COMPMID-428: Port NESoftmaxLayer to 16-bit fixed point.

Change-Id: I65122950bab9124b9758c27096c0f458b77aeabb
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/79365
Reviewed-by: Moritz Pflanzer <moritz.pflanzer@arm.com>
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>
Reviewed-by: Steven Niu <steven.niu@arm.com>

1 files changed, 216 insertions, 89 deletions

diff --git a/src/core/NEON/kernels/NESoftmaxLayerKernel.cpp b/src/core/NEON/kernels/NESoftmaxLayerKernel.cpp
index 854fd84845..fe62d7b575 100644
--- a/src/core/NEON/kernels/NESoftmaxLayerKernel.cpp
+++ b/src/core/NEON/kernels/NESoftmaxLayerKernel.cpp
@@ -43,7 +43,7 @@ using namespace arm_compute;
 
 namespace
 {
-void logits_1d_max_f32(const ITensor *in, ITensor *out, const Window &window)
+void logits_1d_max_qs8(const ITensor *in, ITensor *out, const Window &window)
 {
     Window in_slice = window.first_slice_window_1D();
 
@@ -56,25 +56,57 @@ void logits_1d_max_f32(const ITensor *in, ITensor *out, const Window &window)
         Iterator input(in, in_slice);
         Iterator output(out, max_slice);
 
-        float32x4_t vec_max = vdupq_n_f32(-FLT_MAX);
+        qint8x16_t vec_max = vdupq_n_s8(std::numeric_limits<qint8_t>::lowest());
 
         execute_window_loop(in_slice, [&](const Coordinates & id)
         {
-            const auto        in_ptr        = reinterpret_cast<const float *>(input.ptr());
-            const float32x4_t current_value = vld1q_f32(in_ptr);
-            vec_max                         = vmaxq_f32(vec_max, current_value);
+            const auto       in_ptr        = reinterpret_cast<const qint8_t *>(input.ptr());
+            const qint8x16_t current_value = vld1q_qs8(in_ptr);
+            vec_max                        = vmaxq_qs8(vec_max, current_value);
         },
         input);
 
-        float32x2_t carry_max = vpmax_f32(vget_high_f32(vec_max), vget_low_f32(vec_max));
-        carry_max             = vpmax_f32(carry_max, carry_max);
+        qint8x8_t carry_max = vpmax_qs8(vget_high_s8(vec_max), vget_low_s8(vec_max));
+        carry_max           = vpmax_qs8(carry_max, carry_max);
+        carry_max           = vpmax_qs8(carry_max, carry_max);
+        carry_max           = vpmax_qs8(carry_max, carry_max);
 
-        *(reinterpret_cast<float *>(output.ptr())) = vget_lane_f32(carry_max, 0);
+        *(reinterpret_cast<qint8_t *>(output.ptr())) = vget_lane_s8(carry_max, 0);
     }
     while(window.slide_window_slice_1D(in_slice) && window.slide_window_slice_1D(max_slice));
 }
+void logits_1d_max_qs16(const ITensor *in, ITensor *out, const Window &window)
+{
+    Window in_slice = window.first_slice_window_1D();
 
-void logits_1d_max_qs8(const ITensor *in, ITensor *out, const Window &window)
+    Window window_max(window);
+    window_max.set(Window::DimX, Window::Dimension(0, 0, 0));
+    Window max_slice = window_max.first_slice_window_1D();
+
+    do
+    {
+        Iterator input(in, in_slice);
+        Iterator output(out, max_slice);
+
+        qint16x8_t vec_max = vdupq_n_qs16(std::numeric_limits<qint16_t>::lowest());
+
+        execute_window_loop(in_slice, [&](const Coordinates & id)
+        {
+            const auto       in_ptr        = reinterpret_cast<const qint16_t *>(input.ptr());
+            const qint16x8_t current_value = vld1q_qs16(in_ptr);
+            vec_max                        = vmaxq_qs16(vec_max, current_value);
+        },
+        input);
+
+        qint16x4_t carry_max = vpmax_qs16(vget_high_qs16(vec_max), vget_low_qs16(vec_max));
+        carry_max            = vpmax_qs16(carry_max, carry_max);
+        carry_max            = vpmax_qs16(carry_max, carry_max);
+
+        *(reinterpret_cast<qint16_t *>(output.ptr())) = vget_lane_s16(carry_max, 0);
+    }
+    while(window.slide_window_slice_1D(in_slice) && window.slide_window_slice_1D(max_slice));
+}
+void logits_1d_max_f32(const ITensor *in, ITensor *out, const Window &window)
 {
     Window in_slice = window.first_slice_window_1D();
 
@@ -87,22 +119,20 @@ void logits_1d_max_qs8(const ITensor *in, ITensor *out, const Window &window)
         Iterator input(in, in_slice);
         Iterator output(out, max_slice);
 
-        qint8x16_t vec_max = vdupq_n_s8(-1);
+        float32x4_t vec_max = vdupq_n_f32(-FLT_MAX);
 
         execute_window_loop(in_slice, [&](const Coordinates & id)
         {
-            const auto       in_ptr        = reinterpret_cast<const qint8_t *>(input.ptr());
-            const qint8x16_t current_value = vld1q_qs8(in_ptr);
-            vec_max                        = vmaxq_qs8(vec_max, current_value);
+            const auto        in_ptr        = reinterpret_cast<const float *>(input.ptr());
+            const float32x4_t current_value = vld1q_f32(in_ptr);
+            vec_max                         = vmaxq_f32(vec_max, current_value);
         },
         input);
 
-        qint8x8_t carry_max = vpmax_qs8(vget_high_s8(vec_max), vget_low_s8(vec_max));
-        carry_max           = vpmax_qs8(carry_max, carry_max);
-        carry_max           = vpmax_qs8(carry_max, carry_max);
-        carry_max           = vpmax_qs8(carry_max, carry_max);
+        float32x2_t carry_max = vpmax_f32(vget_high_f32(vec_max), vget_low_f32(vec_max));
+        carry_max             = vpmax_f32(carry_max, carry_max);
 
-        *(reinterpret_cast<int8_t *>(output.ptr())) = vget_lane_s8(carry_max, 0);
+        *(reinterpret_cast<float *>(output.ptr())) = vget_lane_f32(carry_max, 0);
     }
     while(window.slide_window_slice_1D(in_slice) && window.slide_window_slice_1D(max_slice));
 }
@@ -120,7 +150,7 @@ BorderSize NELogits1DMaxKernel::border_size() const
 
 void NELogits1DMaxKernel::configure(const ITensor *input, ITensor *output)
 {
-    ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QS8, DataType::F32);
+    ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QS8, DataType::QS16, DataType::F32);
     ARM_COMPUTE_ERROR_ON_NULLPTR(output);
 
     // Softmax across the x dimension
@@ -135,17 +165,18 @@ void NELogits1DMaxKernel::configure(const ITensor *input, ITensor *output)
     ARM_COMPUTE_ERROR_ON_MISMATCHING_DIMENSIONS(output->info()->tensor_shape(), output_shape);
 
     const int    input_width                       = input->info()->valid_region().shape.x();
-    unsigned int num_elems_processed_per_iteration = 0;
+    unsigned int num_elems_processed_per_iteration = 16 / data_size_from_type(input->info()->data_type());
 
     switch(input->info()->data_type())
     {
         case DataType::QS8:
-            _func                             = &logits_1d_max_qs8;
-            num_elems_processed_per_iteration = 16;
+            _func = &logits_1d_max_qs8;
+            break;
+        case DataType::QS16:
+            _func = &logits_1d_max_qs16;
             break;
         case DataType::F32:
-            num_elems_processed_per_iteration = 4;
-            _func                             = &logits_1d_max_f32;
+            _func = &logits_1d_max_f32;
             break;
         default:
             ARM_COMPUTE_ERROR("Unsupported data type.");
@@ -180,7 +211,7 @@ void NELogits1DMaxKernel::run(const Window &window)
 
 namespace
 {
-void logits_1d_shift_exp_sum_f32(const ITensor *in, const ITensor *max, ITensor *out, ITensor *sum, const Window &window)
+void logits_1d_shift_exp_sum_qs8(const ITensor *in, const ITensor *max, ITensor *out, ITensor *sum, const Window &window)
 {
     Window window_max(window);
     window_max.set(Window::DimX, Window::Dimension(0, 0, 0));
@@ -188,9 +219,10 @@ void logits_1d_shift_exp_sum_f32(const ITensor *in, const ITensor *max, ITensor
     Window max_slice = window_max.first_slice_window_1D();
     Window in_slice  = window.first_slice_window_1D();
 
-    constexpr int step        = 4;
-    const int     long_steps  = in->info()->valid_region().shape.x() / step;
-    const int     small_steps = in->info()->valid_region().shape.x() % step;
+    constexpr int step                 = 8;
+    const int     long_steps           = in->info()->valid_region().shape.x() / step;
+    const int     small_steps          = in->info()->valid_region().shape.x() % step;
+    const int     fixed_point_position = in->info()->fixed_point_position();
 
     do
     {
@@ -200,48 +232,48 @@ void logits_1d_shift_exp_sum_f32(const ITensor *in, const ITensor *max, ITensor
         Iterator _sum(sum, max_slice);
 
         // Get pointers
-        auto in_ptr  = reinterpret_cast<const float *>(input.ptr());
-        auto exp_ptr = reinterpret_cast<float *>(exp.ptr());
+        auto in_ptr  = reinterpret_cast<const qint8_t *>(input.ptr());
+        auto exp_ptr = reinterpret_cast<qint8_t *>(exp.ptr());
 
         // Init sum to zero
-        float32x4_t vec_sum_value = vdupq_n_f32(0.0f);
+        qint16x8_t vec_sum_value = vdupq_n_qs16(0);
 
         // Get max value
-        const auto        max_ptr = reinterpret_cast<const float *>(_max.ptr());
-        const float32x4_t vec_max = vdupq_n_f32(*max_ptr);
+        const auto      max_ptr = reinterpret_cast<const qint8_t *>(_max.ptr());
+        const qint8x8_t vec_max = vdup_n_qs8(*max_ptr);
 
         // Run neon loop
         for(int i = 0; i < long_steps; ++i)
         {
-            float32x4_t vec_elements = vld1q_f32(in_ptr);
-            vec_elements             = vsubq_f32(vec_elements, vec_max);
-            vec_elements             = vexpq_f32(vec_elements);
+            qint8x8_t vec_elements = vld1_qs8(in_ptr);
+            vec_elements           = vqsub_qs8(vec_elements, vec_max);
+            vec_elements           = vqexp_qs8(vec_elements, fixed_point_position);
 
-            vst1q_f32(exp_ptr, vec_elements);
-            vec_sum_value = vaddq_f32(vec_elements, vec_sum_value);
+            vst1_qs8(exp_ptr, vec_elements);
+            vec_sum_value = vqaddq_qs16(vec_sum_value, vmovl_s8(vec_elements));
 
             in_ptr += step;
             exp_ptr += step;
         }
-
         // Reduce sum
-        float32x2_t carry_addition = vpadd_f32(vget_high_f32(vec_sum_value), vget_low_f32(vec_sum_value));
-        carry_addition             = vpadd_f32(carry_addition, carry_addition);
-        float sum                  = vget_lane_f32(carry_addition, 0);
+        const qint16x4_t sum_red = vqadd_qs16(vget_low_s16(vec_sum_value), vget_high_s16(vec_sum_value));
+        const qint16_t   sum0    = sqadd_qs16(vget_lane_s16(sum_red, 0), vget_lane_s16(sum_red, 1));
+        const qint16_t   sum1    = sqadd_qs16(vget_lane_s16(sum_red, 2), vget_lane_s16(sum_red, 3));
+        qint16_t         sum     = sqadd_qs16(sum0, sum1);
 
         // Run remaining elements
         for(int i = 0; i < small_steps; ++i)
         {
-            float element = std::exp(in_ptr[i] - *max_ptr);
-            exp_ptr[i]    = element;
-            sum += element;
+            qint8_t element = sqexp_qs8(sqsub_qs8(in_ptr[i], *max_ptr), fixed_point_position);
+            exp_ptr[i]      = element;
+            sum             = sqadd_qs16(sum, element);
         }
 
-        *(reinterpret_cast<float *>(_sum.ptr())) = sum;
+        *(reinterpret_cast<qint8_t *>(_sum.ptr())) = sqmovn_qs16(sum);
     }
     while(window.slide_window_slice_1D(in_slice) && window.slide_window_slice_1D(max_slice));
 }
-void logits_1d_shift_exp_sum_qs8(const ITensor *in, const ITensor *max, ITensor *out, ITensor *sum, const Window &window)
+void logits_1d_shift_exp_sum_qs16(const ITensor *in, const ITensor *max, ITensor *out, ITensor *sum, const Window &window)
 {
     Window window_max(window);
     window_max.set(Window::DimX, Window::Dimension(0, 0, 0));
@@ -249,7 +281,7 @@ void logits_1d_shift_exp_sum_qs8(const ITensor *in, const ITensor *max, ITensor
     Window max_slice = window_max.first_slice_window_1D();
     Window in_slice  = window.first_slice_window_1D();
 
-    constexpr int step                 = 8;
+    constexpr int step                 = 4;
     const int     long_steps           = in->info()->valid_region().shape.x() / step;
     const int     small_steps          = in->info()->valid_region().shape.x() % step;
     const int     fixed_point_position = in->info()->fixed_point_position();
@@ -262,44 +294,103 @@ void logits_1d_shift_exp_sum_qs8(const ITensor *in, const ITensor *max, ITensor
         Iterator _sum(sum, max_slice);
 
         // Get pointers
-        auto in_ptr  = reinterpret_cast<const qint8_t *>(input.ptr());
-        auto exp_ptr = reinterpret_cast<qint8_t *>(exp.ptr());
+        auto in_ptr  = reinterpret_cast<const qint16_t *>(input.ptr());
+        auto exp_ptr = reinterpret_cast<qint16_t *>(exp.ptr());
 
         // Init sum to zero
-        qint16x8_t vec_sum_value = vdupq_n_qs16(0);
+        qint32x4_t vec_sum_value = vdupq_n_qs32(0);
 
         // Get max value
-        const auto      max_ptr = reinterpret_cast<const qint8_t *>(_max.ptr());
-        const qint8x8_t vec_max = vdup_n_qs8(*max_ptr);
+        const auto       max_ptr = reinterpret_cast<const qint16_t *>(_max.ptr());
+        const qint16x4_t vec_max = vdup_n_qs16(*max_ptr);
 
         // Run neon loop
         for(int i = 0; i < long_steps; ++i)
         {
-            qint8x8_t vec_elements = vld1_qs8(in_ptr);
-            vec_elements           = vqsub_qs8(vec_elements, vec_max);
-            vec_elements           = vqexp_qs8(vec_elements, fixed_point_position);
+            qint16x4_t vec_elements = vld1_qs16(in_ptr);
+            vec_elements            = vqsub_qs16(vec_elements, vec_max);
+            vec_elements            = vqexp_qs16(vec_elements, fixed_point_position);
 
-            vst1_qs8(exp_ptr, vec_elements);
-            vec_sum_value = vqaddq_qs16(vec_sum_value, vmovl_s8(vec_elements));
+            vst1_qs16(exp_ptr, vec_elements);
+            vec_sum_value = vqaddq_qs32(vec_sum_value, vmovl_s16(vec_elements));
 
             in_ptr += step;
             exp_ptr += step;
         }
         // Reduce sum
-        const qint16x4_t sum_red = vqadd_qs16(vget_low_s16(vec_sum_value), vget_high_s16(vec_sum_value));
-        const qint16_t   sum0    = sqadd_qs16(vget_lane_s16(sum_red, 0), vget_lane_s16(sum_red, 1));
-        const qint16_t   sum1    = sqadd_qs16(vget_lane_s16(sum_red, 2), vget_lane_s16(sum_red, 3));
-        qint16_t         sum     = sqadd_qs16(sum0, sum1);
+        qint32x2_t carry_addition = vqadd_qs32(vget_high_s32(vec_sum_value), vget_low_s32(vec_sum_value));
+        qint32_t   sum            = vget_lane_s32(carry_addition, 0) + vget_lane_s32(carry_addition, 1);
 
         // Run remaining elements
         for(int i = 0; i < small_steps; ++i)
         {
-            qint8_t element = sqexp_qs8(sqsub_qs8(in_ptr[i], *max_ptr), fixed_point_position);
-            exp_ptr[i]      = element;
-            sum             = sqadd_qs16(sum, element);
+            qint16_t element = sqexp_qs16(sqsub_qs16(in_ptr[i], *max_ptr), fixed_point_position);
+            exp_ptr[i]       = element;
+            sum              = sqadd_qs32(sum, element);
         }
 
-        *(reinterpret_cast<qint8_t *>(_sum.ptr())) = sqmovn_qs16(sum);
+        *(reinterpret_cast<qint16_t *>(_sum.ptr())) = sqmovn_qs32(sum);
+    }
+    while(window.slide_window_slice_1D(in_slice) && window.slide_window_slice_1D(max_slice));
+}
+void logits_1d_shift_exp_sum_f32(const ITensor *in, const ITensor *max, ITensor *out, ITensor *sum, const Window &window)
+{
+    Window window_max(window);
+    window_max.set(Window::DimX, Window::Dimension(0, 0, 0));
+
+    Window max_slice = window_max.first_slice_window_1D();
+    Window in_slice  = window.first_slice_window_1D();
+
+    constexpr int step        = 4;
+    const int     long_steps  = in->info()->valid_region().shape.x() / step;
+    const int     small_steps = in->info()->valid_region().shape.x() % step;
+
+    do
+    {
+        Iterator input(in, in_slice);
+        Iterator exp(out, in_slice);
+        Iterator _max(max, max_slice);
+        Iterator _sum(sum, max_slice);
+
+        // Get pointers
+        auto in_ptr  = reinterpret_cast<const float *>(input.ptr());
+        auto exp_ptr = reinterpret_cast<float *>(exp.ptr());
+
+        // Init sum to zero
+        float32x4_t vec_sum_value = vdupq_n_f32(0.0f);
+
+        // Get max value
+        const auto        max_ptr = reinterpret_cast<const float *>(_max.ptr());
+        const float32x4_t vec_max = vdupq_n_f32(*max_ptr);
+
+        // Run neon loop
+        for(int i = 0; i < long_steps; ++i)
+        {
+            float32x4_t vec_elements = vld1q_f32(in_ptr);
+            vec_elements             = vsubq_f32(vec_elements, vec_max);
+            vec_elements             = vexpq_f32(vec_elements);
+
+            vst1q_f32(exp_ptr, vec_elements);
+            vec_sum_value = vaddq_f32(vec_elements, vec_sum_value);
+
+            in_ptr += step;
+            exp_ptr += step;
+        }
+
+        // Reduce sum
+        float32x2_t carry_addition = vpadd_f32(vget_high_f32(vec_sum_value), vget_low_f32(vec_sum_value));
+        carry_addition             = vpadd_f32(carry_addition, carry_addition);
+        float sum                  = vget_lane_f32(carry_addition, 0);
+
+        // Run remaining elements
+        for(int i = 0; i < small_steps; ++i)
+        {
+            float element = std::exp(in_ptr[i] - *max_ptr);
+            exp_ptr[i]    = element;
+            sum += element;
+        }
+
+        *(reinterpret_cast<float *>(_sum.ptr())) = sum;
     }
     while(window.slide_window_slice_1D(in_slice) && window.slide_window_slice_1D(max_slice));
 }
@@ -312,7 +403,7 @@ NELogits1DShiftExpSumKernel::NELogits1DShiftExpSumKernel()
 
 void NELogits1DShiftExpSumKernel::configure(const ITensor *input, const ITensor *max, ITensor *output, ITensor *sum)
 {
-    ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QS8, DataType::F32);
+    ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QS8, DataType::QS16, DataType::F32);
     ARM_COMPUTE_ERROR_ON_NULLPTR(max, sum, output);
 
     // Output auto initialization if not yet initialized
@@ -331,6 +422,9 @@ void NELogits1DShiftExpSumKernel::configure(const ITensor *input, const ITensor
         case DataType::QS8:
             _func = &logits_1d_shift_exp_sum_qs8;
             break;
+        case DataType::QS16:
+            _func = &logits_1d_shift_exp_sum_qs16;
+            break;
         case DataType::F32:
             _func = &logits_1d_shift_exp_sum_f32;
             break;
@@ -369,37 +463,39 @@ void NELogits1DShiftExpSumKernel::run(const Window &window)
 
 namespace
 {
-void logits_1d_norm_f32(const ITensor *in, const ITensor *sum, ITensor *out, const Window &window)
+void logits_1d_norm_qs8(const ITensor *in, const ITensor *sum, ITensor *out, const Window &window)
 {
     Window window_sum(window);
     window_sum.set(Window::DimX, Window::Dimension(0, 0, 0));
     Window sum_slice = window_sum.first_slice_window_1D();
     Window in_slice  = window.first_slice_window_1D();
 
+    const int fixed_point_position = in->info()->fixed_point_position();
+
     do
     {
         Iterator input(in, in_slice);
         Iterator _sum(sum, sum_slice);
         Iterator output(out, in_slice);
 
-        const float       sum_value        = *reinterpret_cast<const float *>(_sum.ptr());
-        const float32x4_t vec_sum_inversed = vdupq_n_f32(1.0f / sum_value);
+        const int8_t     sum_value        = *reinterpret_cast<const qint8_t *>(_sum.ptr());
+        const qint8x16_t vec_sum_inversed = vqrecipq_qs8(vdupq_n_qs8(sum_value), fixed_point_position);
 
         execute_window_loop(in_slice, [&](const Coordinates & id)
         {
-            const auto in_ptr  = reinterpret_cast<const float *>(input.ptr());
-            const auto out_ptr = reinterpret_cast<float *>(output.ptr());
+            const auto in_ptr  = reinterpret_cast<const qint8_t *>(input.ptr());
+            const auto out_ptr = reinterpret_cast<qint8_t *>(output.ptr());
 
-            const float32x4_t vec_in           = vld1q_f32(in_ptr);
-            const float32x4_t normalized_value = vmulq_f32(vec_in, vec_sum_inversed);
+            const qint8x16_t vec_in           = vld1q_qs8(in_ptr);
+            const qint8x16_t normalized_value = vqmulq_qs8(vec_in, vec_sum_inversed, fixed_point_position);
 
-            vst1q_f32(out_ptr, normalized_value);
+            vst1q_qs8(out_ptr, normalized_value);
         },
         input, output);
     }
     while(window.slide_window_slice_1D(in_slice) && window.slide_window_slice_1D(sum_slice));
 }
-void logits_1d_norm_qs8(const ITensor *in, const ITensor *sum, ITensor *out, const Window &window)
+void logits_1d_norm_qs16(const ITensor *in, const ITensor *sum, ITensor *out, const Window &window)
 {
     Window window_sum(window);
     window_sum.set(Window::DimX, Window::Dimension(0, 0, 0));
@@ -414,18 +510,48 @@ void logits_1d_norm_qs8(const ITensor *in, const ITensor *sum, ITensor *out, con
         Iterator _sum(sum, sum_slice);
         Iterator output(out, in_slice);
 
-        const int8_t     sum_value        = *reinterpret_cast<const qint8_t *>(_sum.ptr());
-        const qint8x16_t vec_sum_inversed = vqrecipq_qs8(vdupq_n_qs8(sum_value), fixed_point_position);
+        const int16_t    sum_value        = *reinterpret_cast<const qint16_t *>(_sum.ptr());
+        const qint16x8_t vec_sum_inversed = vqrecipq_qs16(vdupq_n_qs16(sum_value), fixed_point_position);
 
         execute_window_loop(in_slice, [&](const Coordinates & id)
         {
-            const auto in_ptr  = reinterpret_cast<const qint8_t *>(input.ptr());
-            const auto out_ptr = reinterpret_cast<qint8_t *>(output.ptr());
+            const auto in_ptr  = reinterpret_cast<const qint16_t *>(input.ptr());
+            const auto out_ptr = reinterpret_cast<qint16_t *>(output.ptr());
 
-            const qint8x16_t vec_in           = vld1q_qs8(in_ptr);
-            const qint8x16_t normalized_value = vqmulq_qs8(vec_in, vec_sum_inversed, fixed_point_position);
+            const qint16x8_t vec_in           = vld1q_qs16(in_ptr);
+            const qint16x8_t normalized_value = vqmulq_qs16(vec_in, vec_sum_inversed, fixed_point_position);
 
-            vst1q_qs8(out_ptr, normalized_value);
+            vst1q_qs16(out_ptr, normalized_value);
+        },
+        input, output);
+    }
+    while(window.slide_window_slice_1D(in_slice) && window.slide_window_slice_1D(sum_slice));
+}
+void logits_1d_norm_f32(const ITensor *in, const ITensor *sum, ITensor *out, const Window &window)
+{
+    Window window_sum(window);
+    window_sum.set(Window::DimX, Window::Dimension(0, 0, 0));
+    Window sum_slice = window_sum.first_slice_window_1D();
+    Window in_slice  = window.first_slice_window_1D();
+
+    do
+    {
+        Iterator input(in, in_slice);
+        Iterator _sum(sum, sum_slice);
+        Iterator output(out, in_slice);
+
+        const float       sum_value        = *reinterpret_cast<const float *>(_sum.ptr());
+        const float32x4_t vec_sum_inversed = vdupq_n_f32(1.0f / sum_value);
+
+        execute_window_loop(in_slice, [&](const Coordinates & id)
+        {
+            const auto in_ptr  = reinterpret_cast<const float *>(input.ptr());
+            const auto out_ptr = reinterpret_cast<float *>(output.ptr());
+
+            const float32x4_t vec_in           = vld1q_f32(in_ptr);
+            const float32x4_t normalized_value = vmulq_f32(vec_in, vec_sum_inversed);
+
+            vst1q_f32(out_ptr, normalized_value);
         },
         input, output);
     }
@@ -440,7 +566,7 @@ NELogits1DNormKernel::NELogits1DNormKernel()
 
 void NELogits1DNormKernel::configure(const ITensor *input, const ITensor *sum, ITensor *output)
 {
-    ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32, DataType::QS8);
+    ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QS8, DataType::QS16, DataType::F32);
     ARM_COMPUTE_ERROR_ON_NULLPTR(sum, output);
 
     // Output auto initialization if not yet initialized
@@ -455,17 +581,18 @@ void NELogits1DNormKernel::configure(const ITensor *input, const ITensor *sum, I
     _output = output;
 
     // Configure kernel window
-    unsigned int num_elems_processed_per_iteration = 0;
+    unsigned int num_elems_processed_per_iteration = 16 / data_size_from_type(input->info()->data_type());
 
     switch(input->info()->data_type())
     {
         case DataType::QS8:
-            _func                             = &logits_1d_norm_qs8;
-            num_elems_processed_per_iteration = 16;
+            _func = &logits_1d_norm_qs8;
+            break;
+        case DataType::QS16:
+            _func = &logits_1d_norm_qs16;
             break;
         case DataType::F32:
-            num_elems_processed_per_iteration = 4;
-            _func                             = &logits_1d_norm_f32;
+            _func = &logits_1d_norm_f32;
             break;
         default:
             ARM_COMPUTE_ERROR("Unsupported data type.");