int axis, float epsilon)
@@ -212,18 +188,10 @@
ARM_COMPUTE_ERROR("Unsupported normalization axis");
}
- switch(_input->info()->data_type())
- {
- case DataType::F32:
- (_actual_axis == Window::DimX) ? l2_normalize_X<float, 4>(_input, _sum, _output, _epsilon, window) : l2_normalize_YZ<float, 4>(_input, _sum, _output, _epsilon, window, _actual_axis);
- break;
-#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
- case DataType::F16:
- (_actual_axis == Window::DimX) ? l2_normalize_X<float16_t, 8>(_input, _sum, _output, _epsilon, window) : l2_normalize_YZ<float16_t, 8>(_input, _sum, _output, _epsilon, window, _actual_axis);
- break;
-#endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
- default:
- ARM_COMPUTE_ERROR("Not implemented");
- }
+ const auto *uk = get_implementation(L2NormalizeLayerSelectorData{ _output->info()->data_type(), _actual_axis, CPUInfo::get().get_isa() });
+ ARM_COMPUTE_ERROR_ON(uk == nullptr);
+ ARM_COMPUTE_ERROR_ON(uk->ukernel == nullptr);
+
+ uk->ukernel(_input, _sum, _output, _epsilon, window, _actual_axis);
}
} // namespace arm_compute
diff --git a/src/cpu/kernels/l2normlayer/generic/neon/fp16.cpp b/src/cpu/kernels/l2normlayer/generic/neon/fp16.cpp
new file mode 100644
index 0000000..ed84c10
--- /dev/null
+++ b/src/cpu/kernels/l2normlayer/generic/neon/fp16.cpp
@@ -0,0 +1,45 @@
+/*
+ * Copyright (c) 2022 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.
+ */
+#if defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) && defined(ENABLE_FP16_KERNELS)
+
+#include "src/cpu/kernels/l2normlayer/generic/neon/impl.h"
+
+#include "arm_compute/core/Helpers.h"
+namespace arm_compute
+{
+namespace cpu
+{
+void neon_fp16_l2_normalize_x(const ITensor *in, const ITensor *sum, ITensor *out, float epsilon, const Window &window, size_t unused_axis)
+{
+ ARM_COMPUTE_UNUSED(unused_axis);
+ return l2_normalize_x<float16_t, 8>(in, sum, out, epsilon, window);
+}
+
+void neon_fp16_l2_normalize_yz(const ITensor *in, const ITensor *sum, ITensor *out, float epsilon, const Window &window, size_t axis)
+{
+ return l2_normalize_yz<float16_t, 8>(in, sum, out, epsilon, window, axis);
+}
+} // namespace cpu
+} // namespace arm_compute
+#endif /* defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) && defined(ENABLE_FP16_KERNELS) */
diff --git a/src/cpu/kernels/l2normlayer/generic/neon/fp32.cpp b/src/cpu/kernels/l2normlayer/generic/neon/fp32.cpp
new file mode 100644
index 0000000..be32bdc
--- /dev/null
+++ b/src/cpu/kernels/l2normlayer/generic/neon/fp32.cpp
@@ -0,0 +1,45 @@
+/*
+ * Copyright (c) 2022 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 "src/cpu/kernels/l2normlayer/generic/neon/impl.h"
+
+#include "arm_compute/core/Helpers.h"
+
+namespace arm_compute
+{
+namespace cpu
+{
+void neon_fp32_l2_normalize_x(const ITensor *in, const ITensor *sum, ITensor *out, float epsilon, const Window &window, size_t unused_axis)
+{
+ ARM_COMPUTE_UNUSED(unused_axis);
+ return l2_normalize_x<float, 4>(in, sum, out, epsilon, window);
+}
+
+void neon_fp32_l2_normalize_yz(const ITensor *in, const ITensor *sum, ITensor *out, float epsilon, const Window &window, size_t axis)
+{
+ return l2_normalize_yz<float, 4>(in, sum, out, epsilon, window, axis);
+}
+
+} // namespace cpu
+} // namespace arm_compute
diff --git a/src/cpu/kernels/l2normlayer/generic/neon/impl.cpp b/src/cpu/kernels/l2normlayer/generic/neon/impl.cpp
new file mode 100644
index 0000000..2886537
--- /dev/null
+++ b/src/cpu/kernels/l2normlayer/generic/neon/impl.cpp
@@ -0,0 +1,131 @@
+/*
+ * Copyright (c) 2017-2022 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 "src/cpu/kernels/l2normlayer/generic/neon/impl.h"
+
+#include "arm_compute/core/Helpers.h"
+#include "arm_compute/core/TensorInfo.h"
+#include "src/core/NEON/wrapper/wrapper.h"
+#include "src/core/common/Registrars.h"
+
+#include <cstddef>
+
+namespace arm_compute
+{
+namespace cpu
+{
+template <typename T, int S>
+void l2_normalize_x(const ITensor *in, const ITensor *sum, ITensor *out, float epsilon, const Window &window)
+{
+ using ExactTagType = typename wrapper::traits::neon_vector<T, S>::tag_type;
+
+ const int window_step_x = 16 / data_size_from_type(in->info()->data_type());
+ 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_it(in, win_collapsed);
+ Iterator sum_it(sum, win_collapsed);
+ Iterator output_it(out, win_collapsed);
+
+ execute_window_loop(win_collapsed, [&](const Coordinates &)
+ {
+ const auto in_ptr = reinterpret_cast<const T *>(input_it.ptr());
+ const auto out_ptr = reinterpret_cast<T *>(output_it.ptr());
+
+ const T sum_value = *reinterpret_cast<const T *>(sum_it.ptr());
+ const T norm_value = static_cast<T>(1.f) / std::sqrt(std::max(sum_value, static_cast<T>(epsilon)));
+ const auto vec_norm_value = wrapper::vdup_n(norm_value, ExactTagType{});
+
+ // Compute elements over vector steps
+ int x = window_start_x;
+ for(; x <= (window_end_x - window_step_x); x += window_step_x)
+ {
+ wrapper::vstore(out_ptr + x, wrapper::vmul(wrapper::vloadq(in_ptr + x), vec_norm_value));
+ }
+
+ // Compute left-over elements
+ for(; x < window_end_x; ++x)
+ {
+ out_ptr[x] = in_ptr[x] * norm_value;
+ }
+ },
+ input_it, sum_it, output_it);
+}
+
+template <typename T, int S>
+void l2_normalize_yz(const ITensor *in, const ITensor *sum, ITensor *out, float epsilon, const Window &window, size_t axis)
+{
+ using ExactTagType = typename wrapper::traits::neon_vector<T, S>::tag_type;
+
+ const int window_step_x = 16 / data_size_from_type(in->info()->data_type());
+ const auto window_start_x = static_cast<int>(window.x().start());
+ const auto window_end_x = static_cast<int>(window.x().end());
+
+ Window win = window;
+ win.set(Window::DimX, Window::Dimension(0, 1, 1));
+
+ Window window_sum(win);
+ window_sum.set(axis, Window::Dimension(0, 0, 0));
+
+ Iterator input_it(in, win);
+ Iterator sum_it(sum, window_sum);
+ Iterator output_it(out, win);
+
+ const auto vec_eps = wrapper::vdup_n(static_cast<T>(epsilon), ExactTagType{});
+
+ execute_window_loop(win, [&](const Coordinates &)
+ {
+ const auto in_ptr = reinterpret_cast<const T *>(input_it.ptr());
+ const auto sum_ptr = reinterpret_cast<const T *>(sum_it.ptr());
+ const auto out_ptr = reinterpret_cast<T *>(output_it.ptr());
+
+ // Compute elements over vector steps
+ int x = window_start_x;
+ for(; x <= (window_end_x - window_step_x); x += window_step_x)
+ {
+ const auto vec_norm_value = wrapper::vinvsqrt(wrapper::vmax(wrapper::vloadq(sum_ptr + x), vec_eps));
+ wrapper::vstore(out_ptr + x, wrapper::vmul(wrapper::vloadq(in_ptr + x), vec_norm_value));
+ }
+
+ // Compute left-over elements
+ for(; x < window_end_x; ++x)
+ {
+ const T norm_value = static_cast<T>(1.f) / std::sqrt(std::max(sum_ptr[x], static_cast<T>(epsilon)));
+ out_ptr[x] = in_ptr[x] * norm_value;
+ }
+ },
+ input_it, sum_it, output_it);
+}
+
+template void l2_normalize_yz<float, 4>(const ITensor *in, const ITensor *sum, ITensor *out, float epsilon, const Window &window, size_t axis);
+template void l2_normalize_x<float, 4>(const ITensor *in, const ITensor *sum, ITensor *out, float epsilon, const Window &window);
+
+#if defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) && defined(ENABLE_FP16_KERNELS)
+template void l2_normalize_yz<float16_t, 8>(const ITensor *in, const ITensor *sum, ITensor *out, float epsilon, const Window &window, size_t axis);
+template void l2_normalize_x<float16_t, 8>(const ITensor *in, const ITensor *sum, ITensor *out, float epsilon, const Window &window);
+#endif //defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) && defined(ENABLE_FP16_KERNELS)
+} // namespace cpu
+} // namespace arm_compute
diff --git a/src/cpu/kernels/l2normlayer/generic/neon/impl.h b/src/cpu/kernels/l2normlayer/generic/neon/impl.h
new file mode 100644
index 0000000..98391fb
--- /dev/null
+++ b/src/cpu/kernels/l2normlayer/generic/neon/impl.h
@@ -0,0 +1,44 @@
+/*
+ * Copyright (c) 2022 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.
+ */
+#ifndef SRC_CORE_NEON_KERNELS_L2NORMLAYER_LIST_H
+#define SRC_CORE_NEON_KERNELS_L2NORMLAYER_LIST_H
+
+#include <cstddef>
+
+namespace arm_compute
+{
+class ITensor;
+class Window;
+
+namespace cpu
+{
+template <typename T, int S>
+void l2_normalize_x(const ITensor *in, const ITensor *sum, ITensor *out, float epsilon, const Window &window);
+
+template <typename T, int S>
+void l2_normalize_yz(const ITensor *in, const ITensor *sum, ITensor *out, float epsilon, const Window &window, size_t axis);
+
+} // namespace cpu
+} // namespace arm_compute
+#endif //SRC_CORE_NEON_KERNELS_L2NORMLAYER_LIST_H
diff --git a/src/cpu/kernels/l2normlayer/list.h b/src/cpu/kernels/l2normlayer/list.h
new file mode 100644
index 0000000..2bad7f5
--- /dev/null
+++ b/src/cpu/kernels/l2normlayer/list.h
@@ -0,0 +1,41 @@
+/*
+ * Copyright (c) 2022 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.
+ */
+#ifndef SRC_CORE_NEON_KERNELS_L2NORMLAYER_LIST_H
+#define SRC_CORE_NEON_KERNELS_L2NORMLAYER_LIST_H
+namespace arm_compute
+{
+namespace cpu
+{
+#define DECLARE_L2NORMLAYER_KERNEL(func_name) \
+ void func_name(const ITensor *in, const ITensor *sum, ITensor *out, float epsilon, const Window &window, size_t axis)
+
+DECLARE_L2NORMLAYER_KERNEL(neon_fp16_l2_normalize_x);
+DECLARE_L2NORMLAYER_KERNEL(neon_fp16_l2_normalize_yz);
+DECLARE_L2NORMLAYER_KERNEL(neon_fp32_l2_normalize_x);
+DECLARE_L2NORMLAYER_KERNEL(neon_fp32_l2_normalize_yz);
+
+#undef DECLARE_L2NORMLAYER_KERNEL
+} // namespace cpu
+} // namespace arm_compute
+#endif //SRC_CORE_NEON_KERNELS_L2NORMLAYER_LIST_H