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authorGeorgios Pinitas <georgios.pinitas@arm.com>2021-04-22 21:13:21 +0100
committerGeorgios Pinitas <georgios.pinitas@arm.com>2021-05-18 14:48:39 +0000
commit856f66e6c61b77d03f754cd0fa8439891f0e4aca (patch)
treef9379cd0853ac407109e54c3d53b385ceee066c2 /arm_compute/runtime/CL/functions
parent37f4b2ef1ea225a90ccb563fcb2c08f8fb0fb5d5 (diff)
downloadComputeLibrary-856f66e6c61b77d03f754cd0fa8439891f0e4aca.tar.gz
Port CLGEMM to memory injecting interface
Moves the following kernels: - CLGEMMMatrixMultiplyKernel - CLGEMMMatrixMultiplyNativeKernel - CLGEMMMatrixMultipluReshapedKernel - CLGEMMMatrixMultiplyReshapedOnlyRHSKernel Moves the following functions - CLGEMM Introduces facilities to easy handling of auxiliary temporary buffers under then new run interface. Such are: - CLAuxTensorHandler: That allows wrapping of workspace buffers memory to CLBuffer objects - Ability to inject TensorInfo to allocator without transferring ownership. This reduce the copy overhead if needed. Resolves: COMPMID-4188 Signed-off-by: Georgios Pinitas <georgios.pinitas@arm.com> Change-Id: I7055435d831b05b749b26302082e4ac45f26dfb0 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/5498 Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Michalis Spyrou <michalis.spyrou@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'arm_compute/runtime/CL/functions')
-rw-r--r--arm_compute/runtime/CL/functions/CLFullyConnectedLayer.h2
-rw-r--r--arm_compute/runtime/CL/functions/CLGEMM.h145
-rw-r--r--arm_compute/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.h10
-rw-r--r--arm_compute/runtime/CL/functions/CLLogicalAnd.h62
-rw-r--r--arm_compute/runtime/CL/functions/CLLogicalOr.h62
-rw-r--r--arm_compute/runtime/CL/functions/CLSlice.h78
6 files changed, 128 insertions, 231 deletions
diff --git a/arm_compute/runtime/CL/functions/CLFullyConnectedLayer.h b/arm_compute/runtime/CL/functions/CLFullyConnectedLayer.h
index eec01bcebe..075c5d1f45 100644
--- a/arm_compute/runtime/CL/functions/CLFullyConnectedLayer.h
+++ b/arm_compute/runtime/CL/functions/CLFullyConnectedLayer.h
@@ -98,7 +98,7 @@ private:
*
* -# @ref CLIm2ColKernel (called when the input comes from a convolutional layer)
* -# @ref CLTranspose (if @p are_weights_reshaped is set to false and transpose_weights is set to true ) (called once)
- * -# @ref CLGEMMMatrixMultiplyKernel or @ref CLGEMMLowpMatrixMultiplyCore (if quantized asymmetric)
+ * -# @ref opencl::kernels::ClGemmMatrixMultiplyKernel or @ref CLGEMMLowpMatrixMultiplyCore (if quantized asymmetric)
*
* @note The fully connected layer accepts "weights" tensors only with 2 dimensions.
*/
diff --git a/arm_compute/runtime/CL/functions/CLGEMM.h b/arm_compute/runtime/CL/functions/CLGEMM.h
index 1e2ae7be64..38a07ef9fb 100644
--- a/arm_compute/runtime/CL/functions/CLGEMM.h
+++ b/arm_compute/runtime/CL/functions/CLGEMM.h
@@ -35,76 +35,12 @@
namespace arm_compute
{
+// Forward declarations
class CLCompileContext;
-class CLGEMMReshapeRHSMatrixKernel;
-class CLGEMMMatrixMultiplyKernel;
-class CLGEMMMatrixMultiplyReshapedKernel;
-class CLGEMMMatrixMultiplyReshapedOnlyRHSKernel;
-class CLGEMMReshapeLHSMatrixKernel;
class ICLTensor;
class ITensorInfo;
-namespace weights_transformations
-{
-/** Basic function to manage the reshape weights generated from @ref CLGEMMReshapeRHSMatrixKernel */
-class CLGEMMReshapeRHSMatrixKernelManaged : public ITransformWeights
-{
-public:
- /** Default constructor */
- CLGEMMReshapeRHSMatrixKernelManaged();
- /** Prevent instances of this class from being copied (As this class contains pointers) */
- CLGEMMReshapeRHSMatrixKernelManaged(const CLGEMMReshapeRHSMatrixKernelManaged &) = delete;
- /** Default move constructor */
- CLGEMMReshapeRHSMatrixKernelManaged(CLGEMMReshapeRHSMatrixKernelManaged &&) = default;
- /** Prevent instances of this class from being copied (As this class contains pointers) */
- CLGEMMReshapeRHSMatrixKernelManaged &operator=(const CLGEMMReshapeRHSMatrixKernelManaged &) = delete;
- /** Default move assignment operator */
- CLGEMMReshapeRHSMatrixKernelManaged &operator=(CLGEMMReshapeRHSMatrixKernelManaged &&) = default;
- /** Default desctructor */
- ~CLGEMMReshapeRHSMatrixKernelManaged();
- //Inherited method override
- void run() override;
-
- //Inherited method override
- void release() override;
-
- //Inherited method override
- ICLTensor *get_weights() override;
-
- //Inherited method override
- uint32_t uid() override;
-
- /** Configures the @ref CLGEMMReshapeRHSMatrixKernel kernel
- *
- * @param[in] input Input tensor. Data types supported: All
- * @param[in] info RHS matrix information to be used for reshaping.
- */
- void configure(const ICLTensor *input, GEMMRHSMatrixInfo info);
-
- /** Configures the @ref CLGEMMReshapeRHSMatrixKernel kernel
- *
- * @param[in] compile_context The compile context to be used.
- * @param[in] input Input tensor. Data types supported: All
- * @param[in] info RHS matrix information to be used for reshaping.
- */
- void configure(const CLCompileContext &compile_context, const ICLTensor *input, GEMMRHSMatrixInfo info);
-
-private:
- static constexpr uint32_t _uid{ 0x15 };
- CLTensor _output{};
- std::unique_ptr<CLGEMMReshapeRHSMatrixKernel> _kernel;
-};
-} // namespace weights_transformations
-
-/** Basic function to execute GEMM on OpenCL. This function calls the following OpenCL kernels:
- *
- * -# @ref CLGEMMReshapeLHSMatrixKernel (only if the RESHAPED_V1 is selected by the heuristic model)
- * -# @ref CLGEMMReshapeRHSMatrixKernel (only if either the RESHAPED_V1 or RESHAPED_ONLY_RHS is selected by the select_gemm_kernel method())
- * -# @ref CLGEMMMatrixMultiplyKernel (only if either the NATIVE or RESHAPED_V1 is selected by the select_gemm_kernel method())
- * -# @ref CLGEMMMatrixMultiplyReshapedKernel (only if RESHAPED_V1 is selected by the select_gemm_kernel method())
- * -# @ref CLGEMMMatrixMultiplyReshapedOnlyRHSKernel (only if RESHAPED_ONLY_RHS is selected by the select_gemm_kernel method())
- *
- */
+/** Basic function to execute GEMM on OpenCL */
class CLGEMM : public IFunction
{
public:
@@ -114,16 +50,16 @@ public:
* @param[in] weights_manager (Optional) Weights manager.
*/
CLGEMM(std::shared_ptr<IMemoryManager> memory_manager = nullptr, IWeightsManager *weights_manager = nullptr);
+ /** Default destructor */
+ ~CLGEMM();
/** Prevent instances of this class from being copied (As this class contains pointers) */
CLGEMM(const CLGEMM &) = delete;
/** Default move constructor */
- CLGEMM(CLGEMM &&) = default;
+ CLGEMM(CLGEMM &&);
/** Prevent instances of this class from being copied (As this class contains pointers) */
CLGEMM &operator=(const CLGEMM &) = delete;
/** Default move assignment operator */
- CLGEMM &operator=(CLGEMM &&) = default;
- /** Default destructor */
- ~CLGEMM();
+ CLGEMM &operator=(CLGEMM &&);
/** Initialise the kernel's inputs and output
*
* Valid data layouts:
@@ -141,25 +77,6 @@ public:
*
* @note Whilst the first input tensor can be a vector, the second input tensor must be at least a matrix
*
- * @param[in] a First input tensor (Matrix or Vector A). Data types supported: F16/F32
- * @param[in] b Second input tensor (Matrix B). Data type supported: same as @p a.
- * @param[in] c Third input tensor (Matrix C). It can be a nullptr if just the multiplication between @p a and @p b is needed. Data type supported: same as @p a.
- * @param[out] output Output tensor. Data type supported: same as @p a
- * @param[in] alpha Weight of the matrix product
- * @param[in] beta Weight of matrix C
- * @param[in] gemm_info (Optional) Specifies if the matrix A and/or matrix B have been reshaped and
- * if the reshape of matrix B should happen only for the first run. GEMMInfo also contains information about the reshaping
- * in case matrix A and matrix B have been already transformed.
- */
- void configure(const ICLTensor *a, const ICLTensor *b, const ICLTensor *c, ICLTensor *output, float alpha, float beta, const GEMMInfo &gemm_info = GEMMInfo());
- /** Initialise the kernel's inputs and output
- *
- * @note GEMM: General Matrix Multiply - [alpha * A * B + beta * C].
- *
- * @note All tensors must have the same data type.
- *
- * @note Whilst the first input tensor can be a vector, the second input tensor must be at least a matrix
- *
* @param[in] compile_context The compile context to be used.
* @param[in] a First input tensor (Matrix or Vector A). Data types supported: F16/F32
* @param[in] b Second input tensor (Matrix B). Data type supported: same as @p a.
@@ -168,20 +85,20 @@ public:
* @param[in] alpha Weight of the matrix product
* @param[in] beta Weight of matrix C
* @param[in] gemm_info (Optional) Specifies if the matrix A and/or matrix B have been reshaped and
- * if the reshape of matrix B should happen only for the first run. GEMMInfo also contains information about the reshaping
- * in case matrix A and matrix B have been already transformed.
+ * if the reshape of matrix B should happen only for the first run. GEMMInfo also contains information about the reshaping
+ * in case matrix A and matrix B have been already transformed.
*/
void configure(const CLCompileContext &compile_context, const ICLTensor *a, const ICLTensor *b, const ICLTensor *c, ICLTensor *output, float alpha, float beta, const GEMMInfo &gemm_info = GEMMInfo());
+
+ /** Initialise the kernel's inputs and output
+ *
+ * Similar to @ref CLGEMM::configure()
+ */
+ void configure(const ICLTensor *a, const ICLTensor *b, const ICLTensor *c, ICLTensor *output, float alpha, float beta, const GEMMInfo &gemm_info = GEMMInfo());
+
/** Static function to check if given info will lead to a valid configuration of @ref CLGEMM.
*
- * @param[in] a First input tensor info (Matrix or Vector A). Data types supported: F16/F32
- * @param[in] b Second input tensor info (Matrix B). Data type supported: same as @p a.
- * @param[in] c Third input tensor info (Matrix C). It can be a nullptr if just the multiplication between @p a and @p b is needed. Data type supported: same as @p a.
- * @param[in] output Output tensor info. Data type supported: same as @p a
- * @param[in] alpha Weight of the matrix product
- * @param[in] beta Weight of matrix C
- * @param[in] gemm_info (Optional) Specifies if the matrix A and/or matrix B have been reshaped and
- * if the reshape of matrix B should happen only for the first run
+ * Similar to @ref CLGEMM::configure()
*
* @return a status
*/
@@ -192,34 +109,8 @@ public:
void prepare() override;
private:
- void configure_native_v1(const CLCompileContext &compile_context, const ICLTensor *a, const ICLTensor *b, const ICLTensor *c, ICLTensor *output, float alpha, float beta, const GEMMInfo &gemm_info);
- void configure_reshaped_v1(const CLCompileContext &compile_context, const ICLTensor *a, const ICLTensor *b, const ICLTensor *c, ICLTensor *output, float alpha, float beta, const GEMMInfo &gemm_info);
- void configure_reshaped_v2(const CLCompileContext &compile_context, const ICLTensor *a, const ICLTensor *b, const ICLTensor *c, ICLTensor *output, float alpha, float beta, const GEMMInfo &gemm_info);
- void configure_reshaped_only_rhs(const CLCompileContext &compile_context, const ICLTensor *a, const ICLTensor *b, const ICLTensor *c, ICLTensor *output, float alpha, float beta,
- const GEMMInfo &gemm_info);
-
- static Status validate_native_v1(const ITensorInfo *a, const ITensorInfo *b, const ITensorInfo *c, const ITensorInfo *output, float alpha, float beta, const GEMMInfo &gemm_info);
- static Status validate_reshaped_v1(const ITensorInfo *a, const ITensorInfo *b, const ITensorInfo *c, const ITensorInfo *output, float alpha, float beta, const GEMMInfo &gemm_info);
- static Status validate_reshaped(const ITensorInfo *a, const ITensorInfo *b, const ITensorInfo *c, const ITensorInfo *output, float alpha, float beta, const GEMMInfo &gemm_info);
- static Status validate_reshaped_only_rhs(const ITensorInfo *a, const ITensorInfo *b, const ITensorInfo *c, const ITensorInfo *output, float alpha, float beta, const GEMMInfo &gemm_info);
-
- MemoryGroup _memory_group;
- IWeightsManager *_weights_manager;
- std::unique_ptr<CLGEMMMatrixMultiplyKernel> _mm_kernel;
- std::unique_ptr<CLGEMMReshapeLHSMatrixKernel> _reshape_lhs_kernel;
- std::unique_ptr<CLGEMMReshapeRHSMatrixKernel> _reshape_rhs_kernel;
- std::unique_ptr<weights_transformations::CLGEMMReshapeRHSMatrixKernelManaged> _reshape_rhs_kernel_managed;
- std::unique_ptr<CLGEMMMatrixMultiplyReshapedKernel> _mm_reshaped_kernel;
- std::unique_ptr<CLGEMMMatrixMultiplyReshapedOnlyRHSKernel> _mm_reshaped_only_rhs_kernel;
- std::unique_ptr<CLGEMMMatrixMultiplyReshapedOnlyRHSKernel> _mm_reshaped_only_rhs_fallback_kernel;
- CLTensor _tmp_a;
- CLTensor _tmp_b;
- const ICLTensor *_original_b;
- const ICLTensor *_lhs;
- ICLTensor *_dst;
- bool _reshape_b_only_on_first_run;
- bool _is_prepared;
- CLGEMMKernelType _gemm_kernel_type;
+ struct Impl;
+ std::unique_ptr<Impl> _impl;
};
} // namespace arm_compute
diff --git a/arm_compute/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.h b/arm_compute/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.h
index e7f4cb9d01..e5de45c34f 100644
--- a/arm_compute/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.h
+++ b/arm_compute/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.h
@@ -41,7 +41,13 @@ class CLGEMMLowpOffsetContributionKernel;
class CLGEMMLowpOffsetContributionOutputStageKernel;
class CLGEMMLowpMatrixAReductionKernel;
class CLGEMMLowpMatrixBReductionKernel;
-class CLGEMMReshapeRHSMatrixKernel;
+namespace opencl
+{
+namespace kernels
+{
+class ClGemmReshapeRhsMatrixKernel;
+} // namespace kernels
+} // namespace opencl
/** Basic function to execute GEMMLowpMatrixMultiplyCore on OpenCL. */
class CLGEMMLowpMatrixMultiplyCore : public IFunction
@@ -140,7 +146,7 @@ private:
std::unique_ptr<CLDepthConvertLayerKernel> _weights_to_qasymm8;
std::unique_ptr<CLGEMMLowpMatrixMultiplyNativeKernel> _mm_native_kernel;
std::unique_ptr<CLGEMMLowpMatrixMultiplyReshapedOnlyRHSKernel> _mm_reshaped_only_rhs_kernel;
- std::unique_ptr<CLGEMMReshapeRHSMatrixKernel> _mtx_b_reshape_kernel;
+ std::unique_ptr<opencl::kernels::ClGemmReshapeRhsMatrixKernel> _mtx_b_reshape_kernel;
std::unique_ptr<CLGEMMLowpMatrixAReductionKernel> _mtx_a_reduction_kernel;
std::unique_ptr<CLGEMMLowpMatrixBReductionKernel> _mtx_b_reduction_kernel;
std::unique_ptr<CLGEMMLowpOffsetContributionKernel> _offset_contribution_kernel;
diff --git a/arm_compute/runtime/CL/functions/CLLogicalAnd.h b/arm_compute/runtime/CL/functions/CLLogicalAnd.h
index 61a15816eb..e3061e1dc3 100644
--- a/arm_compute/runtime/CL/functions/CLLogicalAnd.h
+++ b/arm_compute/runtime/CL/functions/CLLogicalAnd.h
@@ -34,37 +34,6 @@ class CLCompileContext;
class ICLTensor;
class ITensorInfo;
-namespace experimental
-{
-class CLLogicalAnd : public ICLOperator
-{
-public:
- /** Default Constructor */
- CLLogicalAnd() = default;
- /** Initialise the kernel's inputs, output and conversion policy.
- *
- * @param[in] compile_context The compile context to be used.
- * @param[in, out] input1 First tensor input. Data types supported: U8.
- * The input tensor is [in, out] because its TensorInfo might be modified inside the kernel in case of broadcasting of dimension 0.
- * @param[in, out] input2 Second tensor input. Data types supported: same as @p input1.
- * The input tensor is [in, out] because its TensorInfo might be modified inside the kernel in case of broadcasting of dimension 0.
- * @param[out] output Output tensor. Data types supported: same as @p input1.
- */
- void configure(const CLCompileContext &compile_context, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output);
- /** Static function to check if given info will lead to a valid configuration of @ref arm_compute::opencl::kernels::ClLogicalBinaryKernel
- *
- * @param[in] input1 First tensor input info. Data types supported: U8.
- * @param[in] input2 Second tensor input info. Data types supported: same as @p input1.
- * @param[in] output Output tensor info. Data types supported: same as @p input1.
- *
- * @return a status
- */
- static Status validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output);
- // Inherited methods overridden:
- void run(ITensorPack &tensors) override;
-};
-} // namespace experimental
-
/** Basic function to run @ref arm_compute::opencl::kernels::ClLogicalBinaryKernel.
*
* @note The tensor data type for the inputs must be U8.
@@ -125,5 +94,36 @@ private:
struct Impl;
std::unique_ptr<Impl> _impl;
};
+
+namespace experimental
+{
+class CLLogicalAnd : public ICLOperator
+{
+public:
+ /** Default Constructor */
+ CLLogicalAnd() = default;
+ /** Initialise the kernel's inputs, output and conversion policy.
+ *
+ * @param[in] compile_context The compile context to be used.
+ * @param[in, out] input1 First tensor input. Data types supported: U8.
+ * The input tensor is [in, out] because its TensorInfo might be modified inside the kernel in case of broadcasting of dimension 0.
+ * @param[in, out] input2 Second tensor input. Data types supported: same as @p input1.
+ * The input tensor is [in, out] because its TensorInfo might be modified inside the kernel in case of broadcasting of dimension 0.
+ * @param[out] output Output tensor. Data types supported: same as @p input1.
+ */
+ void configure(const CLCompileContext &compile_context, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output);
+ /** Static function to check if given info will lead to a valid configuration of @ref arm_compute::opencl::kernels::ClLogicalBinaryKernel
+ *
+ * @param[in] input1 First tensor input info. Data types supported: U8.
+ * @param[in] input2 Second tensor input info. Data types supported: same as @p input1.
+ * @param[in] output Output tensor info. Data types supported: same as @p input1.
+ *
+ * @return a status
+ */
+ static Status validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output);
+ // Inherited methods overridden:
+ void run(ITensorPack &tensors) override;
+};
+} // namespace experimental
} // namespace arm_compute
#endif /* ARM_COMPUTE_CLLOGICALAND_H */
diff --git a/arm_compute/runtime/CL/functions/CLLogicalOr.h b/arm_compute/runtime/CL/functions/CLLogicalOr.h
index b9ffb4a449..893c22f721 100644
--- a/arm_compute/runtime/CL/functions/CLLogicalOr.h
+++ b/arm_compute/runtime/CL/functions/CLLogicalOr.h
@@ -34,37 +34,6 @@ class CLCompileContext;
class ICLTensor;
class ITensorInfo;
-namespace experimental
-{
-class CLLogicalOr : public ICLOperator
-{
-public:
- /** Default Constructor */
- CLLogicalOr() = default;
- /** Initialise the kernel's inputs, output and conversion policy.
- *
- * @param[in] compile_context The compile context to be used.
- * @param[in, out] input1 First tensor input. Data types supported: U8.
- * The input tensor is [in, out] because its TensorInfo might be modified inside the kernel in case of broadcasting of dimension 0.
- * @param[in, out] input2 Second tensor input. Data types supported: same as @p input1.
- * The input tensor is [in, out] because its TensorInfo might be modified inside the kernel in case of broadcasting of dimension 0.
- * @param[out] output Output tensor. Data types supported: same as @p input1.
- */
- void configure(const CLCompileContext &compile_context, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output);
- /** Static function to check if given info will lead to a valid configuration of @ref arm_compute::opencl::kernels::ClLogicalBinaryKernel
- *
- * @param[in] input1 First tensor input info. Data types supported: U8.
- * @param[in] input2 Second tensor input info. Data types supported: same as @p input1.
- * @param[in] output Output tensor info. Data types supported: same as @p input1.
- *
- * @return a status
- */
- static Status validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output);
- // Inherited methods overridden:
- void run(ITensorPack &tensors) override;
-};
-} // namespace experimental
-
/** Basic function to run @ref arm_compute::opencl::kernels::ClLogicalBinaryKernel.
*
* @note The tensor data type for the inputs must be U8.
@@ -125,5 +94,36 @@ private:
struct Impl;
std::unique_ptr<Impl> _impl;
};
+
+namespace experimental
+{
+class CLLogicalOr : public ICLOperator
+{
+public:
+ /** Default Constructor */
+ CLLogicalOr() = default;
+ /** Initialise the kernel's inputs, output and conversion policy.
+ *
+ * @param[in] compile_context The compile context to be used.
+ * @param[in, out] input1 First tensor input. Data types supported: U8.
+ * The input tensor is [in, out] because its TensorInfo might be modified inside the kernel in case of broadcasting of dimension 0.
+ * @param[in, out] input2 Second tensor input. Data types supported: same as @p input1.
+ * The input tensor is [in, out] because its TensorInfo might be modified inside the kernel in case of broadcasting of dimension 0.
+ * @param[out] output Output tensor. Data types supported: same as @p input1.
+ */
+ void configure(const CLCompileContext &compile_context, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output);
+ /** Static function to check if given info will lead to a valid configuration of @ref arm_compute::opencl::kernels::ClLogicalBinaryKernel
+ *
+ * @param[in] input1 First tensor input info. Data types supported: U8.
+ * @param[in] input2 Second tensor input info. Data types supported: same as @p input1.
+ * @param[in] output Output tensor info. Data types supported: same as @p input1.
+ *
+ * @return a status
+ */
+ static Status validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output);
+ // Inherited methods overridden:
+ void run(ITensorPack &tensors) override;
+};
+} // namespace experimental
} // namespace arm_compute
#endif /* ARM_COMPUTE_CLLOGICALOR_H */
diff --git a/arm_compute/runtime/CL/functions/CLSlice.h b/arm_compute/runtime/CL/functions/CLSlice.h
index 7a7689c528..297bcd86fe 100644
--- a/arm_compute/runtime/CL/functions/CLSlice.h
+++ b/arm_compute/runtime/CL/functions/CLSlice.h
@@ -34,45 +34,6 @@ class ICLTensor;
class CLCompileContext;
class ITensorInfo;
-namespace experimental
-{
-/** Basic function to perform tensor slicing */
-class CLSlice : public ICLOperator
-{
-public:
- /** Configure kernel
- *
- * @note Supported tensor rank: up to 4
- * @note Start indices must be non-negative. 0 <= starts[i]
- * @note End coordinates can be negative, which represents the number of elements before the end of that dimension.
- * @note End indices are not inclusive unless negative.
- *
- * @param[in] compile_context The compile context to be used.
- * @param[in] input Source tensor info. Data type supported: All.
- * @param[out] output Destination tensor info. Data type supported: Same as @p input
- * @param[in] starts The starts of the dimensions of the input tensor to be sliced. The length must be of rank(input).
- * @param[in] ends The ends of the dimensions of the input tensor to be sliced. The length must be of rank(input).
- */
- void configure(const CLCompileContext &compile_context, const ITensorInfo *input, ITensorInfo *output, const Coordinates &starts, const Coordinates &ends);
-
- /** Static function to check if given info will lead to a valid configuration of @ref CLSlice
- *
- * @note Supported tensor rank: up to 4
- * @note Start indices must be non-negative. 0 <= starts[i]
- * @note End coordinates can be negative, which represents the number of elements before the end of that dimension.
- * @note End indices are not inclusive unless negative.
- *
- * @param[in] input Source tensor info. Data type supported: All
- * @param[in] output Destination tensor info. Data type supported: Same as @p input
- * @param[in] starts The starts of the dimensions of the input tensor to be sliced. The length must be of rank(input).
- * @param[in] ends The ends of the dimensions of the input tensor to be sliced. The length must be of rank(input).
- *
- * @return A status
- */
- static Status validate(const ITensorInfo *input, const ITensorInfo *output, const Coordinates &starts, const Coordinates &ends);
-};
-} // namespace experimental
-
/** Basic function to perform tensor slicing */
class CLSlice : public IFunction
{
@@ -148,5 +109,44 @@ private:
struct Impl;
std::unique_ptr<Impl> _impl;
};
+
+namespace experimental
+{
+/** Basic function to perform tensor slicing */
+class CLSlice : public ICLOperator
+{
+public:
+ /** Configure kernel
+ *
+ * @note Supported tensor rank: up to 4
+ * @note Start indices must be non-negative. 0 <= starts[i]
+ * @note End coordinates can be negative, which represents the number of elements before the end of that dimension.
+ * @note End indices are not inclusive unless negative.
+ *
+ * @param[in] compile_context The compile context to be used.
+ * @param[in] input Source tensor info. Data type supported: All.
+ * @param[out] output Destination tensor info. Data type supported: Same as @p input
+ * @param[in] starts The starts of the dimensions of the input tensor to be sliced. The length must be of rank(input).
+ * @param[in] ends The ends of the dimensions of the input tensor to be sliced. The length must be of rank(input).
+ */
+ void configure(const CLCompileContext &compile_context, const ITensorInfo *input, ITensorInfo *output, const Coordinates &starts, const Coordinates &ends);
+
+ /** Static function to check if given info will lead to a valid configuration of @ref CLSlice
+ *
+ * @note Supported tensor rank: up to 4
+ * @note Start indices must be non-negative. 0 <= starts[i]
+ * @note End coordinates can be negative, which represents the number of elements before the end of that dimension.
+ * @note End indices are not inclusive unless negative.
+ *
+ * @param[in] input Source tensor info. Data type supported: All
+ * @param[in] output Destination tensor info. Data type supported: Same as @p input
+ * @param[in] starts The starts of the dimensions of the input tensor to be sliced. The length must be of rank(input).
+ * @param[in] ends The ends of the dimensions of the input tensor to be sliced. The length must be of rank(input).
+ *
+ * @return A status
+ */
+ static Status validate(const ITensorInfo *input, const ITensorInfo *output, const Coordinates &starts, const Coordinates &ends);
+};
+} // namespace experimental
} // namespace arm_compute
#endif /* ARM_COMPUTE_CL_SLICE_H */