COMPMID-1401 Implement NEFullyConnectedLayer for QASYMM8

Change-Id: I0404df6d369855e2f458f2db8f26e81c80a1ee87
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/140148
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Tested-by: Jenkins <bsgcomp@arm.com>

1 files changed, 18 insertions, 36 deletions

diff --git a/tests/validation/fixtures/FullyConnectedLayerFixture.h b/tests/validation/fixtures/FullyConnectedLayerFixture.h
index 18321480f8..49c3be0c2e 100644
--- a/tests/validation/fixtures/FullyConnectedLayerFixture.h
+++ b/tests/validation/fixtures/FullyConnectedLayerFixture.h
@@ -45,7 +45,7 @@ namespace test
 {
 namespace validation
 {
-template <typename TensorType, typename AccessorType, typename FunctionType, typename T, bool run_interleave>
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
 class FullyConnectedLayerValidationGenericFixture : public framework::Fixture
 {
 public:
@@ -103,8 +103,8 @@ protected:
         // -----------+-----------+---------------------------
         //  transpose |           | ***
         // -----------+-----------+---------------------------
-        // !transpose | transpose | transpose &
-        //            |           | transpose1xW (if required)
+        // !transpose | transpose | transpose
+        //            |           |
         //
         // ***: That combination is invalid. But we can ignore the transpose flag and handle all !reshape the same
         if(!reshape_weights || !transpose_weights)
@@ -112,16 +112,6 @@ protected:
             const size_t shape_x = reshaped_weights_shape.x();
             reshaped_weights_shape.set(0, reshaped_weights_shape.y());
             reshaped_weights_shape.set(1, shape_x);
-
-            // Weights have to be passed reshaped
-            // Transpose 1xW for batched version
-            if(!reshape_weights && output_shape.y() > 1 && run_interleave)
-            {
-                const int   transpose_width = 16 / data_size_from_type(_data_type);
-                const float shape_x         = reshaped_weights_shape.x();
-                reshaped_weights_shape.set(0, reshaped_weights_shape.y() * transpose_width);
-                reshaped_weights_shape.set(1, static_cast<unsigned int>(std::ceil(shape_x / transpose_width)));
-            }
         }
 
         // Create tensors
@@ -170,14 +160,6 @@ protected:
             // Transpose elementwise
             tmp = transpose(tmp);
 
-            // Reshape weights for batched runs
-            if(!reshape_weights && output_shape.y() > 1 && run_interleave)
-            {
-                // Transpose with interleave
-                const int interleave_size = 16 / tmp.element_size();
-                tmp                       = transpose(tmp, interleave_size);
-            }
-
             AccessorType weights_accessor(weights);
 
             for(int i = 0; i < tmp.num_elements(); ++i)
@@ -222,43 +204,43 @@ protected:
     QuantizationInfo _quantization_info{};
 };
 
-template <typename TensorType, typename AccessorType, typename FunctionType, typename T, bool run_interleave>
-class FullyConnectedLayerValidationFixture : public FullyConnectedLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T, run_interleave>
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class FullyConnectedLayerValidationFixture : public FullyConnectedLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>
 {
 public:
     template <typename...>
     void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, bool transpose_weights, bool reshape_weights, DataType data_type)
     {
-        FullyConnectedLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T, run_interleave>::setup(input_shape, weights_shape, bias_shape, output_shape, transpose_weights,
-                                                                                                                      reshape_weights, data_type,
-                                                                                                                      QuantizationInfo());
+        FullyConnectedLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, transpose_weights,
+                                                                                                      reshape_weights, data_type,
+                                                                                                      QuantizationInfo());
     }
 };
 
-template <typename TensorType, typename AccessorType, typename FunctionType, typename T, bool run_interleave>
-class FullyConnectedLayerValidationFixedPointFixture : public FullyConnectedLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T, run_interleave>
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class FullyConnectedLayerValidationFixedPointFixture : public FullyConnectedLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>
 {
 public:
     template <typename...>
     void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, bool transpose_weights, bool reshape_weights, DataType data_type)
     {
-        FullyConnectedLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T, run_interleave>::setup(input_shape, weights_shape, bias_shape, output_shape, transpose_weights,
-                                                                                                                      reshape_weights, data_type,
-                                                                                                                      QuantizationInfo());
+        FullyConnectedLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, transpose_weights,
+                                                                                                      reshape_weights, data_type,
+                                                                                                      QuantizationInfo());
     }
 };
 
-template <typename TensorType, typename AccessorType, typename FunctionType, typename T, bool run_interleave>
-class FullyConnectedLayerValidationQuantizedFixture : public FullyConnectedLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T, run_interleave>
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class FullyConnectedLayerValidationQuantizedFixture : public FullyConnectedLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>
 {
 public:
     template <typename...>
     void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, bool transpose_weights, bool reshape_weights, DataType data_type,
                QuantizationInfo quantization_info)
     {
-        FullyConnectedLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T, run_interleave>::setup(input_shape, weights_shape, bias_shape, output_shape, transpose_weights,
-                                                                                                                      reshape_weights, data_type,
-                                                                                                                      quantization_info);
+        FullyConnectedLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, transpose_weights,
+                                                                                                      reshape_weights, data_type,
+                                                                                                      quantization_info);
     }
 };
 } // namespace validation