Optimize Quantized/Integer Bilinear Scale for Neon™

This patch introduces several performance optimizations regarding the Bilinear Scale operator with REPLICATE Border mode. Changes apply only to NHWC.

This patch
   - Reduces the memory footprint by disabling precomputation of indices and weights when they're not used
   - Rewrites the kernels for QASYMM8/QASYMM8_SIGNED/U8(Uint8)
   - Adds S8(Int8) Bilinear Scale for Border mode REPLICATE
   - Removes Bilinear Scale SVE kernels for Quantized and Integer types and adjust the heuristics to choose the Neon™ implementation
   - Adds new test cases where the input and output of the Bilinear Scale operator have different quantization scale and offset

Resolves: COMPMID-5453, COMPMID-5454

Change-Id: I3d251e76e0c6978fd5a0a1795ec62ab536bec93c
Signed-off-by: Gunes Bayir <gunes.bayir@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8250
Reviewed-by: SiCong Li <sicong.li@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>

1 files changed, 41 insertions, 22 deletions

diff --git a/tests/validation/fixtures/ScaleFixture.h b/tests/validation/fixtures/ScaleFixture.h
index c0b44bcb5f..72feb62016 100644
--- a/tests/validation/fixtures/ScaleFixture.h
+++ b/tests/validation/fixtures/ScaleFixture.h
@@ -24,12 +24,6 @@
 #ifndef ARM_COMPUTE_TEST_SCALE_FIXTURE
 #define ARM_COMPUTE_TEST_SCALE_FIXTURE
 
-#include "arm_compute/core/TensorShape.h"
-#include "arm_compute/core/Types.h"
-#include "tests/AssetsLibrary.h"
-#include "tests/Globals.h"
-#include "tests/IAccessor.h"
-#include "tests/framework/Asserts.h"
 #include "tests/framework/Fixture.h"
 #include "tests/validation/reference/Permute.h"
 #include "tests/validation/reference/Scale.h"
@@ -46,16 +40,17 @@ class ScaleValidationGenericFixture : public framework::Fixture
 public:
     template <typename...>
     void setup(TensorShape shape, DataType data_type, QuantizationInfo quantization_info, DataLayout data_layout, InterpolationPolicy policy, BorderMode border_mode, SamplingPolicy sampling_policy,
-               bool align_corners, bool mixed_layout)
+               bool align_corners, bool mixed_layout, QuantizationInfo output_quantization_info)
     {
-        _shape             = shape;
-        _policy            = policy;
-        _border_mode       = border_mode;
-        _sampling_policy   = sampling_policy;
-        _data_type         = data_type;
-        _quantization_info = quantization_info;
-        _align_corners     = align_corners;
-        _mixed_layout      = mixed_layout;
+        _shape                    = shape;
+        _policy                   = policy;
+        _border_mode              = border_mode;
+        _sampling_policy          = sampling_policy;
+        _data_type                = data_type;
+        _input_quantization_info  = quantization_info;
+        _output_quantization_info = output_quantization_info;
+        _align_corners            = align_corners;
+        _mixed_layout             = mixed_layout;
 
         generate_scale(shape);
 
@@ -144,7 +139,7 @@ protected:
         }
 
         // Create tensors
-        TensorType src = create_tensor<TensorType>(shape, _data_type, 1, _quantization_info, data_layout);
+        TensorType src = create_tensor<TensorType>(shape, _data_type, 1, _input_quantization_info, data_layout);
 
         const int idx_width  = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH);
         const int idx_height = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT);
@@ -152,7 +147,7 @@ protected:
         TensorShape shape_scaled(shape);
         shape_scaled.set(idx_width, shape[idx_width] * _scale_x, /* apply_dim_correction = */ false);
         shape_scaled.set(idx_height, shape[idx_height] * _scale_y, /* apply_dim_correction = */ false);
-        TensorType dst = create_tensor<TensorType>(shape_scaled, _data_type, 1, _quantization_info, data_layout);
+        TensorType dst = create_tensor<TensorType>(shape_scaled, _data_type, 1, _output_quantization_info, data_layout);
 
         // Create and configure function
         FunctionType scale;
@@ -188,12 +183,12 @@ protected:
     SimpleTensor<T> compute_reference(const TensorShape &shape)
     {
         // Create reference
-        SimpleTensor<T> src{ shape, _data_type, 1, _quantization_info };
+        SimpleTensor<T> src{ shape, _data_type, 1, _input_quantization_info };
 
         // Fill reference
         fill(src);
 
-        return reference::scale<T>(src, _scale_x, _scale_y, _policy, _border_mode, _constant_border_value, _sampling_policy, /* ceil_policy_scale */ false, _align_corners);
+        return reference::scale<T>(src, _scale_x, _scale_y, _policy, _border_mode, _constant_border_value, _sampling_policy, /* ceil_policy_scale */ false, _align_corners, _output_quantization_info);
     }
 
     TensorType          _target{};
@@ -204,7 +199,8 @@ protected:
     T                   _constant_border_value{};
     SamplingPolicy      _sampling_policy{};
     DataType            _data_type{};
-    QuantizationInfo    _quantization_info{};
+    QuantizationInfo    _input_quantization_info{};
+    QuantizationInfo    _output_quantization_info{};
     bool                _align_corners{ false };
     bool                _mixed_layout{ false };
     float               _scale_x{ 1.f };
@@ -227,7 +223,29 @@ public:
                                                                                         border_mode,
                                                                                         sampling_policy,
                                                                                         align_corners,
-                                                                                        mixed_layout);
+                                                                                        mixed_layout,
+                                                                                        quantization_info);
+    }
+};
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T, bool mixed_layout = false>
+class ScaleValidationDifferentOutputQuantizedFixture : public ScaleValidationGenericFixture<TensorType, AccessorType, FunctionType, T>
+{
+public:
+    template <typename...>
+    void setup(TensorShape shape, DataType data_type, QuantizationInfo input_quantization_info, QuantizationInfo output_quantization_info, DataLayout data_layout, InterpolationPolicy policy,
+               BorderMode border_mode, SamplingPolicy sampling_policy,
+               bool align_corners)
+    {
+        ScaleValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape,
+                                                                                        data_type,
+                                                                                        input_quantization_info,
+                                                                                        data_layout,
+                                                                                        policy,
+                                                                                        border_mode,
+                                                                                        sampling_policy,
+                                                                                        align_corners,
+                                                                                        mixed_layout,
+                                                                                        output_quantization_info);
     }
 };
 template <typename TensorType, typename AccessorType, typename FunctionType, typename T, bool mixed_layout = false>
@@ -245,7 +263,8 @@ public:
                                                                                         border_mode,
                                                                                         sampling_policy,
                                                                                         align_corners,
-                                                                                        mixed_layout);
+                                                                                        mixed_layout,
+                                                                                        QuantizationInfo());
     }
 };
 } // namespace validation