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>
diff --git a/compute_kernel_writer/CMakeLists.txt b/compute_kernel_writer/CMakeLists.txt
index 9f372df..674bc53 100644
--- a/compute_kernel_writer/CMakeLists.txt
+++ b/compute_kernel_writer/CMakeLists.txt
@@ -131,6 +131,7 @@
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 @@
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 100bdc4..eaf3f10 100644
--- a/compute_kernel_writer/include/ckw/Error.h
+++ b/compute_kernel_writer/include/ckw/Error.h
@@ -87,7 +87,7 @@
#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.
@@ -101,18 +101,23 @@
} \
} while(false)
-/** If the condition is not met, throw an std::runtime_error.
+#else // COMPUTE_KERNEL_WRITER_ASSERTS_ENABLED
+
+#define CKW_ASSERT_MSG(cond, msg)
+
+#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)
-#else // COMPUTE_KERNEL_WRITER_ASSERTS_ENABLED
-
-#define CKW_ASSERT_MSG(cond, msg)
-#define CKW_ASSERT(cond)
-
-#endif // COMPUTE_KERNEL_WRITER_ASSERTS_ENABLED
+/** 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
diff --git a/compute_kernel_writer/include/ckw/TensorInfo.h b/compute_kernel_writer/include/ckw/TensorInfo.h
index 63d9f41..87cf7c1 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 0000000..7a5031d
--- /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 0000000..532b299
--- /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 0000000..5a2f17d
--- /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 0000000..40ad69f
--- /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 4970de7..2483609 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 @@
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 @@
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 84eca08..bb0af5c 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 @@
// 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 @@
*
* @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 @@
*
* @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 5a3d0fa..af8a8a0 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 @@
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 a9a84e2..d0ca488 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 @@
*/
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 0000000..ed1c5bd
--- /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 0000000..cd92484
--- /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 0000000..03f4f4f
--- /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 e4884fa..5d53a16 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 @@
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 @@
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 0000000..6db1384
--- /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
similarity index 64%
rename from compute_kernel_writer/validation/tests/TensorBitMaskTest.hpp
rename to compute_kernel_writer/validation/tests/TensorBitMaskTest.h
index 1e7d003..759d926 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 @@
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 @@
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 @@
}
private:
- std::vector<TensorComponent> _component{};
+ std::vector<TensorComponentType> _component{};
std::vector<TensorComponentBitmask> _bitmask{};
};
@@ -100,48 +102,48 @@
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 @@
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 @@
}
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
similarity index 80%
rename from compute_kernel_writer/validation/tests/UtilsTest.hpp
rename to compute_kernel_writer/validation/tests/UtilsTest.h
index db1c8fd..a335a48 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 @@
_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 @@
{
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 @@
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