COMPMID-2805: Add QASYMM8_SIGNED support in NEGEMMLowpOutputStage

Add support from requantizing down from S32 to Int8 with fixed point
requantization. This involves the following:
- Compute fixed point multiplication between each entry of input by
  result_fixedpoint_multiplier
- Add bias to final result if bias tensor is not a nullptr
- Round to nearest division by a power-of-two using result_shift
- Add offset to each result
- Clamp the value between the specified min and max bounds
- Cast to int8 data type

Change-Id: I641b3fac0833c568d8565ccb859bbc561a24c17d
Signed-off-by: Georgios Pinitas <georgios.pinitas@arm.com>
Reviewed-on: https://review.mlplatform.org/c/2340
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>

1 files changed, 104 insertions, 6 deletions

diff --git a/tests/validation/fixtures/GEMMLowpFixture.h b/tests/validation/fixtures/GEMMLowpFixture.h
index 5d092ecac2..c17105edad 100644
--- a/tests/validation/fixtures/GEMMLowpFixture.h
+++ b/tests/validation/fixtures/GEMMLowpFixture.h
@@ -254,8 +254,8 @@ protected:
                                                                                        output_stage.gemmlowp_offset, output_stage.gemmlowp_multipliers, output_stage.gemmlowp_shifts, output_stage.gemmlowp_min_bound, output_stage.gemmlowp_max_bound);
                 break;
             case GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT:
-                return reference::gemmlowp_quantize_down_int32_to_uint8_scale_by_fixedpoint<int32_t>(output, bias,
-                                                                                                     output_stage.gemmlowp_multipliers, output_stage.gemmlowp_shifts, output_stage.gemmlowp_offset, output_stage.gemmlowp_min_bound, output_stage.gemmlowp_max_bound);
+                return reference::gemmlowp_quantize_down_scale_by_fixedpoint<int32_t, uint8_t>(output, bias,
+                                                                                               output_stage.gemmlowp_multipliers, output_stage.gemmlowp_shifts, output_stage.gemmlowp_offset, output_stage.gemmlowp_min_bound, output_stage.gemmlowp_max_bound);
                 break;
             default:
                 ARM_COMPUTE_ERROR("Not Supported!");
@@ -361,6 +361,101 @@ protected:
 };
 
 template <typename TensorType, typename AccessorType, typename FunctionType>
+class GEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointValidationFixture : public framework::Fixture
+{
+public:
+    template <typename...>
+    void setup(TensorShape shape, int32_t result_fixedpoint_multiplier, int32_t result_shift, int32_t result_offset_after_shift, int32_t min, int32_t max, bool add_bias)
+    {
+        _target    = compute_target(shape, result_fixedpoint_multiplier, result_shift, result_offset_after_shift, min, max, add_bias);
+        _reference = compute_reference(shape, result_fixedpoint_multiplier, result_shift, result_offset_after_shift, min, max, add_bias);
+    }
+
+protected:
+    template <typename U>
+    void fill(U &&tensor, int i)
+    {
+        std::uniform_int_distribution<> distribution(-6000, 6000);
+        library->fill(tensor, distribution, i);
+    }
+
+    TensorType compute_target(const TensorShape &shape, int32_t result_fixedpoint_multiplier, int32_t result_shift, int32_t result_offset_after_shift, int32_t min, int32_t max, bool add_bias)
+    {
+        TensorShape shape_bias(shape[0]);
+
+        // Create tensors
+        TensorType a = create_tensor<TensorType>(shape, DataType::S32, 1);
+        TensorType b = create_tensor<TensorType>(shape_bias, DataType::S32, 1);
+        TensorType c = create_tensor<TensorType>(shape, DataType::QASYMM8_SIGNED, 1);
+
+        // Create and configure function
+        FunctionType output_stage;
+        output_stage.configure(&a, add_bias ? &b : nullptr, &c, result_fixedpoint_multiplier, result_shift, result_offset_after_shift, min, max);
+
+        ARM_COMPUTE_EXPECT(a.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(c.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+        // Allocate tensors
+        a.allocator()->allocate();
+        c.allocator()->allocate();
+
+        ARM_COMPUTE_EXPECT(!a.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(!c.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+        // Fill tensor
+        fill(AccessorType(a), 0);
+
+        if(add_bias)
+        {
+            ARM_COMPUTE_EXPECT(b.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+            // Allocate bias tensor
+            b.allocator()->allocate();
+
+            ARM_COMPUTE_EXPECT(!b.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+            // Fill tensor
+            fill(AccessorType(b), 1);
+        }
+
+        // Compute GEMM function
+        output_stage.run();
+        return c;
+    }
+
+    SimpleTensor<int8_t> compute_reference(const TensorShape &shape, int32_t result_fixed_point_multiplier, int32_t result_shift, int32_t result_offset_after_shift, int32_t min, int32_t max,
+                                           bool add_bias)
+    {
+        // Create reference
+        TensorShape shape_bias(shape[0]);
+
+        SimpleTensor<int32_t> a{ shape, DataType::S32, 1 };
+        SimpleTensor<int32_t> b{ shape_bias, DataType::S32, 1 };
+
+        // Fill reference
+        fill(a, 0);
+
+        const std::vector<int32_t> result_fixed_point_multiplier_vec = { result_fixed_point_multiplier };
+        const std::vector<int32_t> result_shift_vec                  = { result_shift };
+
+        if(add_bias)
+        {
+            // Fill bias
+            fill(b, 1);
+
+            return reference::gemmlowp_quantize_down_scale_by_fixedpoint<int32_t, int8_t>(a, b, result_fixed_point_multiplier_vec, result_shift_vec, result_offset_after_shift, min, max);
+        }
+        else
+        {
+            return reference::gemmlowp_quantize_down_scale_by_fixedpoint<int32_t, int8_t>(a, result_fixed_point_multiplier_vec, result_shift_vec, result_offset_after_shift, min, max);
+        }
+    }
+
+    TensorType           _target{};
+    SimpleTensor<int8_t> _reference{};
+};
+
+template <typename TensorType, typename AccessorType, typename FunctionType>
 class GEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointValidationFixture : public framework::Fixture
 {
 public:
@@ -443,11 +538,11 @@ protected:
             // Fill bias
             fill(b, 1);
 
-            return reference::gemmlowp_quantize_down_int32_to_uint8_scale_by_fixedpoint<int32_t>(a, b, result_fixed_point_multiplier_vec, result_shift_vec, result_offset_after_shift, min, max);
+            return reference::gemmlowp_quantize_down_scale_by_fixedpoint<int32_t, uint8_t>(a, b, result_fixed_point_multiplier_vec, result_shift_vec, result_offset_after_shift, min, max);
         }
         else
         {
-            return reference::gemmlowp_quantize_down_int32_to_uint8_scale_by_fixedpoint<int32_t>(a, result_fixed_point_multiplier_vec, result_shift_vec, result_offset_after_shift, min, max);
+            return reference::gemmlowp_quantize_down_scale_by_fixedpoint<int32_t, uint8_t>(a, result_fixed_point_multiplier_vec, result_shift_vec, result_offset_after_shift, min, max);
         }
     }
 
@@ -530,16 +625,19 @@ protected:
         // Fill reference
         fill(a, 0);
 
+        const std::vector<int32_t> result_fixed_point_multiplier_vec = { result_fixed_point_multiplier };
+        const std::vector<int32_t> result_shift_vec                  = { result_shift };
+
         if(add_bias)
         {
             // Fill bias
             fill(b, 1);
 
-            return reference::gemmlowp_quantize_down_int32_to_int16_scale_by_fixedpoint<int32_t>(a, b, result_fixed_point_multiplier, result_shift, min, max);
+            return reference::gemmlowp_quantize_down_scale_by_fixedpoint<int32_t, int16_t>(a, b, result_fixed_point_multiplier_vec, result_shift_vec, 0, min, max);
         }
         else
         {
-            return reference::gemmlowp_quantize_down_int32_to_int16_scale_by_fixedpoint<int32_t>(a, result_fixed_point_multiplier, result_shift, min, max);
+            return reference::gemmlowp_quantize_down_scale_by_fixedpoint<int32_t, int16_t>(a, result_fixed_point_multiplier_vec, result_shift_vec, 0, min, max);
         }
     }