COMPMID-2205: CL runtime context.

CL Interfaces implemented.
Concrete classes implemented.
One test (ActivationLayer) ported to the new interface.

Change-Id: I283808bec36ccfc2f13fe048c45cbbee698ce525
Signed-off-by: Pablo Tello <pablo.tello@arm.com>
Reviewed-on: https://review.mlplatform.org/c/1998
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
diff --git a/tests/Utils.h b/tests/Utils.h
index ea70fff..3bb6060 100644
--- a/tests/Utils.h
+++ b/tests/Utils.h
@@ -520,14 +520,15 @@
  * @param[in] num_channels      (Optional) Number of channels.
  * @param[in] quantization_info (Optional) Quantization info for asymmetric quantized types.
  * @param[in] data_layout       (Optional) Data layout. Default is NCHW.
+ * @param[in] ctx               (Optional) Pointer to the runtime context.
  *
  * @return Initialized tensor of given type.
  */
 template <typename T>
 inline T create_tensor(const TensorShape &shape, DataType data_type, int num_channels = 1,
-                       QuantizationInfo quantization_info = QuantizationInfo(), DataLayout data_layout = DataLayout::NCHW)
+                       QuantizationInfo quantization_info = QuantizationInfo(), DataLayout data_layout = DataLayout::NCHW, IRuntimeContext *ctx = nullptr)
 {
-    T          tensor;
+    T          tensor(ctx);
     TensorInfo info(shape, num_channels, data_type);
     info.set_quantization_info(quantization_info);
     info.set_data_layout(data_layout);
@@ -540,15 +541,16 @@
  *
  * @param[in] shape  Tensor shape.
  * @param[in] format Format type.
+ * @param[in] ctx    (Optional) Pointer to the runtime context.
  *
  * @return Initialized tensor of given type.
  */
 template <typename T>
-inline T create_tensor(const TensorShape &shape, Format format)
+inline T create_tensor(const TensorShape &shape, Format format, IRuntimeContext *ctx = nullptr)
 {
     TensorInfo info(shape, format);
 
-    T tensor;
+    T tensor(ctx);
     tensor.allocator()->init(info);
 
     return tensor;