Decouple CpuSoftmaxKernel

Resolves COMPMID-4633
Change-Id: I9f93b28fbc3b18ccaeb453596dc8e0eddfe06b6a
Signed-off-by: Dana Zlotnik <dana.zlotnik@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/6861
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Pablo Marquez Tello <pablo.tello@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
diff --git a/src/cpu/kernels/softmax/generic/neon/fp16.cpp b/src/cpu/kernels/softmax/generic/neon/fp16.cpp
new file mode 100644
index 0000000..3cb1cd6
--- /dev/null
+++ b/src/cpu/kernels/softmax/generic/neon/fp16.cpp
@@ -0,0 +1,44 @@
+/*
+ * Copyright (c) 2021-2022 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)
+#include "arm_compute/core/Helpers.h"
+#include "src/cpu/kernels/softmax/generic/neon/impl.h"
+
+namespace arm_compute
+{
+namespace cpu
+{
+void neon_fp16_softmax(const ITensor *in, const ITensor *max, void *const tmp,
+                       ITensor *out, const float beta, bool is_log, const Window &window)
+{
+    return neon_softmax_logits_1d_float<float16_t>(in, max, tmp, out, beta, is_log, window);
+}
+
+void neon_fp16_logits(const ITensor *in, ITensor *out, const Window &window)
+{
+    return neon_logits_1d_max<float16_t>(in, out, window);
+}
+}
+} // namespace arm_compute
+#endif //defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC)
diff --git a/src/cpu/kernels/softmax/generic/neon/fp32.cpp b/src/cpu/kernels/softmax/generic/neon/fp32.cpp
new file mode 100644
index 0000000..ddd270a
--- /dev/null
+++ b/src/cpu/kernels/softmax/generic/neon/fp32.cpp
@@ -0,0 +1,42 @@
+/*
+ * Copyright (c) 2021-2022 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 "arm_compute/core/Helpers.h"
+#include "src/cpu/kernels/softmax/generic/neon/impl.h"
+
+namespace arm_compute
+{
+namespace cpu
+{
+void neon_fp32_softmax(const ITensor *in, const ITensor *max, void *const tmp,
+                       ITensor *out, const float beta, bool is_log, const Window &window)
+{
+    return neon_softmax_logits_1d_float<float>(in, max, tmp, out, beta, is_log, window);
+}
+
+void neon_fp32_logits(const ITensor *in, ITensor *out, const Window &window)
+{
+    return neon_logits_1d_max<float>(in, out, window);
+}
+}
+} // namespace arm_compute
diff --git a/src/cpu/kernels/softmax/generic/neon/impl.h b/src/cpu/kernels/softmax/generic/neon/impl.h
new file mode 100644
index 0000000..325e127
--- /dev/null
+++ b/src/cpu/kernels/softmax/generic/neon/impl.h
@@ -0,0 +1,387 @@
+/*
+ * Copyright (c) 2021-2022 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_SOFTMAX_IMPL_H
+#define SRC_CORE_NEON_KERNELS_SOFTMAX_IMPL_H
+
+#include "src/core/NEON/NEMath.h"
+#include "src/core/NEON/wrapper/wrapper.h"
+#include "support/SaturateCast.h"
+
+namespace arm_compute
+{
+namespace cpu
+{
+template <typename T>
+void neon_logits_1d_max(const ITensor *in, ITensor *out, const Window &window)
+{
+    /** SIMD vector tag type. */
+    using ExactTagType = typename wrapper::traits::neon_bitvector_tag_t<T, wrapper::traits::BitWidth::W128>;
+
+    constexpr int window_step_x  = 16 / sizeof(T);
+    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));
+    Iterator input(in, win);
+    Iterator output(out, win);
+
+    const int sum_stages = log2(window_step_x / 2);
+    execute_window_loop(win, [&](const Coordinates &)
+    {
+        // Get pointers
+        const auto in_ptr  = reinterpret_cast<const T *>(input.ptr());
+        const auto out_ptr = reinterpret_cast<T *>(output.ptr());
+
+        // Init max value
+        auto vec_max = wrapper::vdup_n(support::cpp11::lowest<T>(), ExactTagType{});
+        int  x       = window_start_x;
+
+        for(; x <= (window_end_x - window_step_x); x += window_step_x)
+        {
+            const auto current_value = wrapper::vloadq(in_ptr + x);
+            vec_max                  = wrapper::vmax(vec_max, current_value);
+        }
+        auto carry_max = wrapper::vpmax(wrapper::vgethigh(vec_max), wrapper::vgetlow(vec_max));
+
+        for(int i = 0; i < sum_stages; ++i)
+        {
+            carry_max = wrapper::vpmax(carry_max, carry_max);
+        }
+        T max_val = wrapper::vgetlane(carry_max, 0);
+
+        // Compute left-over elements
+        for(; x < window_end_x; ++x)
+        {
+            max_val = *(in_ptr + x) > max_val ? *(in_ptr + x) : max_val;
+        }
+
+        *out_ptr = max_val;
+    },
+    input, output);
+}
+
+template <typename T>
+void neon_softmax_logits_1d_quantized(const ITensor *in, const ITensor *max, void *const tmp,
+                                      ITensor *out, float beta, bool is_log, const Window &window)
+{
+    static_assert(std::is_same<T, qasymm8_t>::value
+                  || std::is_same<T, qasymm8_signed_t>::value,
+                  "quantized type should be either qasymm8_t or qasymm8_signed_t.");
+
+    const int start_x     = in->info()->valid_region().anchor.x();
+    const int input_width = in->info()->valid_region().shape.x();
+
+    const float scale_beta     = -beta * in->info()->quantization_info().uniform().scale;
+    const auto  scale_beta_vec = vdupq_n_f32(scale_beta);
+
+    Iterator      in_it(in, window);
+    Iterator      max_it(max, window);
+    Iterator      out_it(out, window);
+    constexpr int vec_size = 16;
+
+    execute_window_loop(window, [&](const Coordinates &)
+    {
+        /* Get pointers */
+        const auto in_ptr  = reinterpret_cast<const T *>(in_it.ptr()) + start_x;
+        const auto out_ptr = reinterpret_cast<T *>(out_it.ptr()) + start_x;
+        const auto tmp_ptr = reinterpret_cast<float *>(tmp);
+
+        float sum{};
+        float sum_inversed{};
+
+        /* Compute exponentials and sum */
+        {
+            /* Get max value */
+            const auto max_val = *reinterpret_cast<const T *>(max_it.ptr());
+            const auto vec_max = wrapper::vdup_n(max_val, wrapper::traits::vector_128_tag{});
+
+            /* Init sum to zero */
+            float32x4x4_t vec_sum =
+            {
+                vdupq_n_f32(0.f),
+                vdupq_n_f32(0.f),
+                vdupq_n_f32(0.f),
+                vdupq_n_f32(0.f),
+            };
+
+            /* Loop over row and compute exponentials and sum */
+            int x = 0;
+            for(; x <= (input_width - vec_size); x += vec_size)
+            {
+                auto vec_elements     = wrapper::vloadq(in_ptr + x);
+                vec_elements          = wrapper::vqsub(vec_max, vec_elements);
+                auto vec_elements_flt = convert_int_to_float<float32x4x4_t>(vec_elements);
+
+                if(is_log)
+                {
+                    vec_elements_flt.val[0] = vmulq_f32(vec_elements_flt.val[0], scale_beta_vec);
+                    vec_elements_flt.val[1] = vmulq_f32(vec_elements_flt.val[1], scale_beta_vec);
+                    vec_elements_flt.val[2] = vmulq_f32(vec_elements_flt.val[2], scale_beta_vec);
+                    vec_elements_flt.val[3] = vmulq_f32(vec_elements_flt.val[3], scale_beta_vec);
+                    vec_sum.val[0]          = vaddq_f32(vec_sum.val[0], vexpq_f32(vec_elements_flt.val[0]));
+                    vec_sum.val[1]          = vaddq_f32(vec_sum.val[1], vexpq_f32(vec_elements_flt.val[1]));
+                    vec_sum.val[2]          = vaddq_f32(vec_sum.val[2], vexpq_f32(vec_elements_flt.val[2]));
+                    vec_sum.val[3]          = vaddq_f32(vec_sum.val[3], vexpq_f32(vec_elements_flt.val[3]));
+                }
+                else
+                {
+                    vec_elements_flt.val[0] = vexpq_f32(vmulq_f32(vec_elements_flt.val[0], scale_beta_vec));
+                    vec_elements_flt.val[1] = vexpq_f32(vmulq_f32(vec_elements_flt.val[1], scale_beta_vec));
+                    vec_elements_flt.val[2] = vexpq_f32(vmulq_f32(vec_elements_flt.val[2], scale_beta_vec));
+                    vec_elements_flt.val[3] = vexpq_f32(vmulq_f32(vec_elements_flt.val[3], scale_beta_vec));
+                    vec_sum.val[0]          = vaddq_f32(vec_sum.val[0], vec_elements_flt.val[0]);
+                    vec_sum.val[1]          = vaddq_f32(vec_sum.val[1], vec_elements_flt.val[1]);
+                    vec_sum.val[2]          = vaddq_f32(vec_sum.val[2], vec_elements_flt.val[2]);
+                    vec_sum.val[3]          = vaddq_f32(vec_sum.val[3], vec_elements_flt.val[3]);
+                }
+
+                vst4q_f32(tmp_ptr + x, vec_elements_flt);
+            }
+
+            /* Reduce sum */
+            const auto sum_16_byte = vaddq_f32(vaddq_f32(vec_sum.val[0], vec_sum.val[1]), vaddq_f32(vec_sum.val[2], vec_sum.val[3]));
+            auto       sum_res     = vpadd_f32(vget_high_f32(sum_16_byte), vget_low_f32(sum_16_byte));
+            sum_res                = vpadd_f32(sum_res, sum_res);
+            sum                    = wrapper::vgetlane(sum_res, 0);
+
+            /* Run remaining elements */
+            for(; x < input_width; ++x)
+            {
+                float element{};
+                if(is_log)
+                {
+                    element = (max_val - in_ptr[x]) * scale_beta;
+                    sum += std::exp(element);
+                }
+                else
+                {
+                    element = std::exp((max_val - in_ptr[x]) * scale_beta);
+                    sum += element;
+                }
+
+                tmp_ptr[x] = element;
+            }
+
+            if(!is_log)
+            {
+                sum_inversed = 256.f / sum;
+            }
+            else
+            {
+                sum = std::log(sum);
+            }
+        }
+
+        /* Normalize exponentials */
+        {
+            constexpr bool is_qasymm8_signed = std::is_same<T, qasymm8_signed_t>::value;
+            /* Loop over row and compute softmax */
+            int x = 0;
+            for(; x <= (input_width - vec_size); x += vec_size)
+            {
+                using int_vec_type   = wrapper::traits::neon_vector_t<T, 16>;
+                float32x4x4_t vec_in = vld4q_f32(tmp_ptr + x);
+                int_vec_type  normalized_value{};
+                if(is_log)
+                {
+                    const float32x4x4_t sub =
+                    {
+                        vsubq_f32(vec_in.val[0], vdupq_n_f32(sum)),
+                        vsubq_f32(vec_in.val[1], vdupq_n_f32(sum)),
+                        vsubq_f32(vec_in.val[2], vdupq_n_f32(sum)),
+                        vsubq_f32(vec_in.val[3], vdupq_n_f32(sum)),
+                    };
+                    normalized_value = convert_float_to_int<float32x4x4_t, int_vec_type>(sub);
+                }
+                else
+                {
+                    float32x4x4_t mul =
+                    {
+                        vmulq_f32(vec_in.val[0], vdupq_n_f32(sum_inversed)),
+                        vmulq_f32(vec_in.val[1], vdupq_n_f32(sum_inversed)),
+                        vmulq_f32(vec_in.val[2], vdupq_n_f32(sum_inversed)),
+                        vmulq_f32(vec_in.val[3], vdupq_n_f32(sum_inversed)),
+                    };
+
+                    if(is_qasymm8_signed)
+                    {
+                        const auto offset_vec = wrapper::vdup_n(128.f, wrapper::traits::vector_128_tag{});
+                        mul.val[0]            = wrapper::vsub(mul.val[0], offset_vec);
+                        mul.val[1]            = wrapper::vsub(mul.val[1], offset_vec);
+                        mul.val[2]            = wrapper::vsub(mul.val[2], offset_vec);
+                        mul.val[3]            = wrapper::vsub(mul.val[3], offset_vec);
+                    }
+
+                    normalized_value = convert_float_to_int<float32x4x4_t, int_vec_type>(mul);
+                }
+                wrapper::vstore(out_ptr + x, normalized_value);
+            }
+            /* Run remaining elements */
+            for(; x < input_width; ++x)
+            {
+                if(is_log)
+                {
+                    out_ptr[x] = utils::cast::saturate_cast<T>(tmp_ptr[x] - sum);
+                }
+                else
+                {
+                    out_ptr[x] = utils::cast::saturate_cast<T>((tmp_ptr[x] * sum_inversed) - (is_qasymm8_signed ? 128.f : 0));
+                }
+            }
+        }
+    },
+    in_it, max_it, out_it);
+}
+
+template <typename T>
+void neon_softmax_logits_1d_float(const ITensor *in, const ITensor *max, void *const tmp,
+                                  ITensor *out, const float beta, bool is_log, const Window &window)
+{
+    const int start_x     = in->info()->valid_region().anchor.x();
+    const int input_width = in->info()->valid_region().shape.x();
+
+    Iterator in_it(in, window);
+    Iterator max_it(max, window);
+    Iterator out_it(out, window);
+
+    /** SIMD vector tag type. */
+    using ExactTagType = typename wrapper::traits::neon_bitvector_tag_t<T, wrapper::traits::BitWidth::W128>;
+
+    constexpr int vec_size   = 16 / sizeof(T);
+    const int     sum_stages = log2(vec_size / 2);
+
+    execute_window_loop(window, [&](const Coordinates &)
+    {
+        /* Get pointers */
+        const auto in_ptr  = reinterpret_cast<const T *>(in_it.ptr()) + start_x;
+        const auto out_ptr = reinterpret_cast<T *>(out_it.ptr()) + start_x;
+        const auto tmp_ptr = reinterpret_cast<T *>(tmp);
+
+        T sum{};
+        T sum_inversed{};
+
+        /* Compute exponentials and sum */
+        {
+            /* Get max value */
+            const auto max_val = *reinterpret_cast<const T *>(max_it.ptr());
+            const auto vec_max = wrapper::vdup_n(max_val, ExactTagType{});
+
+            /* Init sum to zero */
+            auto vec_sum = wrapper::vdup_n(static_cast<T>(0), ExactTagType{});
+
+            /* Loop over row and compute exponentials and sum */
+            int x = 0;
+            for(; x <= (input_width - vec_size); x += vec_size)
+            {
+                auto vec_elements = wrapper::vloadq(in_ptr + x);
+                vec_elements      = wrapper::vsub(vec_elements, vec_max);
+                if(is_log)
+                {
+                    vec_elements = wrapper::vmul(vec_elements, wrapper::vdup_n(static_cast<T>(beta), ExactTagType{}));
+                    vec_sum      = wrapper::vadd(vec_sum, wrapper::vexpq(vec_elements));
+                }
+                else
+                {
+                    vec_elements = wrapper::vexpq(wrapper::vmul(vec_elements, wrapper::vdup_n(static_cast<T>(beta), ExactTagType{})));
+                    vec_sum      = wrapper::vadd(vec_sum, vec_elements);
+                }
+                wrapper::vstore(tmp_ptr + x, vec_elements);
+            }
+
+            /* Reduce sum */
+            auto sum_res = wrapper::vpadd(wrapper::vgethigh(vec_sum), wrapper::vgetlow(vec_sum));
+            for(int i = 0; i < sum_stages; ++i)
+            {
+                sum_res = wrapper::vpadd(sum_res, sum_res);
+            }
+            sum = wrapper::vgetlane(sum_res, 0);
+
+            /* Run remaining elements */
+            for(; x < input_width; ++x)
+            {
+                T element{};
+
+                if(is_log)
+                {
+                    element = (in_ptr[x] - max_val) * beta;
+                    sum += std::exp(element);
+                }
+                else
+                {
+                    element = std::exp((in_ptr[x] - max_val) * beta);
+                    sum += element;
+                }
+                tmp_ptr[x] = element;
+            }
+
+            if(!is_log)
+            {
+                sum_inversed = T(1) / sum;
+            }
+            else
+            {
+                sum = static_cast<T>(std::log(sum));
+            }
+        }
+
+        /* Normalize exponentials */
+        {
+            /* Loop over row and compute softmax */
+            int x = 0;
+            for(; x <= (input_width - vec_size); x += vec_size)
+            {
+                auto vec_in           = wrapper::vloadq(tmp_ptr + x);
+                auto normalized_value = wrapper::vdup_n(static_cast<T>(0), ExactTagType{});
+                if(is_log)
+                {
+                    normalized_value = wrapper::vsub(vec_in, wrapper::vdup_n(static_cast<T>(sum), ExactTagType{}));
+                }
+                else
+                {
+                    normalized_value = wrapper::vmul(vec_in, wrapper::vdup_n(static_cast<T>(sum_inversed), ExactTagType{}));
+                }
+                wrapper::vstore(out_ptr + x, normalized_value);
+            }
+            /* Run remaining elements */
+            for(; x < input_width; ++x)
+            {
+                if(is_log)
+                {
+                    out_ptr[x] = tmp_ptr[x] - sum;
+                }
+                else
+                {
+                    out_ptr[x] = tmp_ptr[x] * sum_inversed;
+                }
+            }
+        }
+    },
+    in_it, max_it, out_it);
+}
+
+} // namespace cpu
+} // namespace arm_compute
+
+#endif /* SRC_CORE_NEON_KERNELS_SOFTMAX_IMPL_H */
diff --git a/src/cpu/kernels/softmax/generic/neon/qasymm8.cpp b/src/cpu/kernels/softmax/generic/neon/qasymm8.cpp
new file mode 100644
index 0000000..a572891
--- /dev/null
+++ b/src/cpu/kernels/softmax/generic/neon/qasymm8.cpp
@@ -0,0 +1,42 @@
+/*
+ * Copyright (c) 2021-2022 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 "arm_compute/core/Helpers.h"
+#include "src/cpu/kernels/softmax/generic/neon/impl.h"
+
+namespace arm_compute
+{
+namespace cpu
+{
+void neon_qasymm8_softmax(const ITensor *in, const ITensor *max, void *const tmp,
+                          ITensor *out, const float beta, bool is_log, const Window &window)
+{
+    return neon_softmax_logits_1d_quantized<qasymm8_t>(in, max, tmp, out, beta, is_log, window);
+}
+
+void neon_qasymm8_logits(const ITensor *in, ITensor *out, const Window &window)
+{
+    return neon_logits_1d_max<qasymm8_t>(in, out, window);
+}
+}
+} // namespace arm_compute
diff --git a/src/cpu/kernels/softmax/generic/neon/qasymm8_signed.cpp b/src/cpu/kernels/softmax/generic/neon/qasymm8_signed.cpp
new file mode 100644
index 0000000..7d3fe6e
--- /dev/null
+++ b/src/cpu/kernels/softmax/generic/neon/qasymm8_signed.cpp
@@ -0,0 +1,42 @@
+/*
+ * Copyright (c) 2021-2022 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 "arm_compute/core/Helpers.h"
+#include "src/cpu/kernels/softmax/generic/neon/impl.h"
+
+namespace arm_compute
+{
+namespace cpu
+{
+void neon_qasymm8_signed_softmax(const ITensor *in, const ITensor *max, void *const tmp,
+                                 ITensor *out, const float beta, bool is_log, const Window &window)
+{
+    return neon_softmax_logits_1d_quantized<qasymm8_signed_t>(in, max, tmp, out, beta, is_log, window);
+}
+
+void neon_qasymm8_singed_logits(const ITensor *in, ITensor *out, const Window &window)
+{
+    return neon_logits_1d_max<qasymm8_signed_t>(in, out, window);
+}
+}
+} // namespace arm_compute
diff --git a/src/cpu/kernels/softmax/generic/sve/fp16.cpp b/src/cpu/kernels/softmax/generic/sve/fp16.cpp
new file mode 100644
index 0000000..89be6c5
--- /dev/null
+++ b/src/cpu/kernels/softmax/generic/sve/fp16.cpp
@@ -0,0 +1,43 @@
+/*
+ * Copyright (c) 2021-2022 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_COMPUTE_ENABLE_SVE)
+#include "arm_compute/core/Helpers.h"
+#include "src/cpu/kernels/softmax/generic/sve/impl.h"
+namespace arm_compute
+{
+namespace cpu
+{
+void sve_fp16_softmax(const ITensor *in, const ITensor *max, void *const tmp,
+                      ITensor *out, const float beta, bool is_log, const Window &window)
+{
+    return sve_softmax_logits_1d_float<float16_t>(in, max, tmp, out, beta, is_log, window);
+}
+
+void sve_fp16_logits(const ITensor *in, ITensor *out, const Window &window)
+{
+    return sve_logits_1d_max<float16_t>(in, out, window);
+}
+}
+} // namespace arm_compute
+#endif //ARM_COMPUTE_ENABLE_SVE
diff --git a/src/cpu/kernels/softmax/generic/sve/fp32.cpp b/src/cpu/kernels/softmax/generic/sve/fp32.cpp
new file mode 100644
index 0000000..79130bf
--- /dev/null
+++ b/src/cpu/kernels/softmax/generic/sve/fp32.cpp
@@ -0,0 +1,44 @@
+/*
+ * Copyright (c) 2021-2022 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_COMPUTE_ENABLE_SVE)
+#include "arm_compute/core/Helpers.h"
+#include "src/cpu/kernels/softmax/generic/sve/impl.h"
+
+namespace arm_compute
+{
+namespace cpu
+{
+void sve_fp32_softmax(const ITensor *in, const ITensor *max, void *const tmp,
+                      ITensor *out, const float beta, bool is_log, const Window &window)
+{
+    return sve_softmax_logits_1d_float<float>(in, max, tmp, out, beta, is_log, window);
+}
+
+void sve_fp32_logits(const ITensor *in, ITensor *out, const Window &window)
+{
+    return sve_logits_1d_max<float>(in, out, window);
+}
+}
+} // namespace arm_compute
+#endif //ARM_COMPUTE_ENABLE_SVE
diff --git a/src/cpu/kernels/softmax/generic/sve/impl.cpp b/src/cpu/kernels/softmax/generic/sve/impl.cpp
new file mode 100644
index 0000000..f17e50e
--- /dev/null
+++ b/src/cpu/kernels/softmax/generic/sve/impl.cpp
@@ -0,0 +1,179 @@
+/*
+ * Copyright (c) 2021-2022 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_COMPUTE_ENABLE_SVE)
+#include "src/cpu/kernels/softmax/generic/sve/impl.h"
+#include "src/core/NEON/wrapper/intrinsics/intrinsics.h"
+
+namespace arm_compute
+{
+namespace cpu
+{
+template <typename ScalarType>
+void sve_logits_1d_max(const ITensor *in, ITensor *out, const Window &window)
+{
+    const auto all_true_pg    = wrapper::svptrue<ScalarType>();
+    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));
+    Iterator input(in, win);
+    Iterator output(out, win);
+
+    execute_window_loop(win, [&](const Coordinates &)
+    {
+        // Get pointers
+        const auto in_ptr  = reinterpret_cast<const ScalarType *>(input.ptr());
+        const auto out_ptr = reinterpret_cast<ScalarType *>(output.ptr());
+
+        // Init max value
+        auto vec_max = wrapper::svdup_n(support::cpp11::lowest<ScalarType>());
+
+        int      x  = window_start_x;
+        svbool_t pg = wrapper::svwhilelt<ScalarType>(x, window_end_x);
+        do
+        {
+            const auto current_value = svld1(pg, in_ptr + x);
+            vec_max                  = svmax_m(pg, vec_max, current_value);
+
+            x += wrapper::svcnt<ScalarType>();
+            pg = wrapper::svwhilelt<ScalarType>(x, window_end_x);
+        }
+        while(svptest_any(all_true_pg, pg));
+
+        auto max_val = svmaxv(all_true_pg, vec_max);
+
+        *out_ptr = max_val;
+    },
+    input, output);
+}
+
+template <typename ScalarType>
+void sve_softmax_logits_1d_float(const ITensor *in, const ITensor *max, void *const tmp,
+                                 ITensor *out, const float beta, bool is_log, const Window &window)
+{
+    const int start_x     = in->info()->valid_region().anchor.x();
+    const int input_width = in->info()->valid_region().shape.x();
+
+    Iterator in_it(in, window);
+    Iterator max_it(max, window);
+    Iterator out_it(out, window);
+
+    const auto all_true_pg = wrapper::svptrue<ScalarType>();
+
+    execute_window_loop(window, [&](const Coordinates &)
+    {
+        /* Get pointers */
+        const auto in_ptr  = reinterpret_cast<const ScalarType *>(in_it.ptr()) + start_x;
+        const auto out_ptr = reinterpret_cast<ScalarType *>(out_it.ptr()) + start_x;
+        const auto tmp_ptr = reinterpret_cast<ScalarType *>(tmp);
+
+        ScalarType sum{ 0 };
+
+        /* Compute exponentials and sum */
+        {
+            /* Get max value */
+            const auto max_val = *reinterpret_cast<const ScalarType *>(max_it.ptr());
+            const auto vec_max = wrapper::svdup_n(max_val);
+
+            /* Init sum to zero */
+            auto vec_sum = wrapper::svdup_n(static_cast<ScalarType>(0));
+
+            /* Loop over row and compute exponentials and sum */
+            int      x  = 0;
+            svbool_t pg = wrapper::svwhilelt<ScalarType>(x, input_width);
+            do
+            {
+                auto vec_elements = svld1(pg, in_ptr + x);
+                vec_elements      = svsub_z(pg, vec_elements, vec_max);
+                if(is_log)
+                {
+                    vec_elements = svmul_z(pg, vec_elements, wrapper::svdup_n(static_cast<ScalarType>(beta)));
+                    vec_sum      = svadd_m(pg, vec_sum, wrapper::svexp_z(pg, vec_elements));
+                }
+                else
+                {
+                    vec_elements = wrapper::svexp_z(pg, svmul_z(pg, vec_elements, wrapper::svdup_n(static_cast<ScalarType>(beta))));
+                    vec_sum      = svadd_m(pg, vec_sum, vec_elements);
+                }
+                svst1(pg, tmp_ptr + x, vec_elements);
+
+                x += wrapper::svcnt<ScalarType>();
+                pg = wrapper::svwhilelt<ScalarType>(x, input_width);
+            }
+            while(svptest_any(all_true_pg, pg));
+
+            /* Reduce sum */
+            sum = svaddv(all_true_pg, vec_sum);
+
+            if(is_log)
+            {
+                sum = static_cast<ScalarType>(std::log(sum));
+            }
+            else
+            {
+                sum = ScalarType(1) / sum;
+            }
+        }
+
+        /* Normalize exponentials */
+        {
+            /* Loop over row and compute softmax */
+            int      x  = 0;
+            svbool_t pg = wrapper::svwhilelt<ScalarType>(x, input_width);
+            do
+            {
+                auto vec_in           = svld1(pg, tmp_ptr + x);
+                auto normalized_value = wrapper::svdup_n(static_cast<ScalarType>(0));
+                if(is_log)
+                {
+                    normalized_value = svsub_z(pg, vec_in, wrapper::svdup_n(static_cast<ScalarType>(sum)));
+                }
+                else
+                {
+                    normalized_value = svmul_z(pg, vec_in, wrapper::svdup_n(static_cast<ScalarType>(sum)));
+                }
+                svst1(pg, out_ptr + x, normalized_value);
+
+                x += wrapper::svcnt<ScalarType>();
+                pg = wrapper::svwhilelt<ScalarType>(x, input_width);
+            }
+            while(svptest_any(all_true_pg, pg));
+        }
+    },
+    in_it, max_it, out_it);
+}
+
+template void sve_logits_1d_max<float>(const ITensor *in, ITensor *out, const Window &window);
+template void sve_logits_1d_max<float16_t>(const ITensor *in, ITensor *out, const Window &window);
+template void sve_logits_1d_max<qasymm8_t>(const ITensor *in, ITensor *out, const Window &window);
+template void sve_logits_1d_max<qasymm8_signed_t>(const ITensor *in, ITensor *out, const Window &window);
+
+template void sve_softmax_logits_1d_float<float>(const ITensor *in, const ITensor *max, void *const tmp,
+                                                 ITensor *out, const float beta, bool is_log, const Window &window);
+template void sve_softmax_logits_1d_float<float16_t>(const ITensor *in, const ITensor *max, void *const tmp,
+                                                     ITensor *out, const float beta, bool is_log, const Window &window);
+} // namespace cpu
+} // namespace arm_compute
+#endif /* defined(ARM_COMPUTE_ENABLE_SVE) */
diff --git a/src/cpu/kernels/softmax/generic/sve/impl.h b/src/cpu/kernels/softmax/generic/sve/impl.h
new file mode 100644
index 0000000..1051f59
--- /dev/null
+++ b/src/cpu/kernels/softmax/generic/sve/impl.h
@@ -0,0 +1,43 @@
+/*
+ * Copyright (c) 2021-2022 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_SVE_KERNELS_SOFTMAX_IMPL_H
+#define SRC_CORE_SVE_KERNELS_SOFTMAX_IMPL_H
+
+#if defined(ARM_COMPUTE_ENABLE_SVE)
+#include "arm_compute/core/Helpers.h"
+namespace arm_compute
+{
+namespace cpu
+{
+template <typename ScalarType>
+void sve_logits_1d_max(const ITensor *in, ITensor *out, const Window &window);
+
+template <typename ScalarType>
+void sve_softmax_logits_1d_float(const ITensor *in, const ITensor *max, void *const tmp,
+                                 ITensor *out, const float beta, bool is_log, const Window &window);
+} // namespace cpu
+} // namespace arm_compute
+#endif /* defined(ARM_COMPUTE_ENABLE_SVE) */
+
+#endif /* SRC_CORE_SVE_KERNELS_SOFTMAX_IMPL_H */
diff --git a/src/cpu/kernels/softmax/generic/sve/qasymm8.cpp b/src/cpu/kernels/softmax/generic/sve/qasymm8.cpp
new file mode 100644
index 0000000..62afe4b
--- /dev/null
+++ b/src/cpu/kernels/softmax/generic/sve/qasymm8.cpp
@@ -0,0 +1,38 @@
+/*
+ * Copyright (c) 2021-2022 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_COMPUTE_ENABLE_SVE)
+#include "arm_compute/core/Helpers.h"
+#include "src/cpu/kernels/softmax/generic/sve/impl.h"
+
+namespace arm_compute
+{
+namespace cpu
+{
+void sve_qasymm8_logits(const ITensor *in, ITensor *out, const Window &window)
+{
+    return sve_logits_1d_max<qasymm8_t>(in, out, window);
+}
+}
+} // namespace arm_compute
+#endif //defined(ARM_COMPUTE_ENABLE_SVE)
diff --git a/src/cpu/kernels/softmax/generic/sve/qasymm8_signed.cpp b/src/cpu/kernels/softmax/generic/sve/qasymm8_signed.cpp
new file mode 100644
index 0000000..5547cc9
--- /dev/null
+++ b/src/cpu/kernels/softmax/generic/sve/qasymm8_signed.cpp
@@ -0,0 +1,38 @@
+/*
+ * Copyright (c) 2021-2022 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_COMPUTE_ENABLE_SVE)
+#include "arm_compute/core/Helpers.h"
+#include "src/cpu/kernels/softmax/generic/sve/impl.h"
+
+namespace arm_compute
+{
+namespace cpu
+{
+void sve_qasymm8_signed_logits(const ITensor *in, ITensor *out, const Window &window)
+{
+    return sve_logits_1d_max<qasymm8_signed_t>(in, out, window);
+}
+}
+} // namespace arm_compute
+#endif //defined(ARM_COMPUTE_ENABLE_SVE)
diff --git a/src/cpu/kernels/softmax/generic/sve2/impl.h b/src/cpu/kernels/softmax/generic/sve2/impl.h
new file mode 100644
index 0000000..16dde2b
--- /dev/null
+++ b/src/cpu/kernels/softmax/generic/sve2/impl.h
@@ -0,0 +1,210 @@
+/*
+ * Copyright (c) 2021-2022 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_SVE2_KERNELS_SOFTMAX_IMPL_H
+#define SRC_CORE_SVE2_KERNELS_SOFTMAX_IMPL_H
+
+#if defined(ARM_COMPUTE_ENABLE_SVE2)
+#include "arm_compute/core/Types.h"
+#include "src/core/NEON/wrapper/intrinsics/intrinsics.h"
+
+namespace arm_compute
+{
+namespace cpu
+{
+template <typename ScalarType>
+void sve2_softmax_logits_1d_quantized(const ITensor *in, const ITensor *max, void *const tmp,
+                                      ITensor *out, float beta, bool is_log, const Window &window)
+{
+    const int start_x     = in->info()->valid_region().anchor.x();
+    const int input_width = in->info()->valid_region().shape.x();
+
+    const float scale_beta     = -beta * in->info()->quantization_info().uniform().scale;
+    const auto  scale_beta_vec = svdup_n_f32(scale_beta);
+
+    Iterator   in_it(in, window);
+    Iterator   max_it(max, window);
+    Iterator   out_it(out, window);
+    const auto all_true_pg = wrapper::svptrue<ScalarType>();
+    using SVEType          = typename wrapper::traits::sve_vector<ScalarType>::type;
+
+    const int inc_1 = static_cast<int>(svcntw());
+    const int inc_2 = static_cast<int>(2 * svcntw());
+    const int inc_3 = static_cast<int>(3 * svcntw());
+
+    execute_window_loop(window, [&](const Coordinates &)
+    {
+        /* Get pointers */
+        const auto in_ptr  = reinterpret_cast<const ScalarType *>(in_it.ptr()) + start_x;
+        const auto out_ptr = reinterpret_cast<ScalarType *>(out_it.ptr()) + start_x;
+        const auto tmp_ptr = reinterpret_cast<float *>(tmp);
+
+        float sum{};
+
+        /* Compute exponentials and sum */
+        {
+            /* Get max value */
+            const auto max_val = *reinterpret_cast<const ScalarType *>(max_it.ptr());
+            const auto vec_max = wrapper::svdup_n(max_val);
+
+            /* Init sum to zero */
+            auto vec_sum_0 = svdup_n_f32(0.f);
+            auto vec_sum_1 = svdup_n_f32(0.f);
+            auto vec_sum_2 = svdup_n_f32(0.f);
+            auto vec_sum_3 = svdup_n_f32(0.f);
+
+            /* Loop over row and compute exponentials and sum */
+            int      x    = 0;
+            svbool_t pg   = wrapper::svwhilelt<ScalarType>(x, input_width);
+            svbool_t pg_0 = svunpklo(svunpklo(pg));
+            svbool_t pg_1 = svunpkhi(svunpklo(pg));
+            svbool_t pg_2 = svunpklo(svunpkhi(pg));
+            svbool_t pg_3 = svunpkhi(svunpkhi(pg));
+            do
+            {
+                auto vec_elements = svld1(pg, in_ptr + x);
+                vec_elements      = svsub_z(pg, vec_max, vec_elements);
+
+                auto vec_elements_flt_0 = svcvt_f32_z(pg_0, svunpklo(svunpklo(vec_elements)));
+                auto vec_elements_flt_1 = svcvt_f32_z(pg_1, svunpkhi(svunpklo(vec_elements)));
+                auto vec_elements_flt_2 = svcvt_f32_z(pg_2, svunpklo(svunpkhi(vec_elements)));
+                auto vec_elements_flt_3 = svcvt_f32_z(pg_3, svunpkhi(svunpkhi(vec_elements)));
+
+                if(is_log)
+                {
+                    vec_elements_flt_0 = svmul_f32_z(pg_0, vec_elements_flt_0, scale_beta_vec);
+                    vec_elements_flt_1 = svmul_f32_z(pg_1, vec_elements_flt_1, scale_beta_vec);
+                    vec_elements_flt_2 = svmul_f32_z(pg_2, vec_elements_flt_2, scale_beta_vec);
+                    vec_elements_flt_3 = svmul_f32_z(pg_3, vec_elements_flt_3, scale_beta_vec);
+                    vec_sum_0          = svadd_f32_m(pg_0, vec_sum_0, svexp_f32_z(pg_0, vec_elements_flt_0));
+                    vec_sum_1          = svadd_f32_m(pg_1, vec_sum_1, svexp_f32_z(pg_1, vec_elements_flt_1));
+                    vec_sum_2          = svadd_f32_m(pg_2, vec_sum_2, svexp_f32_z(pg_2, vec_elements_flt_2));
+                    vec_sum_3          = svadd_f32_m(pg_3, vec_sum_3, svexp_f32_z(pg_3, vec_elements_flt_3));
+                }
+                else
+                {
+                    vec_elements_flt_0 = svexp_f32_z(pg_0, svmul_f32_z(pg_0, vec_elements_flt_0, scale_beta_vec));
+                    vec_elements_flt_1 = svexp_f32_z(pg_1, svmul_f32_z(pg_1, vec_elements_flt_1, scale_beta_vec));
+                    vec_elements_flt_2 = svexp_f32_z(pg_2, svmul_f32_z(pg_2, vec_elements_flt_2, scale_beta_vec));
+                    vec_elements_flt_3 = svexp_f32_z(pg_3, svmul_f32_z(pg_3, vec_elements_flt_3, scale_beta_vec));
+                    vec_sum_0          = svadd_f32_m(pg_0, vec_sum_0, vec_elements_flt_0);
+                    vec_sum_1          = svadd_f32_m(pg_1, vec_sum_1, vec_elements_flt_1);
+                    vec_sum_2          = svadd_f32_m(pg_2, vec_sum_2, vec_elements_flt_2);
+                    vec_sum_3          = svadd_f32_m(pg_3, vec_sum_3, vec_elements_flt_3);
+                }
+
+                svst1_f32(pg_0, tmp_ptr + x, vec_elements_flt_0);
+                svst1_f32(pg_1, tmp_ptr + x + inc_1, vec_elements_flt_1);
+                svst1_f32(pg_2, tmp_ptr + x + inc_2, vec_elements_flt_2);
+                svst1_f32(pg_3, tmp_ptr + x + inc_3, vec_elements_flt_3);
+
+                x += wrapper::svcnt<ScalarType>();
+                pg   = wrapper::svwhilelt<ScalarType>(x, input_width);
+                pg_0 = svunpklo(svunpklo(pg));
+                pg_1 = svunpkhi(svunpklo(pg));
+                pg_2 = svunpklo(svunpkhi(pg));
+                pg_3 = svunpkhi(svunpkhi(pg));
+            }
+            while(svptest_any(all_true_pg, pg));
+
+            /* Reduce sum */
+            const auto vec_sum = svadd_f32_z(all_true_pg, svadd_f32_z(all_true_pg, vec_sum_0, vec_sum_1), svadd_f32_z(all_true_pg, vec_sum_2, vec_sum_3));
+            sum                = svaddv_f32(all_true_pg, vec_sum);
+
+            /* Run remaining elements */
+            x = 0;
+            if(is_log)
+            {
+                sum = std::log(sum);
+            }
+            else
+            {
+                sum = 256.f / sum;
+            }
+        }
+
+        /* Normalize exponentials */
+        {
+            constexpr bool is_qasymm8_signed = std::is_same<ScalarType, qasymm8_signed_t>::value;
+            /* Loop over row and compute softmax */
+            int      x    = 0;
+            svbool_t pg   = wrapper::svwhilelt<ScalarType>(x, input_width);
+            svbool_t pg_0 = svunpklo(svunpklo(pg));
+            svbool_t pg_1 = svunpkhi(svunpklo(pg));
+            svbool_t pg_2 = svunpklo(svunpkhi(pg));
+            svbool_t pg_3 = svunpkhi(svunpkhi(pg));
+            do
+            {
+                auto vec_in_0 = svld1_f32(pg_0, tmp_ptr + x);
+                auto vec_in_1 = svld1_f32(pg_1, tmp_ptr + x + inc_1);
+                auto vec_in_2 = svld1_f32(pg_2, tmp_ptr + x + inc_2);
+                auto vec_in_3 = svld1_f32(pg_3, tmp_ptr + x + inc_3);
+
+                svfloat32_t res_0{};
+                svfloat32_t res_1{};
+                svfloat32_t res_2{};
+                svfloat32_t res_3{};
+
+                if(is_log)
+                {
+                    res_0 = svsub_f32_z(pg_0, vec_in_0, svdup_n_f32(sum));
+                    res_1 = svsub_f32_z(pg_1, vec_in_1, svdup_n_f32(sum));
+                    res_2 = svsub_f32_z(pg_2, vec_in_2, svdup_n_f32(sum));
+                    res_3 = svsub_f32_z(pg_3, vec_in_3, svdup_n_f32(sum));
+                }
+                else
+                {
+                    res_0 = svmul_f32_z(pg_0, vec_in_0, svdup_n_f32(sum));
+                    res_1 = svmul_f32_z(pg_1, vec_in_1, svdup_n_f32(sum));
+                    res_2 = svmul_f32_z(pg_2, vec_in_2, svdup_n_f32(sum));
+                    res_3 = svmul_f32_z(pg_3, vec_in_3, svdup_n_f32(sum));
+
+                    if(is_qasymm8_signed)
+                    {
+                        const auto offset_vec = svdup_n_f32(128.f);
+                        res_0                 = svsub_z(pg_0, vec_in_0, offset_vec);
+                        res_1                 = svsub_z(pg_1, vec_in_1, offset_vec);
+                        res_2                 = svsub_z(pg_2, vec_in_2, offset_vec);
+                        res_3                 = svsub_z(pg_3, vec_in_3, offset_vec);
+                    }
+                }
+
+                // Store value
+                const auto out = convert_float_to_int<SVEType>(res_0, res_1, res_2, res_3);
+                svst1(pg, out_ptr + x, out);
+                x += wrapper::svcnt<ScalarType>();
+                pg   = wrapper::svwhilelt<ScalarType>(x, input_width);
+                pg_0 = svunpklo(svunpklo(pg));
+                pg_1 = svunpkhi(svunpklo(pg));
+                pg_2 = svunpklo(svunpkhi(pg));
+                pg_3 = svunpkhi(svunpkhi(pg));
+            }
+            while(svptest_any(all_true_pg, pg));
+        }
+    },
+    in_it, max_it, out_it);
+}
+} // namespace cpu
+} // namespace arm_compute
+#endif /* defined(ARM_COMPUTE_ENABLE_SVE2) */
+#endif /* SRC_CORE_SVE2_KERNELS_SOFTMAX_IMPL_H */
diff --git a/src/cpu/kernels/softmax/generic/sve2/qasymm8.cpp b/src/cpu/kernels/softmax/generic/sve2/qasymm8.cpp
new file mode 100644
index 0000000..8566a51
--- /dev/null
+++ b/src/cpu/kernels/softmax/generic/sve2/qasymm8.cpp
@@ -0,0 +1,39 @@
+/*
+ * Copyright (c) 2021-2022 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_COMPUTE_ENABLE_SVE2)
+#include "arm_compute/core/Helpers.h"
+#include "src/cpu/kernels/softmax/generic/sve2/impl.h"
+
+namespace arm_compute
+{
+namespace cpu
+{
+void sve2_qasymm8_softmax(const ITensor *in, const ITensor *max, void *const tmp,
+                          ITensor *out, const float beta, bool is_log, const Window &window)
+{
+    return sve2_softmax_logits_1d_quantized<qasymm8_t>(in, max, tmp, out, beta, is_log, window);
+}
+}
+} // namespace arm_compute
+#endif //defined(ARM_COMPUTE_ENABLE_SVE2)
diff --git a/src/cpu/kernels/softmax/generic/sve2/qasymm8_signed.cpp b/src/cpu/kernels/softmax/generic/sve2/qasymm8_signed.cpp
new file mode 100644
index 0000000..c2bdc50
--- /dev/null
+++ b/src/cpu/kernels/softmax/generic/sve2/qasymm8_signed.cpp
@@ -0,0 +1,39 @@
+/*
+ * Copyright (c) 2021-2022 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_COMPUTE_ENABLE_SVE2)
+#include "arm_compute/core/Helpers.h"
+#include "src/cpu/kernels/softmax/generic/sve2/impl.h"
+
+namespace arm_compute
+{
+namespace cpu
+{
+void sve2_qasymm8_signed_softmax(const ITensor *in, const ITensor *max, void *const tmp,
+                                 ITensor *out, const float beta, bool is_log, const Window &window)
+{
+    return sve2_softmax_logits_1d_quantized<qasymm8_signed_t>(in, max, tmp, out, beta, is_log, window);
+}
+}
+} // namespace arm_compute
+#endif //defined(ARM_COMPUTE_ENABLE_SVE2)