COMPMID-2775 [NE] add support for QASYMM8_SIGNED to SoftmaxLayer

Change-Id: Ic46d4143929c8c9b548355d85c78542faf25d612
Signed-off-by: Sang-Hoon Park <sang-hoon.park@arm.com>
Reviewed-on: https://review.mlplatform.org/c/2376
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>

5 files changed, 154 insertions, 37 deletions

diff --git a/arm_compute/core/NEON/NEColorConvertHelper.inl b/arm_compute/core/NEON/NEColorConvertHelper.inl
index 62c6eb5aea..7145d6f206 100644
--- a/arm_compute/core/NEON/NEColorConvertHelper.inl
+++ b/arm_compute/core/NEON/NEColorConvertHelper.inl
@@ -83,7 +83,7 @@ inline void rgb_to_u8_conversion(const uint8x16x3_t &in, uint8x16_t &out)
                                                       rgb2u8_red_coef, rgb2u8_green_coef, rgb2u8_blue_coef);
 
     //Conversion from 1(Greyscale) 4 floats to 1(Greyscale) 4 uint8s
-    arm_compute::convert_float32x4x4_to_unit8x16(out_float32, out);
+    arm_compute::convert_float32x4x4_to_uint8x16(out_float32, out);
 }
 
 inline void rgb_to_yuv_calculation(const float32x4_t &rvec, const float32x4_t &gvec, const float32x4_t &bvec,
@@ -214,12 +214,12 @@ inline void rgb_to_yuv_conversion(uint8x16x3_t &vec_top, uint8x16x3_t &vec_botto
                                fyvec_bottom.val[i], fuvec_bottom.val[i], fvvec_bottom.val[i]);
     }
 
-    arm_compute::convert_float32x4x4_to_unit8x16(fyvec_top, vec_top.val[0]);
-    arm_compute::convert_float32x4x4_to_unit8x16(fuvec_top, vec_top.val[1]);
-    arm_compute::convert_float32x4x4_to_unit8x16(fvvec_top, vec_top.val[2]);
-    arm_compute::convert_float32x4x4_to_unit8x16(fyvec_bottom, vec_bottom.val[0]);
-    arm_compute::convert_float32x4x4_to_unit8x16(fuvec_bottom, vec_bottom.val[1]);
-    arm_compute::convert_float32x4x4_to_unit8x16(fvvec_bottom, vec_bottom.val[2]);
+    arm_compute::convert_float32x4x4_to_uint8x16(fyvec_top, vec_top.val[0]);
+    arm_compute::convert_float32x4x4_to_uint8x16(fuvec_top, vec_top.val[1]);
+    arm_compute::convert_float32x4x4_to_uint8x16(fvvec_top, vec_top.val[2]);
+    arm_compute::convert_float32x4x4_to_uint8x16(fyvec_bottom, vec_bottom.val[0]);
+    arm_compute::convert_float32x4x4_to_uint8x16(fuvec_bottom, vec_bottom.val[1]);
+    arm_compute::convert_float32x4x4_to_uint8x16(fvvec_bottom, vec_bottom.val[2]);
 }
 
 inline void store_rgb_to_nv12(const uint8x16_t &rvec_top, const uint8x16_t &gvec_top, const uint8x16_t &bvec_top,
@@ -298,9 +298,9 @@ inline void store_rgb_to_yuv4(const uint8x16_t &rvec, const uint8x16_t &gvec, co
     }
 
     uint8x16_t yvec, uvec, vvec;
-    arm_compute::convert_float32x4x4_to_unit8x16(fyvec, yvec);
-    arm_compute::convert_float32x4x4_to_unit8x16(fuvec, uvec);
-    arm_compute::convert_float32x4x4_to_unit8x16(fvvec, vvec);
+    arm_compute::convert_float32x4x4_to_uint8x16(fyvec, yvec);
+    arm_compute::convert_float32x4x4_to_uint8x16(fuvec, uvec);
+    arm_compute::convert_float32x4x4_to_uint8x16(fvvec, vvec);
 
     vst1q_u8(out_y, yvec);
     vst1q_u8(out_u, uvec);
diff --git a/arm_compute/core/NEON/NEMath.h b/arm_compute/core/NEON/NEMath.h
index aa3054306c..54f8252250 100644
--- a/arm_compute/core/NEON/NEMath.h
+++ b/arm_compute/core/NEON/NEMath.h
@@ -165,6 +165,14 @@ int32_t rounding_divide_by_pow2(int32_t x, int exponent);
  */
 float32x4x4_t convert_uint8x16_to_float32x4x4(const uint8x16_t &in);
 
+/** Converts from int8x16 to float32x4x4_t
+ *
+ * @param[in] in Vector of int8 to be converted
+ *
+ * @return Converted vector of float
+ */
+float32x4x4_t convert_int8x16_to_float32x4x4(const int8x16_t &in);
+
 /** Converts from two float32x4x3_t to just one uint8x8x3_t
  *
  * @param[in]  in1 First input vector of float to be converted
@@ -178,7 +186,14 @@ void convert_float32x4x3_to_uint8x8x3(const float32x4x3_t &in1, const float32x4x
  * @param[in]  in  Vector of float to be converted
  * @param[out] out Converted vector of uint8 to store the result
  */
-void convert_float32x4x4_to_unit8x16(const float32x4x4_t &in, uint8x16_t &out);
+void convert_float32x4x4_to_uint8x16(const float32x4x4_t &in, uint8x16_t &out);
+
+/** Converts from float32x4x4_t to just one int8x16_t
+ *
+ * @param[in]  in  Vector of float to be converted
+ * @param[out] out Converted vector of uint8 to store the result
+ */
+void convert_float32x4x4_to_int8x16(const float32x4x4_t &in, int8x16_t &out);
 
 /** Calculate sine.
  *
diff --git a/arm_compute/core/NEON/NEMath.inl b/arm_compute/core/NEON/NEMath.inl
index 179f1b6299..5d8b82c281 100644
--- a/arm_compute/core/NEON/NEMath.inl
+++ b/arm_compute/core/NEON/NEMath.inl
@@ -331,6 +331,20 @@ inline float32x4x4_t convert_uint8x16_to_float32x4x4(const uint8x16_t &in)
     return out;
 }
 
+inline float32x4x4_t convert_int8x16_to_float32x4x4(const int8x16_t &in)
+{
+    float32x4x4_t out;
+
+    const auto tmp1 = vmovl_s8(vget_low_s8(in));
+    out.val[0]      = vcvtq_f32_s32(vmovl_s16(vget_low_s16(tmp1)));
+    out.val[1]      = vcvtq_f32_s32(vmovl_s16(vget_high_s16(tmp1)));
+
+    const auto tmp2 = vmovl_s8(vget_high_s8(in));
+    out.val[2]      = vcvtq_f32_s32(vmovl_s16(vget_low_s16(tmp2)));
+    out.val[3]      = vcvtq_f32_s32(vmovl_s16(vget_high_s16(tmp2)));
+    return out;
+}
+
 inline void convert_float32x4x3_to_uint8x8x3(const float32x4x3_t &in1, const float32x4x3_t &in2, uint8x8x3_t &out)
 {
     out.val[0] = vqmovn_u16(vcombine_u16(vqmovn_u32(vcvtq_u32_f32(in1.val[0])),
@@ -341,7 +355,7 @@ inline void convert_float32x4x3_to_uint8x8x3(const float32x4x3_t &in1, const flo
                                          vqmovn_u32(vcvtq_u32_f32(in2.val[2]))));
 }
 
-inline void convert_float32x4x4_to_unit8x16(const float32x4x4_t &in, uint8x16_t &out)
+inline void convert_float32x4x4_to_uint8x16(const float32x4x4_t &in, uint8x16_t &out)
 {
     const auto low = vcombine_u16(vqmovn_u32(vcvtq_u32_f32(in.val[0])),
                                   vqmovn_u32(vcvtq_u32_f32(in.val[1])));
@@ -350,6 +364,15 @@ inline void convert_float32x4x4_to_unit8x16(const float32x4x4_t &in, uint8x16_t
     out = vcombine_u8(vqmovn_u16(low), vqmovn_u16(high));
 }
 
+inline void convert_float32x4x4_to_int8x16(const float32x4x4_t &in, int8x16_t &out)
+{
+    const auto low = vcombine_s16(vqmovn_s32(vcvtq_s32_f32(in.val[0])),
+                                  vqmovn_s32(vcvtq_s32_f32(in.val[1])));
+    const auto high = vcombine_s16(vqmovn_s32(vcvtq_s32_f32(in.val[2])),
+                                   vqmovn_s32(vcvtq_s32_f32(in.val[3])));
+    out = vcombine_s8(vqmovn_s16(low), vqmovn_s16(high));
+}
+
 #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
 /** Exponent polynomial coefficients */
 /** Logarithm polynomial coefficients */
diff --git a/src/core/NEON/kernels/NESoftmaxLayerKernel.cpp b/src/core/NEON/kernels/NESoftmaxLayerKernel.cpp
index a3ecce3a1e..95cbdf582b 100644
--- a/src/core/NEON/kernels/NESoftmaxLayerKernel.cpp
+++ b/src/core/NEON/kernels/NESoftmaxLayerKernel.cpp
@@ -44,12 +44,46 @@
 
 namespace arm_compute
 {
+template <typename float_vec_type, typename int_vec_type>
+int_vec_type convert_float_to_int(const float_vec_type &in);
+
+template <typename float_vec_type, typename int_vec_type>
+float_vec_type convert_int_to_float(const int_vec_type &in);
+
+template <>
+uint8x16_t convert_float_to_int<float32x4x4_t, uint8x16_t>(const float32x4x4_t &in)
+{
+    uint8x16_t out;
+    convert_float32x4x4_to_uint8x16(in, out);
+    return out;
+}
+
+template <>
+int8x16_t convert_float_to_int<float32x4x4_t, int8x16_t>(const float32x4x4_t &in)
+{
+    int8x16_t out;
+    convert_float32x4x4_to_int8x16(in, out);
+    return out;
+}
+
+template <>
+float32x4x4_t convert_int_to_float<float32x4x4_t, uint8x16_t>(const uint8x16_t &in)
+{
+    return convert_uint8x16_to_float32x4x4(in);
+}
+
+template <>
+float32x4x4_t convert_int_to_float<float32x4x4_t, int8x16_t>(const int8x16_t &in)
+{
+    return convert_int8x16_to_float32x4x4(in);
+}
+
 namespace
 {
 Status validate_arguments_logits_1d_max(const ITensorInfo &input, const ITensorInfo &output)
 {
     ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(&input);
-    ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&input, 1, DataType::QASYMM8, DataType::F16, DataType::F32);
+    ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&input, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::F16, DataType::F32);
 
     // Validate in case of configured output
     if(output.total_size() != 0)
@@ -156,6 +190,9 @@ void NELogits1DMaxKernel::configure(const ITensor *input, ITensor *output)
         case DataType::QASYMM8:
             _func = &logits_1d_max<qasymm8_t>;
             break;
+        case DataType::QASYMM8_SIGNED:
+            _func = &logits_1d_max<qasymm8_signed_t>;
+            break;
 #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
         case DataType::F16:
             _func = &logits_1d_max<float16_t>;
@@ -203,12 +240,12 @@ void NELogits1DMaxKernel::run(const Window &window, const ThreadInfo &info)
 namespace
 {
 Status validate_arguments_logits_softmax(const ITensorInfo &input, const ITensorInfo &max,
-                                         const ITensorInfo &output, const float beta, const ITensorInfo &tmp)
+                                         const ITensorInfo &output, const float beta, const ITensorInfo &tmp, bool is_log)
 {
     ARM_COMPUTE_UNUSED(beta);
     // Check input
     ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(&input);
-    ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&input, 1, DataType::QASYMM8, DataType::F16, DataType::F32);
+    ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&input, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::F16, DataType::F32);
 
     const bool is_quantized_asymmetric = is_data_type_quantized_asymmetric(input.data_type());
 
@@ -220,7 +257,7 @@ Status validate_arguments_logits_softmax(const ITensorInfo &input, const ITensor
     // Check output if configured
     if(output.total_size() != 0)
     {
-        const QuantizationInfo output_quantization = is_quantized_asymmetric ? QuantizationInfo(1.f / 256.f, 0) : output.quantization_info();
+        const QuantizationInfo output_quantization = is_quantized_asymmetric ? arm_compute::get_softmax_output_quantization_info(input.data_type(), is_log) : output.quantization_info();
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(&input, &output);
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(&input, &output);
         ARM_COMPUTE_RETURN_ERROR_ON(output.quantization_info() != output_quantization);
@@ -240,12 +277,12 @@ Status validate_arguments_logits_softmax(const ITensorInfo &input, const ITensor
 }
 
 std::pair<Status, Window> validate_and_configure_window_logits_softmax(ITensorInfo &input, ITensorInfo &max,
-                                                                       ITensorInfo &output, ITensorInfo &tmp)
+                                                                       ITensorInfo &output, ITensorInfo &tmp, bool is_log)
 {
     const bool is_quantized_asymmetric = is_data_type_quantized_asymmetric(input.data_type());
 
     // Output auto initialization if not yet initialized
-    const QuantizationInfo output_quantization = is_quantized_asymmetric ? QuantizationInfo(1.f / 256.f, 0) : output.quantization_info();
+    const QuantizationInfo output_quantization = is_quantized_asymmetric ? arm_compute::get_softmax_output_quantization_info(input.data_type(), is_log) : output.quantization_info();
     auto_init_if_empty(output, TensorInfo(input).set_quantization_info(output_quantization).reset_padding());
 
     // Tmp auto initialization if not yet initialized
@@ -269,9 +306,13 @@ std::pair<Status, Window> validate_and_configure_window_logits_softmax(ITensorIn
     return std::make_pair(err, win);
 }
 
-template <bool is_log>
+template <typename T, bool is_log>
 void logits_1d_softmax_qasymm8(const ITensor &in, const ITensor &max, void *const tmp, ITensor &out, const float beta, 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();
 
@@ -286,8 +327,8 @@ void logits_1d_softmax_qasymm8(const ITensor &in, const ITensor &max, void *cons
     execute_window_loop(window, [&](const Coordinates &)
     {
         /* Get pointers */
-        const auto in_ptr  = reinterpret_cast<const qasymm8_t *>(in_it.ptr()) + start_x;
-        const auto out_ptr = reinterpret_cast<qasymm8_t *>(out_it.ptr()) + start_x;
+        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{};
@@ -296,8 +337,8 @@ void logits_1d_softmax_qasymm8(const ITensor &in, const ITensor &max, void *cons
         /* Compute exponentials and sum */
         {
             /* Get max value */
-            const auto max_val = *reinterpret_cast<const qasymm8_t *>(max_it.ptr());
-            const auto vec_max = vdupq_n_u8(max_val);
+            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 =
@@ -313,8 +354,8 @@ void logits_1d_softmax_qasymm8(const ITensor &in, const ITensor &max, void *cons
             for(; x <= (input_width - vec_size); x += vec_size)
             {
                 auto vec_elements     = wrapper::vloadq(in_ptr + x);
-                vec_elements          = vsubq_u8(vec_max, vec_elements);
-                auto vec_elements_flt = convert_uint8x16_to_float32x4x4(vec_elements);
+                vec_elements          = wrapper::vsub(vec_max, vec_elements);
+                auto vec_elements_flt = convert_int_to_float<float32x4x4_t>(vec_elements);
 
                 if(is_log)
                 {
@@ -374,12 +415,14 @@ void logits_1d_softmax_qasymm8(const ITensor &in, const ITensor &max, void *cons
 
         /* 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);
-                uint8x16_t    normalized_value{};
+                int_vec_type  normalized_value{};
                 if(is_log)
                 {
                     const float32x4x4_t sub =
@@ -389,31 +432,41 @@ void logits_1d_softmax_qasymm8(const ITensor &in, const ITensor &max, void *cons
                         vsubq_f32(vec_in.val[2], vdupq_n_f32(sum)),
                         vsubq_f32(vec_in.val[3], vdupq_n_f32(sum)),
                     };
-                    convert_float32x4x4_to_unit8x16(sub, normalized_value);
+                    normalized_value = convert_float_to_int<float32x4x4_t, int_vec_type>(sub);
                 }
                 else
                 {
-                    const float32x4x4_t mul =
+                    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)),
                     };
-                    convert_float32x4x4_to_unit8x16(mul, normalized_value);
+
+                    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);
                 }
-                vst1q_u8(out_ptr + x, normalized_value);
+                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<qasymm8_t>(tmp_ptr[x] - sum);
+                    out_ptr[x] = utils::cast::saturate_cast<T>(tmp_ptr[x] - sum);
                 }
                 else
                 {
-                    out_ptr[x] = utils::cast::saturate_cast<qasymm8_t>(tmp_ptr[x] * sum_inversed);
+                    out_ptr[x] = utils::cast::saturate_cast<T>((tmp_ptr[x] * sum_inversed) - (is_qasymm8_signed ? 128.f : 0));
                 }
             }
         }
@@ -556,15 +609,18 @@ void NELogits1DSoftmaxKernel<IS_LOG>::configure(const ITensor *input, const ITen
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, max, output, tmp);
     ARM_COMPUTE_ERROR_ON_NULLPTR(input->info(), max->info(), output->info(), tmp->info());
     // Perform validation step
-    ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_logits_softmax(*input->info(), *max->info(), *output->info(), beta, *tmp->info()));
+    ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_logits_softmax(*input->info(), *max->info(), *output->info(), beta, *tmp->info(), IS_LOG));
     // Configure kernel window
-    auto win_config = validate_and_configure_window_logits_softmax(*input->info(), *max->info(), *output->info(), *tmp->info());
+    auto win_config = validate_and_configure_window_logits_softmax(*input->info(), *max->info(), *output->info(), *tmp->info(), IS_LOG);
     ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
 
     switch(input->info()->data_type())
     {
         case DataType::QASYMM8:
-            _func = &logits_1d_softmax_qasymm8<IS_LOG>;
+            _func = &logits_1d_softmax_qasymm8<qasymm8_t, IS_LOG>;
+            break;
+        case DataType::QASYMM8_SIGNED:
+            _func = &logits_1d_softmax_qasymm8<qasymm8_signed_t, IS_LOG>;
             break;
 #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
         case DataType::F16:
@@ -594,8 +650,8 @@ Status NELogits1DSoftmaxKernel<IS_LOG>::validate(const ITensorInfo *input, const
 {
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, max, output, tmp);
 
-    ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_logits_softmax(*input, *max, *output, beta, *tmp));
-    ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window_logits_softmax(*input->clone(), *max->clone(), *output->clone(), *tmp->clone()).first);
+    ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_logits_softmax(*input, *max, *output, beta, *tmp, IS_LOG));
+    ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window_logits_softmax(*input->clone(), *max->clone(), *output->clone(), *tmp->clone(), IS_LOG).first);
 
     return Status{};
 }
diff --git a/tests/validation/NEON/SoftmaxLayer.cpp b/tests/validation/NEON/SoftmaxLayer.cpp
index 7f8c622ef9..cbf7729bc3 100644
--- a/tests/validation/NEON/SoftmaxLayer.cpp
+++ b/tests/validation/NEON/SoftmaxLayer.cpp
@@ -48,6 +48,7 @@ RelativeTolerance<half>            tolerance_f16(half(0.2));
 
 /** Tolerance for quantized operations */
 constexpr AbsoluteTolerance<uint8_t> tolerance_qasymm8(1);
+constexpr AbsoluteTolerance<int8_t>  tolerance_qasymm8_signed(1);
 
 /** CNN data types */
 const auto CNNDataTypes = framework::dataset::make("DataType",
@@ -241,6 +242,28 @@ FIXTURE_DATA_TEST_CASE(RunLarge, NESoftmaxLayerQuantizedFixture<uint8_t>, framew
     validate(Accessor(_target), _reference, tolerance_qasymm8);
 }
 TEST_SUITE_END() //QASYMM8
+
+TEST_SUITE(QASYMM8_SIGNED)
+FIXTURE_DATA_TEST_CASE(RunSmall2D, NESoftmaxLayerQuantizedFixture<int8_t>, framework::DatasetMode::ALL, combine(combine(combine(datasets::SoftmaxLayerSmallShapes(),
+                                                                                                                        framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)),
+                                                                                                                        combine(framework::dataset::make("QuantizationInfo", { QuantizationInfo(0.5f, -10) }),
+                                                                                                                                framework::dataset::make("Beta", { 1.0f, 2.f }))),
+                                                                                                                framework::dataset::make("Axis", { 1 })))
+{
+    // Validate output
+    validate(Accessor(_target), _reference, tolerance_qasymm8_signed);
+}
+FIXTURE_DATA_TEST_CASE(RunSmall4D, NESoftmaxLayerQuantizedFixture<int8_t>, framework::DatasetMode::ALL, combine(combine(combine(datasets::Small4DShapes(),
+                                                                                                                        framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)),
+                                                                                                                        combine(framework::dataset::make("QuantizationInfo", { QuantizationInfo(0.5f, -10) }),
+                                                                                                                                framework::dataset::make("Beta", { 1.0f, 2.f }))),
+                                                                                                                framework::dataset::make("Axis", { 1, 2, 3 })))
+{
+    // Validate output
+    validate(Accessor(_target), _reference, tolerance_qasymm8_signed);
+}
+TEST_SUITE_END() //QASYMM8_SIGNED
+
 TEST_SUITE_END() //Quantized
 
 TEST_SUITE_END() //SoftmaxLayer