Integrate CLTensorArgument

- Add CLTensorArgument to query the components and storages as OpenCL
variables (or by values when possible)
- Add caching mechanism in CLTensorArgument to keep track of the components and storages used
- Add unit tests

Resolves COMPMID-5787

Signed-off-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Signed-off-by: Viet-Hoa Do <viet-hoa.do@arm.com>
Change-Id: Ib39e1f77b097e5b907a296fe6b0d41bb4bcd4ffc
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9908
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Reviewed-by: Jakub Sujak <jakub.sujak@arm.com>

18 files changed, 1396 insertions, 196 deletions

diff --git a/compute_kernel_writer/CMakeLists.txt b/compute_kernel_writer/CMakeLists.txt
index 9f372df585..674bc53309 100644
--- a/compute_kernel_writer/CMakeLists.txt
+++ b/compute_kernel_writer/CMakeLists.txt
@@ -131,6 +131,7 @@ target_sources(ckw PRIVATE
 if(CKW_ENABLE_OPENCL)
     target_sources(ckw PRIVATE
         src/cl/CLConstantTile.cpp
+        src/cl/CLTensorArgument.cpp
         src/cl/CLHelpers.cpp
         src/cl/CLTile.cpp
         src/cl/ICLTile.cpp
@@ -150,11 +151,6 @@ if(CKW_BUILD_TESTING)
     add_executable(ckw_validation
         validation/Validation.cpp
     )
-    if(CKW_ENABLE_OPENCL)
-        target_sources(ckw_validation PRIVATE
-            validation/tests/CLConstantTileTest.hpp
-            validation/tests/CLTileTest.hpp)
-    endif()
 
     target_link_libraries(ckw_validation PRIVATE ckw)
     target_include_directories(ckw_validation
diff --git a/compute_kernel_writer/include/ckw/Error.h b/compute_kernel_writer/include/ckw/Error.h
index 100bdc48fe..eaf3f10c05 100644
--- a/compute_kernel_writer/include/ckw/Error.h
+++ b/compute_kernel_writer/include/ckw/Error.h
@@ -87,7 +87,7 @@ inline void ignore_unused(T &&...)
 
 #ifdef COMPUTE_KERNEL_WRITER_ASSERTS_ENABLED
 
-/** If the condition is not met, throw an std::runtime_error with the specified message.
+/** If the condition is not met, throw an std::runtime_error with the specified message if assertion is enabled.
  *
  * @param[in] cond The condition that is expected to be true.
  * @param[in] msg  The error message when the condition is not met.
@@ -101,19 +101,24 @@ inline void ignore_unused(T &&...)
         }                         \
     } while(false)
 
-/** If the condition is not met, throw an std::runtime_error.
- *
- * @param[in] cond The condition that is expected to be true.
- */
-#define CKW_ASSERT(cond) CKW_ASSERT_MSG(cond, #cond)
-
 #else // COMPUTE_KERNEL_WRITER_ASSERTS_ENABLED
 
 #define CKW_ASSERT_MSG(cond, msg)
-#define CKW_ASSERT(cond)
 
 #endif // COMPUTE_KERNEL_WRITER_ASSERTS_ENABLED
 
+/** If the condition is not met, throw an std::runtime_error if assertion is enabled.
+ *
+ * @param[in] cond The condition that is expected to be true.
+ */
+#define CKW_ASSERT(cond) CKW_ASSERT_MSG(cond, #cond)
+
+/** Throw an std::runtime_error with the specified message if assertion is enabled.
+ *
+ * @param[in] msg  The error message when the condition is not met.
+ */
+#define CKW_ASSERT_FAILED_MSG(msg) CKW_ASSERT_MSG(false, msg)
+
 } // namespace ckw
 
 #endif // CKW_INCLUDE_CKW_ERROR_H
diff --git a/compute_kernel_writer/include/ckw/TensorInfo.h b/compute_kernel_writer/include/ckw/TensorInfo.h
index 63d9f412b6..87cf7c1426 100644
--- a/compute_kernel_writer/include/ckw/TensorInfo.h
+++ b/compute_kernel_writer/include/ckw/TensorInfo.h
@@ -26,85 +26,27 @@
 #define COMPUTE_KERNEL_WRITER_INCLUDE_CKW_TENSORINFO_H
 
 #include "ckw/types/DataType.h"
-
+#include "ckw/types/TensorDataLayout.h"
 #include <array>
 #include <cstdint>
 
 namespace ckw
 {
-/** Compute Kernel Writer tensor data layout (or memory format) */
-enum class TensorDataLayout
-{
-    Unknown,
-    Nhwc,
-    Ndhwc
-};
-
-/** Compute Kernel Writer tensor data layout component */
-enum class TensorDataLayoutComponent
-{
-    Unknown,
-    N,
-    D,
-    H,
-    W,
-    C,
-};
-
-/** Compute Kernel Writer tensor component bitmask. The bitmask can be used to retrieve
- *  the info from @ref TensorComponent.
- */
-enum class TensorComponentBitmask : uint32_t
-{
-    OffsetFirstElement = 0x01000000, // For example, OffsetFirstElement in @ref TensorComponent
-    Stride             = 0x02000000, // For example, stride0 in @ref TensorComponent
-    Dimension          = 0x04000000, // For example, Dim0 in @ref TensorComponent
-    FoldedDimensions   = 0x08000000, // For example, Dim0xDim1 in @ref TensorComponent
-};
-
-/** Compute Kernel Writer tensor component. The tensor components are used to access specific backend-agnostic tensor arguments,
- *  such as the tensor dimensions and tensor strides.
- *  The data type is represented as an integer. The value of the integer value
- *  is assigned to retrieve the information through the @ref TensorComponentBitmask.
- */
-enum class TensorComponent : uint32_t
-{
-    Unknown            = 0x00000000,
-    OffsetFirstElement = 0x01000000,
-    Stride0            = 0x02000001,
-    Stride1            = 0x02000010,
-    Stride2            = 0x02000100,
-    Stride3            = 0x02001000,
-    Stride4            = 0x02010000,
-    Dim0               = 0x04000001,
-    Dim1               = 0x04000010,
-    Dim2               = 0x04000100,
-    Dim3               = 0x04001000,
-    Dim4               = 0x04010000,
-    Dim1xDim2          = 0x08000110,
-    Dim2xDim3          = 0x08001100,
-    Dim1xDim2xDim3     = 0x08001110
-};
-
-/** Compute Kernel Writer tensor storage. The tensor storage represents the type of tensor memory object.
- */
-enum class TensorStorage : uint32_t
-{
-    Unknown            = 0x00000000,
-    BufferUint8Ptr     = 0x01000000,
-    Texture2dReadOnly  = 0x02000001,
-    Texture2dWriteOnly = 0x02000010,
-};
 
 /** Compute Kernel Writer tensor shape
- *  Negative dimensions can be interpreted as dynamic dimensions by the Compute Kernel Writer
+ *  The value -1 for the tensor dimension is reserved to dynamic dimensions.
  */
 using TensorShape = std::array<int32_t, 5>;
 
+/** Tensor dimension value reserved to dynamic dimensions */
+constexpr int32_t kDynamicTensorDimensionValue = -1;
+
 /** Compute Kernel Writer tensor info */
 class TensorInfo
 {
 public:
+    /** Default constructor */
+    TensorInfo() = default;
     /** Constructor
      *
      * @param[in] dt    Tensor data type
diff --git a/compute_kernel_writer/include/ckw/types/TensorComponentType.h b/compute_kernel_writer/include/ckw/types/TensorComponentType.h
new file mode 100644
index 0000000000..7a5031d8c0
--- /dev/null
+++ b/compute_kernel_writer/include/ckw/types/TensorComponentType.h
@@ -0,0 +1,61 @@
+/*
+ * Copyright (c) 2023 Arm Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+
+#ifndef CKW_INCLUDE_CKW_TYPES_TENSORCOMPONENTTYPE_H
+#define CKW_INCLUDE_CKW_TYPES_TENSORCOMPONENTTYPE_H
+
+#include <cstdint>
+
+namespace ckw
+{
+
+/** Compute Kernel Writer tensor component.
+ *
+ * The tensor components are used to access specific backend-agnostic tensor arguments,
+ * such as the tensor dimensions and tensor strides.
+ * The tensor component is represented as an unsigned integer. The value of the integer value
+ * is assigned to retrieve the information through the @ref TensorComponentBitmask.
+ */
+enum class TensorComponentType : uint32_t
+{
+    Unknown            = 0x00000000,
+    OffsetFirstElement = 0x01000000,
+    Stride0            = 0x02000001,
+    Stride1            = 0x02000002,
+    Stride2            = 0x02000003,
+    Stride3            = 0x02000004,
+    Stride4            = 0x02000005,
+    Dim0               = 0x04000001,
+    Dim1               = 0x04000002,
+    Dim2               = 0x04000003,
+    Dim3               = 0x04000004,
+    Dim4               = 0x04000005,
+    Dim1xDim2          = 0x08000032,
+    Dim2xDim3          = 0x08000043,
+    Dim1xDim2xDim3     = 0x08000432
+};
+
+} // namespace ckw
+
+#endif // CKW_INCLUDE_CKW_TYPES_TENSORCOMPONENTTYPE_H
diff --git a/compute_kernel_writer/include/ckw/types/TensorDataLayout.h b/compute_kernel_writer/include/ckw/types/TensorDataLayout.h
new file mode 100644
index 0000000000..532b299910
--- /dev/null
+++ b/compute_kernel_writer/include/ckw/types/TensorDataLayout.h
@@ -0,0 +1,52 @@
+/*
+ * Copyright (c) 2023 Arm Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+
+#ifndef CKW_INCLUDE_CKW_TYPES_TENSORDATALAYOUT_H
+#define CKW_INCLUDE_CKW_TYPES_TENSORDATALAYOUT_H
+
+namespace ckw
+{
+
+/** Compute Kernel Writer tensor data layout (or memory format) */
+enum class TensorDataLayout
+{
+    Unknown,
+    Nhwc,
+    Ndhwc
+};
+
+/** Compute Kernel Writer tensor data layout component */
+enum class TensorDataLayoutComponent
+{
+    Unknown,
+    N,
+    D,
+    H,
+    W,
+    C,
+};
+
+} // namespace ckw
+
+#endif // CKW_INCLUDE_CKW_TYPES_TENSORDATALAYOUT_H
diff --git a/compute_kernel_writer/include/ckw/types/TensorStorageType.h b/compute_kernel_writer/include/ckw/types/TensorStorageType.h
new file mode 100644
index 0000000000..5a2f17d520
--- /dev/null
+++ b/compute_kernel_writer/include/ckw/types/TensorStorageType.h
@@ -0,0 +1,46 @@
+/*
+ * Copyright (c) 2023 Arm Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+
+#ifndef CKW_INCLUDE_CKW_TYPES_TENSORSTORAGETYPE_H
+#define CKW_INCLUDE_CKW_TYPES_TENSORSTORAGETYPE_H
+
+#include <cstdint>
+
+namespace ckw
+{
+
+/** Compute Kernel Writer tensor storage.
+ *  The tensor storage represents the type of tensor memory object.
+ */
+enum class TensorStorageType : uint32_t
+{
+    Unknown            = 0x00000000,
+    BufferUint8Ptr     = 0x01000000,
+    Texture2dReadOnly  = 0x02000001,
+    Texture2dWriteOnly = 0x02000010,
+};
+
+} // namespace ckw
+
+#endif // CKW_INCLUDE_CKW_TYPES_TENSORSTORAGETYPE_H
diff --git a/compute_kernel_writer/src/ITensorArgument.h b/compute_kernel_writer/src/ITensorArgument.h
new file mode 100644
index 0000000000..40ad69fdc0
--- /dev/null
+++ b/compute_kernel_writer/src/ITensorArgument.h
@@ -0,0 +1,121 @@
+/*
+ * Copyright (c) 2023 Arm Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+
+#ifndef CKW_SRC_ITENSORARGUMENT_H
+#define CKW_SRC_ITENSORARGUMENT_H
+
+#include "ckw/TensorInfo.h"
+#include "ckw/types/TensorComponentType.h"
+#include "ckw/types/TensorStorageType.h"
+#include "src/ITile.h"
+
+#include <string>
+#include <vector>
+
+namespace ckw
+{
+/** Tensor storage variable */
+struct TensorStorageVariable
+{
+    std::string val{ "" };  /** Tensor storage as a string */
+    std::string type{ "" }; /** Tensor storage type as a string */
+};
+
+/** Tensor argument base class.
+ *  A tensor is a multidimensional array used to store data. To access an element (or multiple elements) from a tensor,
+ *  the following information are required:
+ *  -# The data memory object. For example, the pointer to the array
+ *  -# The tensor components, such as the size of each tensor dimension, or the number of elements in bytes contained in each dimension (also known as the "stride")
+ */
+class ITensorArgument
+{
+public:
+    virtual ~ITensorArgument() = default;
+    /** Method to get the name of the tensor argument.
+     *
+     * @return the name of the tensor argument
+     */
+    std::string name() const
+    {
+        return _basename;
+    }
+    /** Method to get the tensor info
+     *
+     * @return the @ref TensorInfo
+     */
+    TensorInfo info() const
+    {
+        return _info;
+    }
+
+protected:
+    TensorInfo  _info{};         // Tensor info
+    std::string _basename{ "" }; // Tensor name
+};
+
+/** Tensor component argument base class */
+class ITensorComponentArgument
+{
+public:
+    virtual ~ITensorComponentArgument() = default;
+    /** Method to get the tensor component variable as a string
+     *
+     * @param[in] x The tensor component to query
+     *
+     * @return the tensor component variable as a @ref TileVariable
+     */
+    virtual TileVariable component(TensorComponentType x) = 0;
+    /** Method to get all tensor components needed to access the data in the tensor
+     *
+     * The tensor components returned by this method must be all passed as kernel argument
+     *
+     * @return a vector containing all the tensor components as @ref TileVariable objects
+     */
+    virtual std::vector<TileVariable> components() const = 0;
+};
+
+/** Tensor storage argument base class */
+class ITensorStorageArgument
+{
+public:
+    virtual ~ITensorStorageArgument() = default;
+    /** Method to get the tensor storage as a string
+     *
+     * @param[in] x The tensor storage to query
+     *
+     * @return the tensor storage as a @ref TensorStorageVariable
+     */
+    virtual TensorStorageVariable storage(TensorStorageType x) = 0;
+    /** Method to get all tensor storages needed to access the data in the tensor
+     *
+     * The tensor storages returned by this method must be all passed as kernel argument
+     *
+     * @return a vector containing all the tensor storages as @ref TensorStorageVariable objects
+     */
+    virtual std::vector<TensorStorageVariable> storages() const = 0;
+};
+
+} // namespace ckw
+
+#endif // CKW_SRC_ITENSORARGUMENT_H
diff --git a/compute_kernel_writer/src/TensorUtils.cpp b/compute_kernel_writer/src/TensorUtils.cpp
index 4970de75a6..24836092d4 100644
--- a/compute_kernel_writer/src/TensorUtils.cpp
+++ b/compute_kernel_writer/src/TensorUtils.cpp
@@ -22,14 +22,14 @@
  * SOFTWARE.
  */
 
+#include "src/TensorUtils.h"
 #include "ckw/Error.h"
 #include "ckw/TensorInfo.h"
-
-#include "src/TensorUtils.h"
+#include "ckw/types/TensorComponentType.h"
 
 namespace ckw
 {
-TensorComponent get_tensor_dimension(TensorDataLayout layout, TensorDataLayoutComponent component)
+TensorComponentType get_tensor_dimension(TensorDataLayout layout, TensorDataLayoutComponent component)
 {
     switch(layout)
     {
@@ -37,41 +37,41 @@ TensorComponent get_tensor_dimension(TensorDataLayout layout, TensorDataLayoutCo
             switch(component)
             {
                 case TensorDataLayoutComponent::C:
-                    return TensorComponent::Dim0;
+                    return TensorComponentType::Dim0;
                 case TensorDataLayoutComponent::W:
-                    return TensorComponent::Dim1;
+                    return TensorComponentType::Dim1;
                 case TensorDataLayoutComponent::H:
-                    return TensorComponent::Dim2;
+                    return TensorComponentType::Dim2;
                 case TensorDataLayoutComponent::N:
-                    return TensorComponent::Dim3;
+                    return TensorComponentType::Dim3;
                 default:
                     COMPUTE_KERNEL_WRITER_ERROR_ON_MSG("Unsupported tensor component for NHWC");
-                    return TensorComponent::Unknown;
+                    return TensorComponentType::Unknown;
             }
         case TensorDataLayout::Ndhwc:
             switch(component)
             {
                 case TensorDataLayoutComponent::C:
-                    return TensorComponent::Dim0;
+                    return TensorComponentType::Dim0;
                 case TensorDataLayoutComponent::W:
-                    return TensorComponent::Dim1;
+                    return TensorComponentType::Dim1;
                 case TensorDataLayoutComponent::H:
-                    return TensorComponent::Dim2;
+                    return TensorComponentType::Dim2;
                 case TensorDataLayoutComponent::D:
-                    return TensorComponent::Dim3;
+                    return TensorComponentType::Dim3;
                 case TensorDataLayoutComponent::N:
-                    return TensorComponent::Dim4;
+                    return TensorComponentType::Dim4;
                 default:
                     COMPUTE_KERNEL_WRITER_ERROR_ON_MSG("Unsupported tensor component for NDHWC");
-                    return TensorComponent::Unknown;
+                    return TensorComponentType::Unknown;
             }
         default:
             COMPUTE_KERNEL_WRITER_ERROR_ON_MSG("Unsupported tensor data layout");
-            return TensorComponent::Unknown;
+            return TensorComponentType::Unknown;
     }
 }
 
-TensorComponent get_tensor_stride(TensorDataLayout layout, TensorDataLayoutComponent component)
+TensorComponentType get_tensor_stride(TensorDataLayout layout, TensorDataLayoutComponent component)
 {
     switch(layout)
     {
@@ -79,37 +79,37 @@ TensorComponent get_tensor_stride(TensorDataLayout layout, TensorDataLayoutCompo
             switch(component)
             {
                 case TensorDataLayoutComponent::C:
-                    return TensorComponent::Stride0;
+                    return TensorComponentType::Stride0;
                 case TensorDataLayoutComponent::W:
-                    return TensorComponent::Stride1;
+                    return TensorComponentType::Stride1;
                 case TensorDataLayoutComponent::H:
-                    return TensorComponent::Stride2;
+                    return TensorComponentType::Stride2;
                 case TensorDataLayoutComponent::N:
-                    return TensorComponent::Stride3;
+                    return TensorComponentType::Stride3;
                 default:
                     COMPUTE_KERNEL_WRITER_ERROR_ON_MSG("Unsupported tensor component for NHWC");
-                    return TensorComponent::Unknown;
+                    return TensorComponentType::Unknown;
             }
         case TensorDataLayout::Ndhwc:
             switch(component)
             {
                 case TensorDataLayoutComponent::C:
-                    return TensorComponent::Stride0;
+                    return TensorComponentType::Stride0;
                 case TensorDataLayoutComponent::W:
-                    return TensorComponent::Stride1;
+                    return TensorComponentType::Stride1;
                 case TensorDataLayoutComponent::H:
-                    return TensorComponent::Stride2;
+                    return TensorComponentType::Stride2;
                 case TensorDataLayoutComponent::D:
-                    return TensorComponent::Stride3;
+                    return TensorComponentType::Stride3;
                 case TensorDataLayoutComponent::N:
-                    return TensorComponent::Stride4;
+                    return TensorComponentType::Stride4;
                 default:
                     COMPUTE_KERNEL_WRITER_ERROR_ON_MSG("Unsupported tensor component for NDHWC");
-                    return TensorComponent::Unknown;
+                    return TensorComponentType::Unknown;
             }
         default:
             COMPUTE_KERNEL_WRITER_ERROR_ON_MSG("Unsupported tensor data layout");
-            return TensorComponent::Unknown;
+            return TensorComponentType::Unknown;
     }
 }
 } // namespace ckw
diff --git a/compute_kernel_writer/src/TensorUtils.h b/compute_kernel_writer/src/TensorUtils.h
index 84eca084bb..bb0af5c0b9 100644
--- a/compute_kernel_writer/src/TensorUtils.h
+++ b/compute_kernel_writer/src/TensorUtils.h
@@ -22,8 +22,8 @@
  * SOFTWARE.
  */
 
-#ifndef COMPUTE_KERNEL_WRITER_SRC_TENSORUTILS_H
-#define COMPUTE_KERNEL_WRITER_SRC_TENSORUTILS_H
+#ifndef CKW_SRC_TENSORUTILS_H
+#define CKW_SRC_TENSORUTILS_H
 
 #include <cstdint>
 
@@ -33,7 +33,7 @@ namespace ckw
 // Forward declarations
 enum class TensorDataLayout;
 enum class TensorDataLayoutComponent;
-enum class TensorComponent : uint32_t;
+enum class TensorComponentType : uint32_t;
 
 /** Get tensor dimension from a given data layout and data layout component
  *
@@ -42,7 +42,7 @@ enum class TensorComponent : uint32_t;
  *
  * @return the @ref TensorComponent
  */
-TensorComponent get_tensor_dimension(TensorDataLayout layout, TensorDataLayoutComponent component);
+TensorComponentType get_tensor_dimension(TensorDataLayout layout, TensorDataLayoutComponent component);
 
 /** Get tensor stride from a given data layout and data layout component
  *
@@ -51,6 +51,7 @@ TensorComponent get_tensor_dimension(TensorDataLayout layout, TensorDataLayoutCo
  *
  * @return the @ref TensorComponent
  */
-TensorComponent get_tensor_stride(TensorDataLayout layout, TensorDataLayoutComponent component);
+TensorComponentType get_tensor_stride(TensorDataLayout layout, TensorDataLayoutComponent component);
 } // namespace ckw
-#endif /* COMPUTE_KERNEL_WRITER_SRC_TENSORUTILS_H */
+
+#endif // CKW_SRC_TENSORUTILS_H
diff --git a/compute_kernel_writer/src/cl/CLHelpers.cpp b/compute_kernel_writer/src/cl/CLHelpers.cpp
index 5a3d0fab81..af8a8a07ac 100644
--- a/compute_kernel_writer/src/cl/CLHelpers.cpp
+++ b/compute_kernel_writer/src/cl/CLHelpers.cpp
@@ -21,10 +21,10 @@
  * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
  * SOFTWARE.
  */
+#include "src/cl/CLHelpers.h"
 #include "ckw/Error.h"
 #include "ckw/types/DataType.h"
-
-#include "src/cl/CLHelpers.h"
+#include "ckw/types/TensorStorageType.h"
 
 namespace ckw
 {
@@ -120,4 +120,26 @@ int32_t width_to_cl_vector_size(int32_t width)
             return 0;
     }
 }
+
+std::string cl_get_variable_storagetype_as_string(TensorStorageType storage)
+{
+    std::string res;
+    switch(storage)
+    {
+        case TensorStorageType::BufferUint8Ptr:
+            res += "__global uchar*";
+            break;
+        case TensorStorageType::Texture2dReadOnly:
+            res += "__read_only image2d_t";
+            break;
+        case TensorStorageType::Texture2dWriteOnly:
+            res += "__write_only image2d_t";
+            break;
+        default:
+            COMPUTE_KERNEL_WRITER_ERROR_ON_MSG("Unsupported storage type");
+    }
+
+    return res;
+}
+
 } // namespace ckw
diff --git a/compute_kernel_writer/src/cl/CLHelpers.h b/compute_kernel_writer/src/cl/CLHelpers.h
index a9a84e2187..d0ca488617 100644
--- a/compute_kernel_writer/src/cl/CLHelpers.h
+++ b/compute_kernel_writer/src/cl/CLHelpers.h
@@ -24,14 +24,15 @@
 #ifndef CKW_SRC_CL_CLHELPERS_H
 #define CKW_SRC_CL_CLHELPERS_H
 
-#include <string>
 #include <cstdint>
+#include <string>
 
 /** OpenCL specific helper functions */
 namespace ckw
 {
 // Forward declarations
 enum class DataType;
+enum class TensorStorageType : uint32_t;
 
 /** Helper function to validate the vector length of OpenCL vector data types
  *
@@ -58,6 +59,13 @@ std::string cl_get_variable_datatype_as_string(DataType dt, int32_t len);
 */
 int32_t width_to_cl_vector_size(int32_t width);
 
+/** Helper function to return the OpenCL storage type as a string from a @ref TensorStorage
+ *
+ * @param[in] storage Storage type
+ *
+ * @return the OpenCL storage type as a string
+ */
+std::string cl_get_variable_storagetype_as_string(TensorStorageType storage);
 } // namespace ckw
 
 #endif /* COMPUTE_KERNEL_WRITER_SRC_CL_CLHELPERS_H */
diff --git a/compute_kernel_writer/src/cl/CLTensorArgument.cpp b/compute_kernel_writer/src/cl/CLTensorArgument.cpp
new file mode 100644
index 0000000000..ed1c5bd687
--- /dev/null
+++ b/compute_kernel_writer/src/cl/CLTensorArgument.cpp
@@ -0,0 +1,247 @@
+/*
+ * Copyright (c) 2023 Arm Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+
+#include "src/cl/CLTensorArgument.h"
+#include "ckw/Error.h"
+#include "src/cl/CLHelpers.h"
+#include "src/types/TensorComponentType.h"
+
+#include <algorithm>
+#include <vector>
+
+namespace ckw
+{
+CLTensorArgument::CLTensorArgument(const std::string &name, const TensorInfo &info, bool return_dims_by_value)
+{
+    _return_dims_by_value = return_dims_by_value;
+    _basename             = name;
+    _info                 = info;
+}
+
+TileVariable CLTensorArgument::component(TensorComponentType x)
+{
+    if(_return_dims_by_value)
+    {
+        uint32_t component_type = static_cast<uint32_t>(x);
+
+        const bool is_dimension         = (component_type & static_cast<uint32_t>(TensorComponentBitmask::Dimension)) != 0;
+        const bool is_folded_dimensions = (component_type & static_cast<uint32_t>(TensorComponentBitmask::FoldedDimensions)) != 0;
+
+        constexpr auto bitmask_all     = static_cast<uint32_t>(TensorComponentIndexBitmask::All);
+        constexpr auto bitmask_index_0 = static_cast<uint32_t>(TensorComponentIndexBitmask::Index0);
+#ifdef COMPUTE_KERNEL_WRITER_ASSERTS_ENABLED
+        constexpr auto bitmask_index_1 = static_cast<uint32_t>(TensorComponentIndexBitmask::Index1);
+        constexpr auto bitmask_index_2 = static_cast<uint32_t>(TensorComponentIndexBitmask::Index2);
+        constexpr auto bitmask_index_3 = static_cast<uint32_t>(TensorComponentIndexBitmask::Index3);
+#endif // COMPUTE_KERNEL_WRITER_ASSERTS_ENABLED
+
+        // Make sure that the encoding of component type hasn't changed and each nibble is 4 bits apart.
+        CKW_ASSERT(bitmask_all == (bitmask_index_0 | bitmask_index_1 | bitmask_index_2 | bitmask_index_3));
+        CKW_ASSERT(bitmask_index_0 == bitmask_index_1 >> 4);
+        CKW_ASSERT(bitmask_index_1 == bitmask_index_2 >> 4);
+        CKW_ASSERT(bitmask_index_2 == bitmask_index_3 >> 4);
+
+        // If we have a dimension or folded dimensions, we can return the corresponding value if it is not dynamic (not equal to -1)
+        if(is_dimension == true || is_folded_dimensions == true)
+        {
+            component_type = component_type & bitmask_all;
+
+            int32_t idx = 1;
+            for(int32_t i = 0; i < tensor_component_index_max_count; ++i)
+            {
+                uint32_t dim_idx = component_type & bitmask_index_0;
+
+                if(dim_idx == 0)
+                {
+                    // Stop at the first nibble containing 0
+                    break;
+                }
+
+                // Subtract - 1. Please refer to the TensorComponentIndexBitmask documentation
+                dim_idx -= 1;
+
+                // Get the dimension value
+                const int32_t dim_val = _info.shape()[dim_idx];
+
+                if(dim_val == kDynamicTensorDimensionValue)
+                {
+                    // We cannot return the dimension by value if it is dynamic.
+                    // Therefore, force the idx variable to kDynamicTensorDimensionValue and break the loop.
+                    idx = kDynamicTensorDimensionValue;
+                    break;
+                }
+
+                idx *= dim_val;
+
+                // Go to the next nibble
+                component_type >>= 4;
+            }
+
+            if(idx != kDynamicTensorDimensionValue)
+            {
+                TileVariable t;
+                t.str      = std::to_string(idx);
+                t.desc.dt  = DataType::Uint32;
+                t.desc.len = 1;
+                return t;
+            }
+        }
+    }
+
+    auto it = std::find(_components_used.begin(), _components_used.end(), x);
+
+    // Add to the list of used components if not present yet
+    if(it == _components_used.end())
+    {
+        _components_used.push_back(x);
+    }
+
+    TileVariable t;
+    t.str      = create_component_name(x);
+    t.desc.dt  = DataType::Int32;
+    t.desc.len = 1;
+    return t;
+}
+
+TensorStorageVariable CLTensorArgument::storage(TensorStorageType x)
+{
+    if(std::find(_storages_used.begin(), _storages_used.end(), x) == _storages_used.end())
+    {
+        _storages_used.push_back(x);
+    }
+
+    TensorStorageVariable t;
+    t.val  = create_storage_name(x);
+    t.type = cl_get_variable_storagetype_as_string(x);
+
+    return t;
+}
+
+std::string CLTensorArgument::create_storage_name(TensorStorageType x) const
+{
+    std::string var_name = _basename;
+
+    switch(x)
+    {
+        case TensorStorageType::BufferUint8Ptr:
+            var_name += "_ptr";
+            break;
+        case TensorStorageType::Texture2dReadOnly:
+        case TensorStorageType::Texture2dWriteOnly:
+            var_name += "_img2d";
+            break;
+        default:
+            CKW_ASSERT_FAILED_MSG("Unsupported tensor storage");
+            return "";
+    }
+
+    return var_name;
+}
+
+std::string CLTensorArgument::create_component_name(TensorComponentType x) const
+{
+    std::string var_name = _basename;
+
+    switch(x)
+    {
+        case TensorComponentType::OffsetFirstElement:
+            var_name += "_offset_first_element";
+            break;
+        case TensorComponentType::Stride0:
+            var_name += "_stride0";
+            break;
+        case TensorComponentType::Stride1:
+            var_name += "_stride1";
+            break;
+        case TensorComponentType::Stride2:
+            var_name += "_stride2";
+            break;
+        case TensorComponentType::Stride3:
+            var_name += "_stride3";
+            break;
+        case TensorComponentType::Stride4:
+            var_name += "_stride4";
+            break;
+        case TensorComponentType::Dim0:
+            var_name += "_dim0";
+            break;
+        case TensorComponentType::Dim1:
+            var_name += "_dim1";
+            break;
+        case TensorComponentType::Dim2:
+            var_name += "_dim2";
+            break;
+        case TensorComponentType::Dim3:
+            var_name += "_dim3";
+            break;
+        case TensorComponentType::Dim4:
+            var_name += "_dim4";
+            break;
+        case TensorComponentType::Dim1xDim2:
+            var_name += "_dim1xdim2";
+            break;
+        case TensorComponentType::Dim2xDim3:
+            var_name += "_dim2xdim3";
+            break;
+        case TensorComponentType::Dim1xDim2xDim3:
+            var_name += "_dim1xdim2xdim3";
+            break;
+        default:
+            COMPUTE_KERNEL_WRITER_ERROR_ON_MSG("Unsupported tensor component");
+            return "";
+    }
+
+    return var_name;
+}
+
+std::vector<TensorStorageVariable> CLTensorArgument::storages() const
+{
+    std::vector<TensorStorageVariable> storages;
+    for(auto &val : _storages_used)
+    {
+        TensorStorageVariable t;
+        t.val  = create_storage_name(val);
+        t.type = cl_get_variable_storagetype_as_string(val);
+        storages.push_back(t);
+    }
+
+    return storages;
+}
+
+std::vector<TileVariable> CLTensorArgument::components() const
+{
+    std::vector<TileVariable> components;
+
+    for(auto &val : _components_used)
+    {
+        TileVariable t;
+        t.str      = create_component_name(val);
+        t.desc.dt  = DataType::Int32;
+        t.desc.len = 1;
+        components.push_back(t);
+    }
+
+    return components;
+}
+} // namespace ckw
diff --git a/compute_kernel_writer/src/cl/CLTensorArgument.h b/compute_kernel_writer/src/cl/CLTensorArgument.h
new file mode 100644
index 0000000000..cd924846c5
--- /dev/null
+++ b/compute_kernel_writer/src/cl/CLTensorArgument.h
@@ -0,0 +1,70 @@
+/*
+ * Copyright (c) 2023 Arm Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#ifndef CKW_SRC_CL_CLTENSORARGUMENT_H
+#define CKW_SRC_CL_CLTENSORARGUMENT_H
+
+#include "src/ITensorArgument.h"
+
+#include <string>
+#include <vector>
+
+namespace ckw
+{
+// Forward declarations
+class TensorInfo;
+
+/** OpenCL specific tensor argument
+ *  Internally, the object keeps track of the components and storages used to minimize the number
+ *  of kernel arguments required. Therefore, if we create this object but we do not access any components
+ *  or storages, the storages() and components() method will return an empty list.
+*/
+class CLTensorArgument : public ITensorArgument, ITensorStorageArgument, ITensorComponentArgument
+{
+public:
+    /** Constructor
+     *
+     * @param[in] name                 Tensor name
+     * @param[in] info                 Tensor info
+     * @param[in] return_dims_by_value Flag to return the dimensions by value whenever it is possible.
+     *                                 True, if the dimensions should be returned as value instead as variable.
+    */
+    CLTensorArgument(const std::string &name, const TensorInfo &info, bool return_dims_by_value);
+
+    // Inherited method overridden
+    TensorStorageVariable              storage(TensorStorageType x);
+    TileVariable                       component(TensorComponentType x);
+    std::vector<TensorStorageVariable> storages() const;
+    std::vector<TileVariable>          components() const;
+
+private:
+    std::string create_storage_name(TensorStorageType x) const;
+    std::string create_component_name(TensorComponentType x) const;
+
+    bool                             _return_dims_by_value{ false };
+    std::vector<TensorStorageType>       _storages_used{};
+    std::vector<TensorComponentType> _components_used{};
+};
+} // namespace ckw
+
+#endif // CKW_SRC_CL_CLTENSORARGUMENT_H
diff --git a/compute_kernel_writer/src/types/TensorComponentType.h b/compute_kernel_writer/src/types/TensorComponentType.h
new file mode 100644
index 0000000000..03f4f4f5c8
--- /dev/null
+++ b/compute_kernel_writer/src/types/TensorComponentType.h
@@ -0,0 +1,78 @@
+/*
+ * Copyright (c) 2023 Arm Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+
+#ifndef CKW_SRC_TYPES_TENSORCOMPONENTTYPE_H
+#define CKW_SRC_TYPES_TENSORCOMPONENTTYPE_H
+
+#include <cstdint>
+
+namespace ckw
+{
+
+/** Compute Kernel Writer tensor component bitmask.
+ *
+ * The bitmask can be used to retrieve the info from @ref TensorComponent.
+ */
+enum class TensorComponentBitmask : uint32_t
+{
+    OffsetFirstElement = 0x01000000, // For example, OffsetFirstElement in TensorComponent
+    Stride             = 0x02000000, // For example, stride0 in TensorComponent
+    Dimension          = 0x04000000, // For example, Dim0 in TensorComponent
+    FoldedDimensions   = 0x08000000, // For example, Dim0xDim1 in TensorComponent
+};
+
+/** Mask to retrieve the component index (for example, 1 for stride1, 2 for stride2, or 1 and 2 for Dim1xDim2).
+ *
+ * The 4 least significant half-bytes (nibbles) of the @ref TensorComponent are used to retrieve the specific component index.
+ * TensorComponent = | i7 | i6 | i5 | i4 | i3 | i2 | i1 | i0 |, where i7,...i0 are the nibbles
+ * of the TensorComponent hexadecimal number. i0, i1, i2 and i3 are reserved to the component index.
+ *
+ * In particular:
+ *
+ *   -# i0: reserved to the first folded dimension component index
+ *   -# i1: reserved to the second folded dimension component index
+ *   -# i2: reserved to the third folded dimension component index
+ *   -# i3: reserved to the fourth folded dimension component index
+ *
+ * Therefore, if there are no folded dimensions (dimensions and strides), only i0 is used.
+ * Instead, if there are two folded dimensions, only i0 and i1 are used.
+ *
+ * The component index is stored with the corresponding hexadecimal number + 1,
+ * hence the component index 0 is represented as 1, while the component index 3 is represented as 4.
+ */
+enum class TensorComponentIndexBitmask : uint32_t
+{
+    All    = 0x0000ffff, // All nibbles reserved to the tensor component index
+    Index0 = 0x0000000f, // Folded dimension 0
+    Index1 = 0x000000f0, // Folded dimension 1
+    Index2 = 0x00000f00, // Folded dimension 2
+    Index3 = 0x0000f000  // Folded dimension 3
+};
+
+/** The maximum number of folded dimensions. */
+constexpr int tensor_component_index_max_count = 4;
+
+} // namespace ckw
+
+#endif // CKW_SRC_TYPES_TENSORCOMPONENTTYPE_H
diff --git a/compute_kernel_writer/validation/Validation.cpp b/compute_kernel_writer/validation/Validation.cpp
index e4884fa4aa..5d53a16eff 100644
--- a/compute_kernel_writer/validation/Validation.cpp
+++ b/compute_kernel_writer/validation/Validation.cpp
@@ -22,12 +22,13 @@
  * SOFTWARE.
  */
 
+#include "tests/CLConstantTileTest.hpp"
 #include "tests/CLKernelWriterCommentTest.h"
 #include "tests/CLKernelWriterDeclareTileTest.h"
-#include "tests/CLConstantTileTest.hpp"
+#include "tests/CLTensorArgumentTest.h"
 #include "tests/CLTileTest.hpp"
-#include "tests/TensorBitMaskTest.hpp"
-#include "tests/UtilsTest.hpp"
+#include "tests/TensorBitMaskTest.h"
+#include "tests/UtilsTest.h"
 
 #include <memory>
 #include <vector>
@@ -65,6 +66,13 @@ int32_t main()
     const auto test15 = std::make_unique<CLKernelWriterCommentTest>();
 #endif /* COMPUTE_KERNEL_WRITER_DEBUG_ENABLED */
     const auto test16 = std::make_unique<CLKernelWriterDeclareTileTest>();
+    const auto test17 = std::make_unique<CLTensorArgumentComponentNamesTest>();
+    const auto test18 = std::make_unique<CLTensorArgumentStorageNamesTest>();
+    const auto test19 = std::make_unique<CLTensorArgumentComponentValuesTest>();
+    const auto test20 = std::make_unique<CLTensorArgumentComponentsUsedPassByValueFalseTest>();
+    const auto test21 = std::make_unique<CLTensorArgumentComponentsUsedPassByValueTrueTest>();
+    const auto test22 = std::make_unique<CLTensorArgumentStoragesUsedTest>();
+    const auto test23 = std::make_unique<CLTensorArgumentComponentsUsedPassByValueTrueDynamicDimTrueTest>();
 
     tests.push_back(test3.get());
     tests.push_back(test4.get());
@@ -82,6 +90,13 @@ int32_t main()
     tests.push_back(test15.get());
 #endif /* COMPUTE_KERNEL_WRITER_DEBUG_ENABLED */
     tests.push_back(test16.get());
+    tests.push_back(test17.get());
+    tests.push_back(test18.get());
+    tests.push_back(test19.get());
+    tests.push_back(test20.get());
+    tests.push_back(test21.get());
+    tests.push_back(test22.get());
+    tests.push_back(test23.get());
 #endif /* COMPUTE_KERNEL_WRITER_OPENCL_ENABLED */
 
     bool all_test_passed = true;
diff --git a/compute_kernel_writer/validation/tests/CLTensorArgumentTest.h b/compute_kernel_writer/validation/tests/CLTensorArgumentTest.h
new file mode 100644
index 0000000000..6db1384247
--- /dev/null
+++ b/compute_kernel_writer/validation/tests/CLTensorArgumentTest.h
@@ -0,0 +1,533 @@
+/*
+ * Copyright (c) 2023 Arm Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+
+#ifndef CKW_TESTS_CLTENSORARGUMENTTEST_H
+#define CKW_TESTS_CLTENSORARGUMENTTEST_H
+
+#include "common/Common.h"
+#include "src/cl/CLHelpers.h"
+#include "src/cl/CLTensorArgument.h"
+
+#include <string>
+#include <vector>
+
+namespace ckw
+{
+class CLTensorArgumentComponentNamesTest : public ITest
+{
+public:
+    const DataType    dt          = DataType::Fp32;
+    const TensorShape shape       = TensorShape({ { 12, 14, 3, 1, 2 } });
+    const std::string tensor_name = "src";
+
+    CLTensorArgumentComponentNamesTest()
+    {
+        _components.push_back(TensorComponentType::Dim0);
+        _components.push_back(TensorComponentType::Dim1);
+        _components.push_back(TensorComponentType::Dim2);
+        _components.push_back(TensorComponentType::Dim3);
+        _components.push_back(TensorComponentType::Dim4);
+        _components.push_back(TensorComponentType::Dim1xDim2);
+        _components.push_back(TensorComponentType::Dim2xDim3);
+        _components.push_back(TensorComponentType::OffsetFirstElement);
+        _components.push_back(TensorComponentType::Stride0);
+        _components.push_back(TensorComponentType::Stride1);
+        _components.push_back(TensorComponentType::Stride2);
+        _components.push_back(TensorComponentType::Stride3);
+        _components.push_back(TensorComponentType::Stride4);
+
+        _expected_vars.push_back("src_dim0");
+        _expected_vars.push_back("src_dim1");
+        _expected_vars.push_back("src_dim2");
+        _expected_vars.push_back("src_dim3");
+        _expected_vars.push_back("src_dim4");
+        _expected_vars.push_back("src_dim1xdim2");
+        _expected_vars.push_back("src_dim2xdim3");
+        _expected_vars.push_back("src_offset_first_element");
+        _expected_vars.push_back("src_stride0");
+        _expected_vars.push_back("src_stride1");
+        _expected_vars.push_back("src_stride2");
+        _expected_vars.push_back("src_stride3");
+        _expected_vars.push_back("src_stride4");
+    }
+
+    bool run() override
+    {
+        VALIDATE_ON_MSG(_components.size() == _expected_vars.size(), "The number of components and variables does not match");
+
+        // The status of this variable can change in VALIDATE_TEST()
+        bool all_tests_passed = true;
+
+        const TensorInfo info(dt, shape, TensorDataLayout::Nhwc, 1);
+
+        const size_t num_tests = _expected_vars.size();
+
+        int32_t test_idx = 0;
+        for(size_t i = 0; i < num_tests; ++i)
+        {
+            CLTensorArgument arg(tensor_name, info, false /* return_dims_by_value */);
+
+            const std::string expected_var_name = _expected_vars[i];
+            const std::string actual_var_name   = arg.component(_components[i]).str;
+
+            VALIDATE_TEST(actual_var_name.compare(expected_var_name) == 0, all_tests_passed, test_idx++);
+        }
+        return all_tests_passed;
+    }
+
+    std::string name() override
+    {
+        return "CLTensorArgumentVariableNamesTest";
+    }
+
+private:
+    std::vector<TensorComponentType> _components{};
+    std::vector<std::string>         _expected_vars{};
+};
+
+class CLTensorArgumentStorageNamesTest : public ITest
+{
+public:
+    const DataType    dt          = DataType::Fp32;
+    const TensorShape shape       = TensorShape({ { 12, 14, 3, 1, 2 } });
+    const std::string tensor_name = "src";
+
+    CLTensorArgumentStorageNamesTest()
+    {
+        _storages.push_back(TensorStorageType::BufferUint8Ptr);
+        _storages.push_back(TensorStorageType::Texture2dReadOnly);
+        _storages.push_back(TensorStorageType::Texture2dWriteOnly);
+
+        _expected_vars.push_back("src_ptr");
+        _expected_vars.push_back("src_img2d");
+        _expected_vars.push_back("src_img2d");
+    }
+
+    bool run() override
+    {
+        VALIDATE_ON_MSG(_storages.size() == _expected_vars.size(), "The number of storages and variables does not match");
+
+        // The status of this variable can change in VALIDATE_TEST()
+        bool all_tests_passed = true;
+
+        const TensorInfo info(dt, shape, TensorDataLayout::Nhwc, 1);
+
+        const size_t num_tests = _expected_vars.size();
+
+        int32_t test_idx = 0;
+        for(size_t i = 0; i < num_tests; ++i)
+        {
+            CLTensorArgument arg(tensor_name, info, false /* return_dims_by_value */);
+
+            const std::string expected_var_name = _expected_vars[i];
+            const std::string actual_var_name   = arg.storage(_storages[i]).val;
+
+            VALIDATE_TEST(actual_var_name.compare(expected_var_name) == 0, all_tests_passed, test_idx++);
+        }
+        return all_tests_passed;
+    }
+
+    std::string name() override
+    {
+        return "CLTensorArgumentStorageNamesTest";
+    }
+
+private:
+    std::vector<TensorStorageType> _storages{};
+    std::vector<std::string>       _expected_vars{};
+};
+
+class CLTensorArgumentComponentValuesTest : public ITest
+{
+public:
+    const DataType    dt          = DataType::Fp32;
+    const TensorShape shape       = TensorShape({ { 12, 14, 3, 1, 2 } });
+    const std::string tensor_name = "src";
+
+    CLTensorArgumentComponentValuesTest()
+    {
+        _components.push_back(TensorComponentType::Dim0);
+        _components.push_back(TensorComponentType::Dim1);
+        _components.push_back(TensorComponentType::Dim2);
+        _components.push_back(TensorComponentType::Dim3);
+        _components.push_back(TensorComponentType::Dim4);
+        _components.push_back(TensorComponentType::Dim1xDim2);
+        _components.push_back(TensorComponentType::Dim2xDim3);
+
+        _expected_vals.push_back(std::to_string(shape[0]));
+        _expected_vals.push_back(std::to_string(shape[1]));
+        _expected_vals.push_back(std::to_string(shape[2]));
+        _expected_vals.push_back(std::to_string(shape[3]));
+        _expected_vals.push_back(std::to_string(shape[4]));
+        _expected_vals.push_back(std::to_string(shape[1] * shape[2]));
+        _expected_vals.push_back(std::to_string(shape[2] * shape[3]));
+    }
+
+    bool run() override
+    {
+        VALIDATE_ON_MSG(_components.size() == _expected_vals.size(), "The number of components and values does not match");
+
+        // The status of this variable can change in VALIDATE_TEST()
+        bool all_tests_passed = true;
+
+        const TensorInfo info(dt, shape, TensorDataLayout::Nhwc, 1);
+
+        const size_t num_tests = _expected_vals.size();
+
+        int32_t test_idx = 0;
+        for(size_t i = 0; i < num_tests; ++i)
+        {
+            CLTensorArgument arg(tensor_name, info, true /* return_dims_by_value */);
+
+            const std::string expected_var_val = _expected_vals[i];
+            const std::string actual_var_val   = arg.component(_components[i]).str;
+
+            VALIDATE_TEST(actual_var_val.compare(expected_var_val) == 0, all_tests_passed, test_idx++);
+        }
+        return all_tests_passed;
+    }
+
+    std::string name() override
+    {
+        return "CLTensorArgumentComponentValuesTest";
+    }
+
+private:
+    std::vector<TensorComponentType> _components{};
+    std::vector<std::string>         _expected_vals{};
+};
+
+class CLTensorArgumentComponentsUsedPassByValueFalseTest : public ITest
+{
+public:
+    const DataType    dt          = DataType::Fp32;
+    const TensorShape shape       = TensorShape({ { 12, 14, 3, 1, 2 } });
+    const std::string tensor_name = "src";
+
+    CLTensorArgumentComponentsUsedPassByValueFalseTest()
+    {
+        _components.push_back(TensorComponentType::Dim0);
+        _components.push_back(TensorComponentType::Dim2);
+        _components.push_back(TensorComponentType::Dim3);
+        _components.push_back(TensorComponentType::Dim1xDim2);
+        _components.push_back(TensorComponentType::OffsetFirstElement);
+        _components.push_back(TensorComponentType::Stride1);
+        _components.push_back(TensorComponentType::Stride2);
+        _components.push_back(TensorComponentType::Stride3);
+        _components.push_back(TensorComponentType::Dim0); // Repeat the query. The TensorArgument should not create a new variable
+        _components.push_back(TensorComponentType::Dim2); // Repeat the query. The TensorArgument should not create a new variable
+        _components.push_back(TensorComponentType::Dim3); // Repeat the query. The TensorArgument should not create a new variable
+
+        _expected_vars.push_back("src_dim0");
+        _expected_vars.push_back("src_dim2");
+        _expected_vars.push_back("src_dim3");
+        _expected_vars.push_back("src_dim1xdim2");
+        _expected_vars.push_back("src_offset_first_element");
+        _expected_vars.push_back("src_stride1");
+        _expected_vars.push_back("src_stride2");
+        _expected_vars.push_back("src_stride3");
+    }
+
+    bool run() override
+    {
+        // The status of this variable can change in VALIDATE_TEST()
+        bool all_tests_passed = true;
+
+        const TensorInfo info(dt, shape, TensorDataLayout::Nhwc, 1);
+
+        const size_t num_components = _components.size();
+
+        int32_t test_idx = 0;
+
+        CLTensorArgument arg(tensor_name, info, false /* return_dims_by_value */);
+        for(size_t i = 0; i < num_components; ++i)
+        {
+            arg.component(_components[i]);
+        }
+
+        const auto actual_vars = arg.components();
+
+        const size_t num_vars = _expected_vars.size();
+
+        VALIDATE_ON_MSG(actual_vars.size() == num_vars, "The number of variables must match the number of expected variables");
+
+        for(size_t i = 0; i < num_vars; ++i)
+        {
+            // Validate variable name
+            const std::string expected_var_name = _expected_vars[i];
+            const std::string actual_var_name   = actual_vars[i].str;
+            VALIDATE_TEST(actual_var_name.compare(expected_var_name) == 0, all_tests_passed, test_idx++);
+
+            // Validate data type
+            const DataType expected_var_type = DataType::Int32;
+            const DataType actual_var_type   = actual_vars[i].desc.dt;
+            VALIDATE_TEST(actual_var_type == expected_var_type, all_tests_passed, test_idx++);
+
+            // Validate data type length
+            const int32_t expected_var_len = 1;
+            const int32_t actual_var_len   = actual_vars[i].desc.len;
+            VALIDATE_TEST(actual_var_len == expected_var_len, all_tests_passed, test_idx++);
+        }
+        return all_tests_passed;
+    }
+
+    std::string name() override
+    {
+        return "CLTensorArgumentComponentsUsedPassByValueFalseTest";
+    }
+
+private:
+    std::vector<TensorComponentType> _components{};
+    std::vector<std::string>         _expected_vars{};
+};
+
+class CLTensorArgumentComponentsUsedPassByValueTrueTest : public ITest
+{
+public:
+    const DataType    dt          = DataType::Fp32;
+    const TensorShape shape       = TensorShape({ { 12, 14, 3, 1, 2 } });
+    const std::string tensor_name = "src";
+
+    CLTensorArgumentComponentsUsedPassByValueTrueTest()
+    {
+        _components.push_back(TensorComponentType::Dim0);
+        _components.push_back(TensorComponentType::Dim2);
+        _components.push_back(TensorComponentType::Dim3);
+        _components.push_back(TensorComponentType::Dim1xDim2);
+        _components.push_back(TensorComponentType::OffsetFirstElement);
+        _components.push_back(TensorComponentType::Stride1);
+        _components.push_back(TensorComponentType::Stride2);
+        _components.push_back(TensorComponentType::Stride3);
+        _components.push_back(TensorComponentType::OffsetFirstElement); // Repeat the query. The TensorArgument should not create a new variable
+        _components.push_back(TensorComponentType::Stride1);            // Repeat the query. The TensorArgument should not create a new variable
+
+        _expected_vars.push_back("src_offset_first_element");
+        _expected_vars.push_back("src_stride1");
+        _expected_vars.push_back("src_stride2");
+        _expected_vars.push_back("src_stride3");
+    }
+
+    bool run() override
+    {
+        // The status of this variable can change in VALIDATE_TEST()
+        bool all_tests_passed = true;
+
+        const TensorInfo info(dt, shape, TensorDataLayout::Nhwc, 1);
+
+        const size_t num_components = _components.size();
+
+        int32_t test_idx = 0;
+
+        CLTensorArgument arg(tensor_name, info, true /* return_dims_by_value */);
+        for(size_t i = 0; i < num_components; ++i)
+        {
+            arg.component(_components[i]);
+        }
+
+        const auto actual_vars = arg.components();
+
+        const size_t num_vars = _expected_vars.size();
+
+        VALIDATE_ON_MSG(actual_vars.size() == num_vars, "The number of variables must match the number of expected variables");
+
+        // Since the dimensions are passed by value, we expect only the variables for the strides
+        for(size_t i = 0; i < num_vars; ++i)
+        {
+            // Validate variable name
+            const std::string expected_var_name = _expected_vars[i];
+            const std::string actual_var_name   = actual_vars[i].str;
+            VALIDATE_TEST(actual_var_name.compare(expected_var_name) == 0, all_tests_passed, test_idx++);
+
+            // Validate data type
+            const DataType expected_var_type = DataType::Int32;
+            const DataType actual_var_type   = actual_vars[i].desc.dt;
+            VALIDATE_TEST(actual_var_type == expected_var_type, all_tests_passed, test_idx++);
+
+            // Validate data type length
+            const int32_t expected_var_len = 1;
+            const int32_t actual_var_len   = actual_vars[i].desc.len;
+            VALIDATE_TEST(actual_var_len == expected_var_len, all_tests_passed, test_idx++);
+        }
+        return all_tests_passed;
+    }
+
+    std::string name() override
+    {
+        return "CLTensorArgumentComponentsUsedPassByValueTrueTest";
+    }
+
+private:
+    std::vector<TensorComponentType> _components{};
+    std::vector<std::string>         _expected_vars{};
+};
+
+class CLTensorArgumentStoragesUsedTest : public ITest
+{
+public:
+    const DataType    dt          = DataType::Fp32;
+    const TensorShape shape       = TensorShape({ { 12, 14, 3, 1, 2 } });
+    const std::string tensor_name = "src";
+
+    CLTensorArgumentStoragesUsedTest()
+    {
+        _storages.push_back(TensorStorageType::BufferUint8Ptr);
+        _storages.push_back(TensorStorageType::Texture2dReadOnly);
+        _storages.push_back(TensorStorageType::BufferUint8Ptr); // Repeat the query. The TensorArgument should not create a new variable
+
+        _expected_vars.push_back("src_ptr");
+        _expected_vars.push_back("src_img2d");
+    }
+
+    bool run() override
+    {
+        // The status of this variable can change in VALIDATE_TEST()
+        bool all_tests_passed = true;
+
+        const TensorInfo info(dt, shape, TensorDataLayout::Nhwc, 1);
+
+        const size_t num_storages = _storages.size();
+
+        int32_t test_idx = 0;
+
+        CLTensorArgument arg(tensor_name, info, true /* return_dims_by_value */);
+        for(size_t i = 0; i < num_storages; ++i)
+        {
+            arg.storage(_storages[i]);
+        }
+
+        const auto actual_vars = arg.storages();
+
+        const size_t num_vars = _expected_vars.size();
+
+        VALIDATE_ON_MSG(actual_vars.size() == num_vars, "The number of variables must match the number of expected variables");
+
+        for(size_t i = 0; i < num_vars; ++i)
+        {
+            // Validate variable name
+            const std::string expected_var_name = _expected_vars[i];
+            const std::string actual_var_name   = actual_vars[i].val;
+            VALIDATE_TEST(actual_var_name.compare(expected_var_name) == 0, all_tests_passed, test_idx++);
+
+            // Validate storage type
+            const std::string expected_var_type = cl_get_variable_storagetype_as_string(_storages[i]);
+            const std::string actual_var_type   = actual_vars[i].type;
+            VALIDATE_TEST(actual_var_type == expected_var_type, all_tests_passed, test_idx++);
+        }
+        return all_tests_passed;
+    }
+
+    std::string name() override
+    {
+        return "CLTensorArgumentStoragesUsedTest";
+    }
+
+private:
+    std::vector<TensorStorageType> _storages{};
+    std::vector<std::string>       _expected_vars{};
+};
+
+class CLTensorArgumentComponentsUsedPassByValueTrueDynamicDimTrueTest : public ITest
+{
+public:
+    const DataType    dt          = DataType::Fp32;
+    const TensorShape shape       = TensorShape({ { -1, -1, 3, 1, 2 } });
+    const std::string tensor_name = "src";
+
+    CLTensorArgumentComponentsUsedPassByValueTrueDynamicDimTrueTest()
+    {
+        _components.push_back(TensorComponentType::Dim0);
+        _components.push_back(TensorComponentType::Dim2);
+        _components.push_back(TensorComponentType::Dim3);
+        _components.push_back(TensorComponentType::Dim1xDim2);
+        _components.push_back(TensorComponentType::OffsetFirstElement);
+        _components.push_back(TensorComponentType::Stride1);
+        _components.push_back(TensorComponentType::Stride2);
+        _components.push_back(TensorComponentType::Stride3);
+        _components.push_back(TensorComponentType::OffsetFirstElement); // Repeat the query. The TensorArgument should not create a new variable
+        _components.push_back(TensorComponentType::Stride1);            // Repeat the query. The TensorArgument should not create a new variable
+
+        _expected_vars.push_back("src_dim0");
+        _expected_vars.push_back("src_dim1xdim2");
+        _expected_vars.push_back("src_offset_first_element");
+        _expected_vars.push_back("src_stride1");
+        _expected_vars.push_back("src_stride2");
+        _expected_vars.push_back("src_stride3");
+    }
+
+    bool run() override
+    {
+        // The status of this variable can change in VALIDATE_TEST()
+        bool all_tests_passed = true;
+
+        const TensorInfo info(dt, shape, TensorDataLayout::Nhwc, 1);
+
+        const size_t num_components = _components.size();
+
+        int32_t test_idx = 0;
+
+        CLTensorArgument arg(tensor_name, info, true /* return_dims_by_value */);
+        for(size_t i = 0; i < num_components; ++i)
+        {
+            arg.component(_components[i]);
+        }
+
+        const auto actual_vars = arg.components();
+
+        const size_t num_vars = _expected_vars.size();
+
+        VALIDATE_ON_MSG(actual_vars.size() == num_vars, "The number of variables must match the number of expected variables");
+
+        // Since the dimensions are passed by value, we expect only the variables for the strides
+        for(size_t i = 0; i < num_vars; ++i)
+        {
+            // Validate variable name
+            const std::string expected_var_name = _expected_vars[i];
+            const std::string actual_var_name   = actual_vars[i].str;
+            VALIDATE_TEST(actual_var_name.compare(expected_var_name) == 0, all_tests_passed, test_idx++);
+
+            // Validate data type
+            const DataType expected_var_type = DataType::Int32;
+            const DataType actual_var_type   = actual_vars[i].desc.dt;
+            VALIDATE_TEST(actual_var_type == expected_var_type, all_tests_passed, test_idx++);
+
+            // Validate data type length
+            const int32_t expected_var_len = 1;
+            const int32_t actual_var_len   = actual_vars[i].desc.len;
+            VALIDATE_TEST(actual_var_len == expected_var_len, all_tests_passed, test_idx++);
+        }
+        return all_tests_passed;
+    }
+
+    std::string name() override
+    {
+        return "CLTensorArgumentComponentsUsedPassByValueTrueDynamicDimTrueTest";
+    }
+
+private:
+    std::vector<TensorComponentType> _components{};
+    std::vector<std::string>         _expected_vars{};
+};
+} // namespace ckw
+
+#endif // CKW_TESTS_CLTENSORARGUMENTTEST_H
diff --git a/compute_kernel_writer/validation/tests/TensorBitMaskTest.hpp b/compute_kernel_writer/validation/tests/TensorBitMaskTest.h
index 1e7d003879..759d926d18 100644
--- a/compute_kernel_writer/validation/tests/TensorBitMaskTest.hpp
+++ b/compute_kernel_writer/validation/tests/TensorBitMaskTest.h
@@ -21,11 +21,13 @@
  * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
  * SOFTWARE.
  */
-#ifndef COMPUTE_KERNEL_WRITER_TESTS_TENSORBITMASK_HPP
-#define COMPUTE_KERNEL_WRITER_TESTS_TENSORBITMASK_HPP
+#ifndef CKW_TESTS_TENSORBITMASKTEST_H
+#define CKW_TESTS_TENSORBITMASKTEST_H
 
 #include "ckw/TensorInfo.h"
+#include "ckw/types/TensorComponentType.h"
 #include "common/Common.h"
+#include "src/types/TensorComponentType.h"
 
 #include <vector>
 
@@ -36,20 +38,20 @@ class TensorBitMaskTrueTest : public ITest
 public:
     TensorBitMaskTrueTest()
     {
-        _component.push_back(TensorComponent::Dim0);
-        _component.push_back(TensorComponent::Dim1);
-        _component.push_back(TensorComponent::Dim2);
-        _component.push_back(TensorComponent::Dim3);
-        _component.push_back(TensorComponent::Dim4);
-        _component.push_back(TensorComponent::Stride0);
-        _component.push_back(TensorComponent::Stride1);
-        _component.push_back(TensorComponent::Stride2);
-        _component.push_back(TensorComponent::Stride3);
-        _component.push_back(TensorComponent::Stride4);
-        _component.push_back(TensorComponent::Dim1xDim2);
-        _component.push_back(TensorComponent::Dim1xDim2xDim3);
-        _component.push_back(TensorComponent::Dim2xDim3);
-        _component.push_back(TensorComponent::OffsetFirstElement);
+        _component.push_back(TensorComponentType::Dim0);
+        _component.push_back(TensorComponentType::Dim1);
+        _component.push_back(TensorComponentType::Dim2);
+        _component.push_back(TensorComponentType::Dim3);
+        _component.push_back(TensorComponentType::Dim4);
+        _component.push_back(TensorComponentType::Stride0);
+        _component.push_back(TensorComponentType::Stride1);
+        _component.push_back(TensorComponentType::Stride2);
+        _component.push_back(TensorComponentType::Stride3);
+        _component.push_back(TensorComponentType::Stride4);
+        _component.push_back(TensorComponentType::Dim1xDim2);
+        _component.push_back(TensorComponentType::Dim1xDim2xDim3);
+        _component.push_back(TensorComponentType::Dim2xDim3);
+        _component.push_back(TensorComponentType::OffsetFirstElement);
 
         _bitmask.push_back(TensorComponentBitmask::Dimension);
         _bitmask.push_back(TensorComponentBitmask::Dimension);
@@ -77,7 +79,7 @@ public:
         const size_t num_tests = _component.size();
         for(size_t i = 0; i < num_tests; ++i)
         {
-            const TensorComponent        component = _component[i];
+            const TensorComponentType    component = _component[i];
             const TensorComponentBitmask bitmask   = _bitmask[i];
             const bool                   out       = static_cast<uint32_t>(component) & static_cast<uint32_t>(bitmask);
             VALIDATE_TEST(out == true, all_tests_passed, i);
@@ -91,7 +93,7 @@ public:
     }
 
 private:
-    std::vector<TensorComponent>        _component{};
+    std::vector<TensorComponentType>    _component{};
     std::vector<TensorComponentBitmask> _bitmask{};
 };
 
@@ -100,48 +102,48 @@ class TensorBitMaskFalseTest : public ITest
 public:
     TensorBitMaskFalseTest()
     {
-        _component.push_back(TensorComponent::Dim0);
-        _component.push_back(TensorComponent::Dim1);
-        _component.push_back(TensorComponent::Dim2);
-        _component.push_back(TensorComponent::Dim3);
-        _component.push_back(TensorComponent::Dim4);
-        _component.push_back(TensorComponent::Dim0);
-        _component.push_back(TensorComponent::Dim1);
-        _component.push_back(TensorComponent::Dim2);
-        _component.push_back(TensorComponent::Dim3);
-        _component.push_back(TensorComponent::Dim4);
-        _component.push_back(TensorComponent::Dim0);
-        _component.push_back(TensorComponent::Dim1);
-        _component.push_back(TensorComponent::Dim2);
-        _component.push_back(TensorComponent::Dim3);
-        _component.push_back(TensorComponent::Dim4);
-        _component.push_back(TensorComponent::Stride0);
-        _component.push_back(TensorComponent::Stride1);
-        _component.push_back(TensorComponent::Stride2);
-        _component.push_back(TensorComponent::Stride3);
-        _component.push_back(TensorComponent::Stride4);
-        _component.push_back(TensorComponent::Stride0);
-        _component.push_back(TensorComponent::Stride1);
-        _component.push_back(TensorComponent::Stride2);
-        _component.push_back(TensorComponent::Stride3);
-        _component.push_back(TensorComponent::Stride4);
-        _component.push_back(TensorComponent::Stride0);
-        _component.push_back(TensorComponent::Stride1);
-        _component.push_back(TensorComponent::Stride2);
-        _component.push_back(TensorComponent::Stride3);
-        _component.push_back(TensorComponent::Stride4);
-        _component.push_back(TensorComponent::Dim1xDim2);
-        _component.push_back(TensorComponent::Dim1xDim2xDim3);
-        _component.push_back(TensorComponent::Dim2xDim3);
-        _component.push_back(TensorComponent::Dim1xDim2);
-        _component.push_back(TensorComponent::Dim1xDim2xDim3);
-        _component.push_back(TensorComponent::Dim2xDim3);
-        _component.push_back(TensorComponent::Dim1xDim2);
-        _component.push_back(TensorComponent::Dim1xDim2xDim3);
-        _component.push_back(TensorComponent::Dim2xDim3);
-        _component.push_back(TensorComponent::OffsetFirstElement);
-        _component.push_back(TensorComponent::OffsetFirstElement);
-        _component.push_back(TensorComponent::OffsetFirstElement);
+        _component.push_back(TensorComponentType::Dim0);
+        _component.push_back(TensorComponentType::Dim1);
+        _component.push_back(TensorComponentType::Dim2);
+        _component.push_back(TensorComponentType::Dim3);
+        _component.push_back(TensorComponentType::Dim4);
+        _component.push_back(TensorComponentType::Dim0);
+        _component.push_back(TensorComponentType::Dim1);
+        _component.push_back(TensorComponentType::Dim2);
+        _component.push_back(TensorComponentType::Dim3);
+        _component.push_back(TensorComponentType::Dim4);
+        _component.push_back(TensorComponentType::Dim0);
+        _component.push_back(TensorComponentType::Dim1);
+        _component.push_back(TensorComponentType::Dim2);
+        _component.push_back(TensorComponentType::Dim3);
+        _component.push_back(TensorComponentType::Dim4);
+        _component.push_back(TensorComponentType::Stride0);
+        _component.push_back(TensorComponentType::Stride1);
+        _component.push_back(TensorComponentType::Stride2);
+        _component.push_back(TensorComponentType::Stride3);
+        _component.push_back(TensorComponentType::Stride4);
+        _component.push_back(TensorComponentType::Stride0);
+        _component.push_back(TensorComponentType::Stride1);
+        _component.push_back(TensorComponentType::Stride2);
+        _component.push_back(TensorComponentType::Stride3);
+        _component.push_back(TensorComponentType::Stride4);
+        _component.push_back(TensorComponentType::Stride0);
+        _component.push_back(TensorComponentType::Stride1);
+        _component.push_back(TensorComponentType::Stride2);
+        _component.push_back(TensorComponentType::Stride3);
+        _component.push_back(TensorComponentType::Stride4);
+        _component.push_back(TensorComponentType::Dim1xDim2);
+        _component.push_back(TensorComponentType::Dim1xDim2xDim3);
+        _component.push_back(TensorComponentType::Dim2xDim3);
+        _component.push_back(TensorComponentType::Dim1xDim2);
+        _component.push_back(TensorComponentType::Dim1xDim2xDim3);
+        _component.push_back(TensorComponentType::Dim2xDim3);
+        _component.push_back(TensorComponentType::Dim1xDim2);
+        _component.push_back(TensorComponentType::Dim1xDim2xDim3);
+        _component.push_back(TensorComponentType::Dim2xDim3);
+        _component.push_back(TensorComponentType::OffsetFirstElement);
+        _component.push_back(TensorComponentType::OffsetFirstElement);
+        _component.push_back(TensorComponentType::OffsetFirstElement);
 
         _bitmask.push_back(TensorComponentBitmask::Stride);
         _bitmask.push_back(TensorComponentBitmask::Stride);
@@ -197,7 +199,7 @@ public:
         const size_t num_tests = _component.size();
         for(size_t i = 0; i < num_tests; ++i)
         {
-            const TensorComponent        component = _component[i];
+            const TensorComponentType    component = _component[i];
             const TensorComponentBitmask bitmask   = _bitmask[i];
             const bool                   out       = static_cast<uint32_t>(component) & static_cast<uint32_t>(bitmask);
             VALIDATE_TEST(out == false, all_tests_passed, i);
@@ -211,9 +213,9 @@ public:
     }
 
 private:
-    std::vector<TensorComponent>        _component{};
+    std::vector<TensorComponentType>    _component{};
     std::vector<TensorComponentBitmask> _bitmask{};
 };
 } // namespace ckw
 
-#endif /* COMPUTE_KERNEL_WRITER_TESTS_TENSORBITMASK_HPP */
+#endif // CKW_TESTS_TENSORBITMASKTEST_H
diff --git a/compute_kernel_writer/validation/tests/UtilsTest.hpp b/compute_kernel_writer/validation/tests/UtilsTest.h
index db1c8fd4ae..a335a48f81 100644
--- a/compute_kernel_writer/validation/tests/UtilsTest.hpp
+++ b/compute_kernel_writer/validation/tests/UtilsTest.h
@@ -21,10 +21,11 @@
  * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
  * SOFTWARE.
  */
-#ifndef COMPUTE_KERNEL_WRITER_TESTS_UTILSTEST_HPP
-#define COMPUTE_KERNEL_WRITER_TESTS_UTILSTEST_HPP
+#ifndef CKW_TESTS_UTILSTEST_H
+#define CKW_TESTS_UTILSTEST_H
 
 #include "ckw/TensorInfo.h"
+#include "ckw/types/TensorDataLayout.h"
 #include "common/Common.h"
 #include "src/TensorUtils.h"
 
@@ -57,15 +58,15 @@ public:
         _component.push_back(TensorDataLayoutComponent::W);
         _component.push_back(TensorDataLayoutComponent::C);
 
-        _expected.push_back(TensorComponent::Dim3);
-        _expected.push_back(TensorComponent::Dim2);
-        _expected.push_back(TensorComponent::Dim1);
-        _expected.push_back(TensorComponent::Dim0);
-        _expected.push_back(TensorComponent::Dim4);
-        _expected.push_back(TensorComponent::Dim3);
-        _expected.push_back(TensorComponent::Dim2);
-        _expected.push_back(TensorComponent::Dim1);
-        _expected.push_back(TensorComponent::Dim0);
+        _expected.push_back(TensorComponentType::Dim3);
+        _expected.push_back(TensorComponentType::Dim2);
+        _expected.push_back(TensorComponentType::Dim1);
+        _expected.push_back(TensorComponentType::Dim0);
+        _expected.push_back(TensorComponentType::Dim4);
+        _expected.push_back(TensorComponentType::Dim3);
+        _expected.push_back(TensorComponentType::Dim2);
+        _expected.push_back(TensorComponentType::Dim1);
+        _expected.push_back(TensorComponentType::Dim0);
     }
 
     bool run() override
@@ -81,8 +82,8 @@ public:
         {
             const TensorDataLayout          layout    = _layout[i];
             const TensorDataLayoutComponent component = _component[i];
-            const TensorComponent           expected  = _expected[i];
-            const TensorComponent           out       = get_tensor_dimension(layout, component);
+            const TensorComponentType       expected  = _expected[i];
+            const TensorComponentType       out       = get_tensor_dimension(layout, component);
             VALIDATE_TEST(out == expected, all_tests_passed, i);
         }
         return all_tests_passed;
@@ -96,8 +97,8 @@ public:
 private:
     std::vector<TensorDataLayout>          _layout{};
     std::vector<TensorDataLayoutComponent> _component{};
-    std::vector<TensorComponent>           _expected{};
+    std::vector<TensorComponentType>       _expected{};
 };
 } // namespace ckw
 
-#endif /* COMPUTE_KERNEL_WRITER_TESTS_UTILSTEST_HPP */
+#endif // CKW_TESTS_UTILSTEST_H