Retain weights in ClGemm when reconfiguring the operator with retention

- Reduces the size of the WeightRetentions tests
- Ensure the weights are retained the only the Src,Dst are updated

Resolves: COMPMID-4775

Signed-off-by: Georgios Pinitas <georgios.pinitas@arm.com>
Change-Id: If12daa4bd4bf89ec28faa743fb7291895cbe7b7c
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/6121
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>

1 files changed, 10 insertions, 10 deletions

diff --git a/tests/validation/fixtures/UNIT/WeightsRetentionFixture.h b/tests/validation/fixtures/UNIT/WeightsRetentionFixture.h
index af9f776ebc..f5e6071340 100644
--- a/tests/validation/fixtures/UNIT/WeightsRetentionFixture.h
+++ b/tests/validation/fixtures/UNIT/WeightsRetentionFixture.h
@@ -74,10 +74,10 @@ protected:
     TensorType compute_target()
     {
         // Create tensors
-        TensorType w1  = create_tensor<TensorType>(TensorShape(180000U, 150U), DataType::F32, 1);
-        TensorType b1  = create_tensor<TensorType>(TensorShape(150U), DataType::F32, 1);
-        TensorType src = create_tensor<TensorType>(TensorShape(1U, 150U, 1200U, _max_batches), DataType::F32, 1);
-        TensorType dst = create_tensor<TensorType>(TensorShape(150U, _max_batches), DataType::F32, 1);
+        TensorType w1  = create_tensor<TensorType>(TensorShape(6000U, 15U), DataType::F32, 1);
+        TensorType b1  = create_tensor<TensorType>(TensorShape(15U), DataType::F32, 1);
+        TensorType src = create_tensor<TensorType>(TensorShape(1U, 15U, 400U, _max_batches), DataType::F32, 1);
+        TensorType dst = create_tensor<TensorType>(TensorShape(15U, _max_batches), DataType::F32, 1);
 
         // Create and configure function
         FullyConnectedFunction fc_layer_1;
@@ -105,9 +105,9 @@ protected:
         int  diff            = _max_batches - _cur_batches;
         auto new_src_padding = PaddingSize(src_padding.top, src_padding.right, src_padding.bottom + diff, src_padding.left);
         auto new_dst_padding = PaddingSize(dst_padding.top, dst_padding.right, dst_padding.bottom + diff, dst_padding.left);
-        src.allocator()->info().set_tensor_shape(TensorShape(1U, 150U, 1200U, _cur_batches)).set_is_resizable(true).extend_padding(new_src_padding);
+        src.allocator()->info().set_tensor_shape(TensorShape(1U, 15U, 400U, _cur_batches)).set_is_resizable(true).extend_padding(new_src_padding);
         src.allocator()->info().set_is_resizable(false);
-        dst.allocator()->info().set_tensor_shape(TensorShape(150U, _cur_batches)).set_is_resizable(true).extend_padding(new_dst_padding);
+        dst.allocator()->info().set_tensor_shape(TensorShape(15U, _cur_batches)).set_is_resizable(true).extend_padding(new_dst_padding);
         dst.allocator()->info().set_is_resizable(false);
 
         // Configure FC info
@@ -129,16 +129,16 @@ protected:
     SimpleTensor<T> compute_reference()
     {
         // Create reference
-        SimpleTensor<T> w1{ TensorShape(180000U, 150U), DataType::F32 };
-        SimpleTensor<T> b1{ TensorShape(150U), DataType::F32 };
-        SimpleTensor<T> src{ TensorShape(1U, 150U, 1200U, _cur_batches), DataType::F32 };
+        SimpleTensor<T> w1{ TensorShape(6000U, 15U), DataType::F32 };
+        SimpleTensor<T> b1{ TensorShape(15U), DataType::F32 };
+        SimpleTensor<T> src{ TensorShape(1U, 15U, 400U, _cur_batches), DataType::F32 };
 
         // Fill reference
         fill(src, 5);
         fill(w1, 1);
         fill(b1, 2);
 
-        return reference::fully_connected_layer(src, w1, b1, TensorShape(150U, _cur_batches));
+        return reference::fully_connected_layer(src, w1, b1, TensorShape(15U, _cur_batches));
     }
 
 protected: