Make CLArithmeticAddition kernel and function state-less
Resolves COMPMID-4006
Change-Id: Iddc32b0b250142aac9a4a7b9dc0eef462d196025
Signed-off-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/4913
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Sang-Hoon Park <sang-hoon.park@arm.com>
diff --git a/Android.bp b/Android.bp
index 8a596cd..6937ab5 100644
--- a/Android.bp
+++ b/Android.bp
@@ -110,7 +110,6 @@
"src/core/CL/kernels/CLDilateKernel.cpp",
"src/core/CL/kernels/CLDirectConvolutionLayerKernel.cpp",
"src/core/CL/kernels/CLElementWiseUnaryLayerKernel.cpp",
- "src/core/CL/kernels/CLElementwiseOperationKernel.cpp",
"src/core/CL/kernels/CLErodeKernel.cpp",
"src/core/CL/kernels/CLFFTDigitReverseKernel.cpp",
"src/core/CL/kernels/CLFFTRadixStageKernel.cpp",
@@ -441,6 +440,7 @@
"src/core/gpu/cl/kernels/ClActivationKernel.cpp",
"src/core/gpu/cl/kernels/ClBatchConcatenateKernel.cpp",
"src/core/gpu/cl/kernels/ClDepthConcatenateKernel.cpp",
+ "src/core/gpu/cl/kernels/ClElementwiseKernel.cpp",
"src/core/gpu/cl/kernels/ClFloorKernel.cpp",
"src/core/gpu/cl/kernels/ClHeightConcatenateKernel.cpp",
"src/core/gpu/cl/kernels/ClWidthConcatenate2TensorsKernel.cpp",
@@ -795,6 +795,7 @@
"src/runtime/cpu/operators/CpuReshape.cpp",
"src/runtime/cpu/operators/CpuSub.cpp",
"src/runtime/gpu/cl/operators/ClActivation.cpp",
+ "src/runtime/gpu/cl/operators/ClAdd.cpp",
"src/runtime/gpu/cl/operators/ClConcatenate.cpp",
"src/runtime/gpu/cl/operators/ClFloor.cpp",
"utils/CommonGraphOptions.cpp",
diff --git a/arm_compute/runtime/CL/functions/CLElementwiseOperations.h b/arm_compute/runtime/CL/functions/CLElementwiseOperations.h
index 55c5fb3..4dd4912 100644
--- a/arm_compute/runtime/CL/functions/CLElementwiseOperations.h
+++ b/arm_compute/runtime/CL/functions/CLElementwiseOperations.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2018-2020 Arm Limited.
+ * Copyright (c) 2018-2021 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -35,74 +35,7 @@
namespace experimental
{
-/** Basic function to run @ref CLSaturatedArithmeticOperationKernel for addition
- *
- * @note The tensor data type for the inputs must be U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/S32/F16/F32.
- * @note The function performs an arithmetic addition between two tensors.
- */
-class CLArithmeticAddition : public ICLOperator
-{
-public:
- /** Default Constructor */
- CLArithmeticAddition();
- /** Initialise the kernel's inputs, output and conversion policy.
- *
- * Valid configurations (Input1,Input2) -> Output :
- *
- * - (U8,U8) -> U8
- * - (U8,U8) -> S16
- * - (S16,U8) -> S16
- * - (U8,S16) -> S16
- * - (S16,S16) -> S16
- * - (S32,S32) -> S32
- * - (F16,F16) -> F16
- * - (F32,F32) -> F32
- * - (QASYMM8,QASYMM8) -> QASYMM8
- * - (QASYMM8_SIGNED,QASYMM8_SIGNED) -> QASYMM8_SIGNED
- * - (QSYMM16,QSYMM16) -> QSYMM16
- *
- * @param[in] compile_context The compile context to be used.
- * @param[in, out] input1 First tensor input. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/S32/F16/F32.
- * 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: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/S32/F16/F32.
- * 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: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/S32/F16/F32.
- * @param[in] policy Policy to use to handle overflow.
- * @param[in] act_info (Optional) Activation layer information in case of a fused activation.
- */
- void configure(const CLCompileContext &compile_context, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output, ConvertPolicy policy,
- const ActivationLayerInfo &act_info = ActivationLayerInfo());
- /** Static function to check if given info will lead to a valid configuration of @ref CLSaturatedArithmeticOperationKernel for addition
- *
- * Valid configurations (Input1,Input2) -> Output :
- *
- * - (U8,U8) -> U8
- * - (U8,U8) -> S16
- * - (S16,U8) -> S16
- * - (U8,S16) -> S16
- * - (S16,S16) -> S16
- * - (S32,S32) -> S32
- * - (F16,F16) -> F16
- * - (F32,F32) -> F32
- * - (QASYMM8,QASYMM8) -> QASYMM8
- * - (QASYMM8_SIGNED,QASYMM8_SIGNED) -> QASYMM8_SIGNED
- * - (QSYMM16,QSYMM16) -> QSYMM16
- *
- * @param[in] input1 First tensor input info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/S32/F16/F32.
- * @param[in] input2 Second tensor input info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/S32/F16/F32.
- * @param[in] output Output tensor info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/S32/F16/F32.
- * @param[in] policy Policy to use to handle overflow.
- * @param[in] act_info (Optional) Activation layer information in case of a fused activation.
- *
- * @return a status
- */
- static Status validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, ConvertPolicy policy, const ActivationLayerInfo &act_info = ActivationLayerInfo());
-
- // Inherited methods overridden:
- void run(ITensorPack &tensors) override;
-};
-
-/** Basic function to run @ref CLSaturatedArithmeticOperationKernel for subtraction
+/** Basic function to run @ref arm_compute::opencl::kernels::ClSaturatedArithmeticKernel for subtraction
*
* @note The tensor data type for the inputs must be U8/QASYMM8/QASYMM8_SIGNED/S16/S32/F16/F32.
* @note The function performs an arithmetic subtraction between two tensors.
@@ -139,7 +72,7 @@
*/
void configure(const CLCompileContext &compile_context, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output, ConvertPolicy policy,
const ActivationLayerInfo &act_info = ActivationLayerInfo());
- /** Static function to check if given info will lead to a valid configuration of @ref CLSaturatedArithmeticOperationKernel for subtraction
+ /** Static function to check if given info will lead to a valid configuration of @ref arm_compute::opencl::kernels::ClSaturatedArithmeticKernel for subtraction
*
* Valid configurations (Input1,Input2) -> Output :
*
@@ -169,7 +102,7 @@
void run(ITensorPack &tensors) override;
};
-/** Basic function to run @ref CLSaturatedArithmeticOperationKernel for division
+/** Basic function to run @ref arm_compute::opencl::kernels::ClSaturatedArithmeticKernel for division
*
* @note The tensor data type for the inputs must be F16/F32.
* @note The function performs an arithmetic division between two tensors.
@@ -205,7 +138,7 @@
void run(ITensorPack &tensors) override;
};
-/** Basic function to run @ref CLArithmeticOperationKernel for max
+/** Basic function to run @ref arm_compute::opencl::kernels::ClArithmeticKernel for max
*
* @note The tensor data type for the inputs must be U8/QASYMM8/S16/QSYMM16/S32/U32/F16/F32.
* @note The function performs a max operation between two tensors.
@@ -226,7 +159,7 @@
* @param[in] act_info (Optional) Activation layer information in case of a fused activation.
*/
void configure(const CLCompileContext &compile_context, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output, const ActivationLayerInfo &act_info = ActivationLayerInfo());
- /** Static function to check if given info will lead to a valid configuration of @ref CLArithmeticOperationKernel for max
+ /** Static function to check if given info will lead to a valid configuration of @ref arm_compute::opencl::kernels::ClArithmeticKernel for max
*
* @param[in] input1 First tensor input info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/S32/U32/F16/F32.
* @param[in] input2 Second tensor input info. Data types supported: same as @p input1.
@@ -241,7 +174,7 @@
void run(ITensorPack &tensors) override;
};
-/** Basic function to run @ref CLArithmeticOperationKernel for min
+/** Basic function to run @ref arm_compute::opencl::kernels::ClArithmeticKernel for min
*
* @note The tensor data type for the inputs must be U8/QASYMM8/S16/QSYMM16/S32/U32/F16/F32.
* @note The function performs a max operation between two tensors.
@@ -262,7 +195,7 @@
* @param[in] act_info (Optional) Activation layer information in case of a fused activation.
*/
void configure(const CLCompileContext &compile_context, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output, const ActivationLayerInfo &act_info = ActivationLayerInfo());
- /** Static function to check if given info will lead to a valid configuration of @ref CLArithmeticOperationKernel for min
+ /** Static function to check if given info will lead to a valid configuration of @ref arm_compute::opencl::kernels::ClArithmeticKernel for min
*
* @param[in] input1 First tensor input info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/S32/U32/F16/F32.
* @param[in] input2 Second tensor input info. Data types supported: same as @p input1.
@@ -277,7 +210,7 @@
void run(ITensorPack &tensors) override;
};
-/** Basic function to run @ref CLArithmeticOperationKernel for squared difference
+/** Basic function to run @ref arm_compute::opencl::kernels::ClArithmeticKernel for squared difference
*
* @note The tensor data type for the inputs must be QASYMM8/U8/S16/QSYMM16/F16/F32.
* @note The function performs a squared different operation between two tensors (i.e., out[i] = (in1[i] - in2[i])^2
@@ -298,7 +231,7 @@
* @param[in] act_info (Optional) Activation layer information in case of a fused activation.
*/
void configure(const CLCompileContext &compile_context, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output, const ActivationLayerInfo &act_info = ActivationLayerInfo());
- /** Static function to check if given info will lead to a valid configuration of @ref CLArithmeticOperationKernel for squared difference
+ /** Static function to check if given info will lead to a valid configuration of @ref arm_compute::opencl::kernels::ClArithmeticKernel for squared difference
*
* @param[in] input1 First tensor input info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/F16/F32.
* @param[in] input2 Second tensor input info. Data types supported: same as @p input1.
@@ -313,7 +246,7 @@
void run(ITensorPack &tensors) override;
};
-/** Basic function to run @ref CLArithmeticOperationKernel for power
+/** Basic function to run @ref arm_compute::opencl::kernels::ClArithmeticKernel for power
*
* @note The tensor data type for the inputs must be F16/F32.
* @note The function performs an elementwise power of in1 to in2 (i.e., out[i] = in1[i] ^ in2[i])
@@ -334,7 +267,7 @@
* @param[in] act_info (Optional) Activation layer information in case of a fused activation.
*/
void configure(const CLCompileContext &compile_context, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output, const ActivationLayerInfo &act_info = ActivationLayerInfo());
- /** Static function to check if given info will lead to a valid configuration of @ref CLArithmeticOperationKernel for power
+ /** Static function to check if given info will lead to a valid configuration of @ref arm_compute::opencl::kernels::ClArithmeticKernel for power
*
* @param[in] input1 First tensor input info. Data types supported: F16/F32.
* @param[in] input2 Second tensor input info. Data types supported: F16/F32.
@@ -350,7 +283,7 @@
};
} // namespace experimental
-/** Basic function to run @ref CLSaturatedArithmeticOperationKernel for addition
+/** Basic function to run @ref opencl::kernels::ClSaturatedArithmeticKernel for addition
*
* @note The tensor data type for the inputs must be U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/S32/F16/F32.
* @note The function performs an arithmetic addition between two tensors.
@@ -422,7 +355,7 @@
*/
void configure(const CLCompileContext &compile_context, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, ConvertPolicy policy,
const ActivationLayerInfo &act_info = ActivationLayerInfo());
- /** Static function to check if given info will lead to a valid configuration of @ref CLSaturatedArithmeticOperationKernel for addition
+ /** Static function to check if given info will lead to a valid configuration of @ref opencl::kernels::ClSaturatedArithmeticKernel for addition
*
* Valid configurations (Input1,Input2) -> Output :
*
@@ -456,7 +389,7 @@
std::unique_ptr<Impl> _impl;
};
-/** Basic function to run @ref CLSaturatedArithmeticOperationKernel for subtraction
+/** Basic function to run @ref opencl::kernels::ClSaturatedArithmeticKernel for subtraction
*
* @note The tensor data type for the inputs must be U8/QASYMM8/QASYMM8_SIGNED/S16/S32/F16/F32.
* @note The function performs an arithmetic subtraction between two tensors.
@@ -528,7 +461,7 @@
*/
void configure(const CLCompileContext &compile_context, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, ConvertPolicy policy,
const ActivationLayerInfo &act_info = ActivationLayerInfo());
- /** Static function to check if given info will lead to a valid configuration of @ref CLSaturatedArithmeticOperationKernel for subtraction
+ /** Static function to check if given info will lead to a valid configuration of @ref opencl::kernels::ClSaturatedArithmeticKernel for subtraction
*
* Valid configurations (Input1,Input2) -> Output :
*
@@ -562,7 +495,7 @@
std::unique_ptr<Impl> _impl;
};
-/** Basic function to run @ref CLSaturatedArithmeticOperationKernel for division
+/** Basic function to run @ref opencl::kernels::ClSaturatedArithmeticKernel for division
*
* @note The tensor data type for the inputs must be F16/F32.
* @note The function performs an arithmetic division between two tensors.
@@ -622,7 +555,7 @@
std::unique_ptr<Impl> _impl;
};
-/** Basic function to run @ref CLArithmeticOperationKernel for max
+/** Basic function to run @ref opencl::kernels::ClArithmeticKernel for max
*
* @note The tensor data type for the inputs must be U8/QASYMM8/S16/QSYMM16/S32/U32/F16/F32.
* @note The function performs a max operation between two tensors.
@@ -663,7 +596,7 @@
* @param[in] act_info (Optional) Activation layer information in case of a fused activation.
*/
void configure(const CLCompileContext &compile_context, ICLTensor *input1, ICLTensor *input2, ICLTensor *output, const ActivationLayerInfo &act_info = ActivationLayerInfo());
- /** Static function to check if given info will lead to a valid configuration of @ref CLArithmeticOperationKernel for max
+ /** Static function to check if given info will lead to a valid configuration of @ref opencl::kernels::ClArithmeticKernel for max
*
* @param[in] input1 First tensor input info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/S32/U32/F16/F32.
* @param[in] input2 Second tensor input info. Data types supported: same as @p input1.
@@ -682,7 +615,7 @@
std::unique_ptr<Impl> _impl;
};
-/** Basic function to run @ref CLArithmeticOperationKernel for min
+/** Basic function to run @ref opencl::kernels::ClArithmeticKernel for min
*
* @note The tensor data type for the inputs must be U8/QASYMM8/S16/QSYMM16/S32/U32/F16/F32.
* @note The function performs a max operation between two tensors.
@@ -723,7 +656,7 @@
* @param[in] act_info (Optional) Activation layer information in case of a fused activation.
*/
void configure(const CLCompileContext &compile_context, ICLTensor *input1, ICLTensor *input2, ICLTensor *output, const ActivationLayerInfo &act_info = ActivationLayerInfo());
- /** Static function to check if given info will lead to a valid configuration of @ref CLArithmeticOperationKernel for min
+ /** Static function to check if given info will lead to a valid configuration of @ref opencl::kernels::ClArithmeticKernel for min
*
* @param[in] input1 First tensor input info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/S32/U32/F16/F32.
* @param[in] input2 Second tensor input info. Data types supported: same as @p input1.
@@ -742,7 +675,7 @@
std::unique_ptr<Impl> _impl;
};
-/** Basic function to run @ref CLArithmeticOperationKernel for squared difference
+/** Basic function to run @ref opencl::kernels::ClArithmeticKernel for squared difference
*
* @note The tensor data type for the inputs must be QASYMM8/U8/S16/QSYMM16/F16/F32.
* @note The function performs a squared different operation between two tensors (i.e., out[i] = (in1[i] - in2[i])^2
@@ -783,7 +716,7 @@
* @param[in] act_info (Optional) Activation layer information in case of a fused activation.
*/
void configure(const CLCompileContext &compile_context, ICLTensor *input1, ICLTensor *input2, ICLTensor *output, const ActivationLayerInfo &act_info = ActivationLayerInfo());
- /** Static function to check if given info will lead to a valid configuration of @ref CLArithmeticOperationKernel for squared difference
+ /** Static function to check if given info will lead to a valid configuration of @ref opencl::kernels::ClArithmeticKernel for squared difference
*
* @param[in] input1 First tensor input info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/F16/F32.
* @param[in] input2 Second tensor input info. Data types supported: same as @p input1.
@@ -802,7 +735,7 @@
std::unique_ptr<Impl> _impl;
};
-/** Basic function to run @ref CLArithmeticOperationKernel for power
+/** Basic function to run @ref opencl::kernels::ClArithmeticKernel for power
*
* @note The tensor data type for the inputs must be F16/F32.
* @note The function performs an elementwise power of in1 to in2 (i.e., out[i] = in1[i] ^ in2[i])
@@ -843,7 +776,7 @@
* @param[in] act_info (Optional) Activation layer information in case of a fused activation.
*/
void configure(const CLCompileContext &compile_context, ICLTensor *input1, ICLTensor *input2, ICLTensor *output, const ActivationLayerInfo &act_info = ActivationLayerInfo());
- /** Static function to check if given info will lead to a valid configuration of @ref CLArithmeticOperationKernel for power
+ /** Static function to check if given info will lead to a valid configuration of @ref opencl::kernels::ClArithmeticKernel for power
*
* @param[in] input1 First tensor input info. Data types supported: F16/F32.
* @param[in] input2 Second tensor input info. Data types supported: F16/F32.
diff --git a/arm_compute/runtime/CL/functions/CLLogicalAnd.h b/arm_compute/runtime/CL/functions/CLLogicalAnd.h
index f5d834c..f7038ee 100644
--- a/arm_compute/runtime/CL/functions/CLLogicalAnd.h
+++ b/arm_compute/runtime/CL/functions/CLLogicalAnd.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2020 Arm Limited.
+ * Copyright (c) 2020-2021 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -51,7 +51,7 @@
* @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 CLLogicalBinaryKernel
+ /** 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.
@@ -65,7 +65,7 @@
};
} // namespace experimental
-/** Basic function to run @ref CLLogicalBinaryKernel.
+/** Basic function to run @ref arm_compute::opencl::kernels::ClLogicalBinaryKernel.
*
* @note The tensor data type for the inputs must be U8.
* @note The function performs a logical AND operation using the two input tensors.
diff --git a/arm_compute/runtime/CL/functions/CLLogicalOr.h b/arm_compute/runtime/CL/functions/CLLogicalOr.h
index daf7d85..948baee 100644
--- a/arm_compute/runtime/CL/functions/CLLogicalOr.h
+++ b/arm_compute/runtime/CL/functions/CLLogicalOr.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2020 Arm Limited.
+ * Copyright (c) 2020-2021 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -51,7 +51,7 @@
* @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 CLLogicalBinaryKernel
+ /** 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.
@@ -65,7 +65,7 @@
};
} // namespace experimental
-/** Basic function to run @ref CLLogicalBinaryKernel.
+/** Basic function to run @ref arm_compute::opencl::kernels::ClLogicalBinaryKernel.
*
* @note The tensor data type for the inputs must be U8.
* @note The function performs a logical OR operation using the two input tensors.
diff --git a/arm_compute/runtime/CL/functions/CLPReluLayer.h b/arm_compute/runtime/CL/functions/CLPReluLayer.h
index ab32bcc..1751fda 100644
--- a/arm_compute/runtime/CL/functions/CLPReluLayer.h
+++ b/arm_compute/runtime/CL/functions/CLPReluLayer.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2019-2020 Arm Limited.
+ * Copyright (c) 2019-2021 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -35,7 +35,7 @@
namespace experimental
{
-/** Basic function to run @ref CLArithmeticOperationKernel for PRELU
+/** Basic function to run @ref arm_compute::opencl::kernels::ClArithmeticKernel for PRELU
*
* @note The function implements an activation layer with the PRELU activation function.
*/
@@ -69,7 +69,7 @@
};
} // namespace experimental
-/** Basic function to run @ref CLArithmeticOperationKernel for PRELU
+/** Basic function to run @ref opencl::kernels::ClArithmeticKernel for PRELU
*
* @note The function implements an activation layer with the PRELU activation function.
*/
diff --git a/docs/00_introduction.dox b/docs/00_introduction.dox
index 3c89cfd..d7ef3dc 100644
--- a/docs/00_introduction.dox
+++ b/docs/00_introduction.dox
@@ -166,7 +166,7 @@
- @ref NEGEMMLowpMatrixBReductionKernel
- Removed padding from OpenCL kernels:
- CLBatchConcatenateLayerKernel
- - @ref CLElementwiseOperationKernel
+ - CLElementwiseOperationKernel
- @ref CLBatchNormalizationLayerKernel
- @ref CLPoolingLayerKernel
- @ref CLWinogradInputTransformKernel
diff --git a/src/core/CL/CLKernels.h b/src/core/CL/CLKernels.h
index 76bc527..916cf45 100644
--- a/src/core/CL/CLKernels.h
+++ b/src/core/CL/CLKernels.h
@@ -57,7 +57,6 @@
#include "src/core/CL/kernels/CLDilateKernel.h"
#include "src/core/CL/kernels/CLDirectConvolutionLayerKernel.h"
#include "src/core/CL/kernels/CLElementWiseUnaryLayerKernel.h"
-#include "src/core/CL/kernels/CLElementwiseOperationKernel.h"
#include "src/core/CL/kernels/CLErodeKernel.h"
#include "src/core/CL/kernels/CLFFTDigitReverseKernel.h"
#include "src/core/CL/kernels/CLFFTRadixStageKernel.h"
diff --git a/src/core/CL/kernels/CLElementwiseOperationKernel.cpp b/src/core/CL/kernels/CLElementwiseOperationKernel.cpp
deleted file mode 100644
index 7c1d940..0000000
--- a/src/core/CL/kernels/CLElementwiseOperationKernel.cpp
+++ /dev/null
@@ -1,516 +0,0 @@
-/*
- * Copyright (c) 2018-2020 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/core/CL/kernels/CLElementwiseOperationKernel.h"
-
-#include "arm_compute/core/CL/CLHelpers.h"
-#include "arm_compute/core/CL/ICLTensor.h"
-#include "src/core/CL/CLValidate.h"
-#include "src/core/common/Validate.h"
-#include "src/core/helpers/AutoConfiguration.h"
-#include "src/core/helpers/WindowHelpers.h"
-#include "support/Cast.h"
-#include "support/StringSupport.h"
-#include <map>
-
-namespace arm_compute
-{
-namespace
-{
-constexpr unsigned int vector_size_byte_opencl = 16;
-
-std::map<ArithmeticOperation, std::string> supported_arithmetic_ops =
-{
- { ArithmeticOperation::ADD, "ADD" },
- { ArithmeticOperation::SUB, "SUB" },
- { ArithmeticOperation::DIV, "DIV" },
- { ArithmeticOperation::SQUARED_DIFF, "SQUARED_DIFF" },
- { ArithmeticOperation::MIN, "MIN" },
- { ArithmeticOperation::MAX, "MAX" },
- { ArithmeticOperation::POWER, "POWER" },
- { ArithmeticOperation::PRELU, "PRELU" },
-};
-
-std::map<ArithmeticOperation, std::string> supported_sat_arithmetic_ops =
-{
- { ArithmeticOperation::ADD, "ADD" },
- { ArithmeticOperation::SUB, "SUB" },
-};
-
-std::string generate_id_for_tuning_common(const std::string &kernel_name, const ITensorInfo &input1, const ITensorInfo &output)
-{
- std::string config_id;
- // Set config_id for enabling LWS tuning
- config_id = kernel_name;
- config_id += "_";
- config_id += lower_string(string_from_data_type(input1.data_type()));
- config_id += "_";
- config_id += support::cpp11::to_string(output.dimension(0));
- config_id += "_";
- config_id += support::cpp11::to_string(output.dimension(1));
- return config_id;
-}
-
-Status validate_arguments_with_float_only_supported_rules(const ITensorInfo &input1, const ITensorInfo &input2, const ITensorInfo &output)
-{
- ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(&input1, &input2, &output);
- ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(&input1);
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&input1, 1, DataType::F16, DataType::F32);
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(&input1, &input2);
-
- const TensorShape out_shape = TensorShape::broadcast_shape(input1.tensor_shape(), input2.tensor_shape());
-
- ARM_COMPUTE_RETURN_ERROR_ON_MSG(out_shape.total_size() == 0, "Inputs are not broadcast compatible");
-
- // Validate in case of configured output
- if(output.total_size() > 0)
- {
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&output, 1, DataType::F16, DataType::F32);
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(&input1, &output);
- ARM_COMPUTE_RETURN_ERROR_ON_MSG(detail::have_different_dimensions(out_shape, output.tensor_shape(), 0),
- "Wrong shape for output");
- }
-
- return Status{};
-}
-
-Status validate_arguments_with_arithmetic_rules(const ITensorInfo &input1, const ITensorInfo &input2, const ITensorInfo &output)
-{
- ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(&input1);
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&input1, 1, DataType::U8, DataType::QASYMM8, DataType::QASYMM8_SIGNED,
- DataType::S16, DataType::QSYMM16, DataType::F16,
- DataType::S32, DataType::F32);
- ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(&input2);
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&input2, 1, DataType::U8, DataType::QASYMM8, DataType::QASYMM8_SIGNED,
- DataType::S16, DataType::QSYMM16, DataType::F16,
- DataType::S32, DataType::F32);
-
- const bool is_quantized = is_data_type_quantized(input1.data_type()) || is_data_type_quantized(input2.data_type());
- if(is_quantized)
- {
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(&input1, &input2);
-
- if(is_data_type_quantized_symmetric(input1.data_type()))
- {
- const int32_t in1_offset = input1.quantization_info().uniform().offset;
- const int32_t in2_offset = input2.quantization_info().uniform().offset;
- ARM_COMPUTE_RETURN_ERROR_ON_MSG(in1_offset != 0, "For quantized symmetric, offset must be zero");
- ARM_COMPUTE_RETURN_ERROR_ON_MSG(in2_offset != 0, "For quantized symmetric, offset must be zero");
- }
- }
-
- const TensorShape out_shape = TensorShape::broadcast_shape(input1.tensor_shape(), input2.tensor_shape());
-
- ARM_COMPUTE_RETURN_ERROR_ON_MSG(out_shape.total_size() == 0, "Inputs are not broadcast compatible");
-
- // Validate in case of configured output
- if(output.total_size() > 0)
- {
- ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(&output);
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&output, 1, DataType::U8, DataType::QASYMM8, DataType::QASYMM8_SIGNED,
- DataType::S16, DataType::QSYMM16, DataType::F16,
- DataType::S32, DataType::F32);
- ARM_COMPUTE_RETURN_ERROR_ON_MSG((output.data_type() == DataType::U8) && ((input1.data_type() != DataType::U8) || (input2.data_type() != DataType::U8)),
- "Output can only be U8 if both inputs are U8");
- ARM_COMPUTE_RETURN_ERROR_ON_MSG(detail::have_different_dimensions(out_shape, output.tensor_shape(), 0),
- "Wrong shape for output");
-
- if(is_quantized)
- {
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(&input1, &output);
-
- if(is_data_type_quantized_symmetric(output.data_type()))
- {
- const int32_t offset = output.quantization_info().uniform().offset;
- ARM_COMPUTE_RETURN_ERROR_ON_MSG(offset != 0, "For quantized symmetric, offset must be zero");
- }
- }
- }
- return Status{};
-}
-
-CLBuildOptions generate_build_options_with_arithmetic_rules(const ITensorInfo &input1, const ITensorInfo &input2, const ITensorInfo &output, const std::string &operation_string)
-{
- CLBuildOptions build_opts;
-
- const unsigned int num_elems_processed_per_iteration = adjust_vec_size(vector_size_byte_opencl / output.element_size(), output.dimension(0));
-
- build_opts.add_option("-DDATA_TYPE_IN1=" + get_cl_type_from_data_type(input1.data_type()));
- build_opts.add_option("-DDATA_TYPE_IN2=" + get_cl_type_from_data_type(input2.data_type()));
- build_opts.add_option("-DDATA_TYPE_OUT=" + get_cl_type_from_data_type(output.data_type()));
- build_opts.add_option("-DVEC_SIZE_IN1=" + support::cpp11::to_string(input1.dimension(0) == 1 ? 1 : num_elems_processed_per_iteration));
- build_opts.add_option("-DVEC_SIZE_IN2=" + support::cpp11::to_string(input2.dimension(0) == 1 ? 1 : num_elems_processed_per_iteration));
- build_opts.add_option("-DVEC_SIZE_OUT=" + support::cpp11::to_string(num_elems_processed_per_iteration));
- build_opts.add_option("-DVEC_SIZE_LEFTOVER=" + support::cpp11::to_string(output.dimension(0) % num_elems_processed_per_iteration));
- build_opts.add_option("-DOP=" + operation_string);
- if(is_data_type_quantized(input1.data_type()))
- {
- const UniformQuantizationInfo iq1info = input1.quantization_info().uniform();
- const UniformQuantizationInfo iq2info = input2.quantization_info().uniform();
- const UniformQuantizationInfo oqinfo = output.quantization_info().uniform();
-
- build_opts.add_option("-DOFFSET_IN1=" + support::cpp11::to_string(iq1info.offset));
- build_opts.add_option("-DOFFSET_IN2=" + support::cpp11::to_string(iq2info.offset));
- build_opts.add_option("-DOFFSET_OUT=" + support::cpp11::to_string(oqinfo.offset));
- build_opts.add_option("-DSCALE_IN1=" + float_to_string_with_full_precision(iq1info.scale));
- build_opts.add_option("-DSCALE_IN2=" + float_to_string_with_full_precision(iq2info.scale));
- build_opts.add_option("-DSCALE_OUT=" + float_to_string_with_full_precision(oqinfo.scale));
- }
- return build_opts;
-}
-
-std::pair<Status, Window> configure_window_arithmetic_common(ITensorInfo &output)
-{
- const unsigned int num_elems_processed_per_iteration = adjust_vec_size(vector_size_byte_opencl / output.element_size(), output.dimension(0));
- Window win = calculate_max_window(output, Steps(num_elems_processed_per_iteration));
- return std::make_pair(Status{}, win);
-}
-
-std::pair<Status, Window> validate_and_configure_window_for_arithmetic_operators(ITensorInfo &input1, ITensorInfo &input2, ITensorInfo &output)
-{
- const std::pair<TensorShape, ValidRegion> broadcast_pair = ITensorInfo::broadcast_shape_and_valid_region(input1, input2);
- const TensorShape &out_shape = broadcast_pair.first;
-
- set_shape_if_empty(output, out_shape);
-
- if(input1.data_type() == DataType::S16 || input2.data_type() == DataType::S16)
- {
- set_format_if_unknown(output, Format::S16);
- }
- else if(input1.data_type() == DataType::F16 || input2.data_type() == DataType::F16)
- {
- set_format_if_unknown(output, Format::F16);
- }
- else if(input1.data_type() == DataType::F32 || input2.data_type() == DataType::F32)
- {
- set_format_if_unknown(output, Format::F32);
- }
- else if(input1.data_type() == DataType::QASYMM8 || input2.data_type() == DataType::QASYMM8)
- {
- set_data_type_if_unknown(output, DataType::QASYMM8);
- }
- else if(input1.data_type() == DataType::QASYMM8_SIGNED || input2.data_type() == DataType::QASYMM8_SIGNED)
- {
- set_data_type_if_unknown(output, DataType::QASYMM8_SIGNED);
- }
- else if(input1.data_type() == DataType::QSYMM16 || input2.data_type() == DataType::QSYMM16)
- {
- set_data_type_if_unknown(output, DataType::QSYMM16);
- }
-
- return configure_window_arithmetic_common(output);
-}
-
-std::pair<Status, Window> validate_and_configure_window_for_logical_binary_operators(ITensorInfo &input1, ITensorInfo &input2, ITensorInfo &output)
-{
- const std::pair<TensorShape, ValidRegion> broadcast_pair = ITensorInfo::broadcast_shape_and_valid_region(input1, input2);
- const TensorShape &out_shape = broadcast_pair.first;
-
- set_shape_if_empty(output, out_shape);
- set_data_type_if_unknown(output, DataType::U8);
-
- // The arithmetic utility functions can be share
- return configure_window_arithmetic_common(output);
-}
-
-std::pair<Status, Window> validate_and_configure_window_for_division(ITensorInfo &input1, ITensorInfo &input2, ITensorInfo &output)
-{
- const std::pair<TensorShape, ValidRegion> broadcast_pair = ITensorInfo::broadcast_shape_and_valid_region(input1, input2);
- const TensorShape &out_shape = broadcast_pair.first;
- auto_init_if_empty(output, out_shape, 1, input1.data_type());
- return configure_window_arithmetic_common(output);
-}
-} // namespace
-
-CLElementwiseOperationKernel::CLElementwiseOperationKernel()
- : _act_info(), _input1(nullptr), _input2(nullptr), _output(nullptr)
-{
-}
-
-void CLElementwiseOperationKernel::configure_common(ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output)
-{
- configure_common(CLKernelLibrary::get().get_compile_context(), input1, input2, output);
-}
-
-void CLElementwiseOperationKernel::configure_common(const CLCompileContext &compile_context, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output)
-{
- // Configure kernel window
- auto win_config = validate_and_configure_window(*input1, *input2, *output);
- ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
-
- _input1 = input1;
- _input2 = input2;
- _output = output;
-
- std::string kernel_name = "elementwise_operation_" + name();
- if(is_data_type_quantized(input1->data_type()))
- {
- kernel_name += "_quantized";
- }
-
- // Set kernel build options
- CLBuildOptions build_opts = generate_build_options(*input1, *input2, *output);
- if(_act_info.enabled())
- {
- build_opts.add_option("-DACTIVATION_TYPE=" + lower_string(string_from_activation_func(_act_info.activation())));
- build_opts.add_option("-DA_VAL=" + float_to_string_with_full_precision(_act_info.a()));
- build_opts.add_option("-DB_VAL=" + float_to_string_with_full_precision(_act_info.b()));
- }
-
- // Create kernel
- _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
-
- ICLKernel::configure_internal(win_config.second);
-
- _config_id = generate_id_for_tuning(kernel_name, *input1, *output);
-}
-
-void CLElementwiseOperationKernel::run_op(ITensorPack &tensors, const Window &window, cl::CommandQueue &queue)
-{
- ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
- ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window);
-
- const auto src_0 = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC_0));
- const auto src_1 = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC_1));
- auto dst = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_DST));
-
- const TensorShape &in_shape1 = src_0->info()->tensor_shape();
- const TensorShape &in_shape2 = src_1->info()->tensor_shape();
- const TensorShape &out_shape = dst->info()->tensor_shape();
-
- bool can_collapse = true;
- const bool is_vector = in_shape1.num_dimensions() == 1 || in_shape2.num_dimensions() == 1;
- if(std::min(in_shape1.total_size(), in_shape2.total_size()) > 1 && !is_vector)
- {
- can_collapse = (std::min(in_shape1.num_dimensions(), in_shape2.num_dimensions()) > Window::DimZ);
- for(size_t d = Window::DimZ; can_collapse && (d < out_shape.num_dimensions()); d++)
- {
- can_collapse = (in_shape1[d] == in_shape2[d]);
- }
- }
-
- bool has_collapsed = false;
- Window collapsed = can_collapse ? window.collapse_if_possible(ICLKernel::window(), Window::DimZ, &has_collapsed) : window;
-
- const TensorShape &in_shape1_collapsed = has_collapsed ? in_shape1.collapsed_from(Window::DimZ) : in_shape1;
- const TensorShape &in_shape2_collapsed = has_collapsed ? in_shape2.collapsed_from(Window::DimZ) : in_shape2;
-
- Window slice = collapsed.first_slice_window_3D();
- Window slice_input1 = slice.broadcast_if_dimension_le_one(in_shape1_collapsed);
- Window slice_input2 = slice.broadcast_if_dimension_le_one(in_shape2_collapsed);
- do
- {
- unsigned int idx = 0;
- add_3D_tensor_argument(idx, src_0, slice_input1);
- add_3D_tensor_argument(idx, src_1, slice_input2);
- add_3D_tensor_argument(idx, dst, slice);
-
- enqueue(queue, *this, slice, lws_hint());
- ARM_COMPUTE_UNUSED(collapsed.slide_window_slice_3D(slice_input1));
- ARM_COMPUTE_UNUSED(collapsed.slide_window_slice_3D(slice_input2));
- }
- while(collapsed.slide_window_slice_3D(slice));
-}
-
-/** Logical binary */
-
-void CLLogicalBinaryKernel::configure(const CLCompileContext &compile_context, kernels::LogicalOperation op, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output)
-{
- ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output);
- ARM_COMPUTE_ERROR_THROW_ON(CLLogicalBinaryKernel::validate(op, input1, input2, output));
- _op = op;
- configure_common(compile_context, input1, input2, output);
-}
-
-Status CLLogicalBinaryKernel::validate(kernels::LogicalOperation op, const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output)
-{
- ARM_COMPUTE_UNUSED(op);
- ARM_COMPUTE_ASSERT(op != kernels::LogicalOperation::Unknown && op != kernels::LogicalOperation::Not);
- ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input1, input2, output);
-
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input1, 1, DataType::U8);
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input1, input2);
-
- ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_with_arithmetic_rules(*input1, *input2, *output));
- ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window_for_logical_binary_operators(*input1->clone(), *input2->clone(), *output->clone()).first);
-
- return Status{};
-}
-
-std::string CLLogicalBinaryKernel::name()
-{
- switch(_op)
- {
- case kernels::LogicalOperation::And:
- return "AND";
- case kernels::LogicalOperation::Or:
- return "OR";
- case kernels::LogicalOperation::Not:
- /* fall through */
- default:
- ARM_COMPUTE_ASSERT(true);
- }
- return "";
-}
-
-std::pair<Status, Window> CLLogicalBinaryKernel::validate_and_configure_window(ITensorInfo &input1, ITensorInfo &input2, ITensorInfo &output)
-{
- return validate_and_configure_window_for_logical_binary_operators(input1, input2, output);
-}
-
-CLBuildOptions CLLogicalBinaryKernel::generate_build_options(const ITensorInfo &input1, const ITensorInfo &input2, const ITensorInfo &output)
-{
- // The arithmetic utility functions can be share
- return generate_build_options_with_arithmetic_rules(input1, input2, output, name());
-}
-
-std::string CLLogicalBinaryKernel::generate_id_for_tuning(const std::string &kernel_name, const ITensorInfo &input1, const ITensorInfo &output)
-{
- return generate_id_for_tuning_common(kernel_name, input1, output);
-}
-
-/** Arithmetic operations with saturation*/
-
-void CLSaturatedArithmeticOperationKernel::configure(ArithmeticOperation op, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output, const ConvertPolicy &policy,
- const ActivationLayerInfo &act_info)
-{
- configure(CLKernelLibrary::get().get_compile_context(), op, input1, input2, output, policy, act_info);
-}
-
-void CLSaturatedArithmeticOperationKernel::configure(const CLCompileContext &compile_context, ArithmeticOperation op, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output,
- const ConvertPolicy &policy,
- const ActivationLayerInfo &act_info)
-{
- ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output);
- ARM_COMPUTE_ERROR_THROW_ON(CLSaturatedArithmeticOperationKernel::validate(op, input1, input2, output, policy, act_info));
- auto padding_info = get_padding_info({ input1, input2, output });
-
- _policy = policy;
- _op = op;
- _act_info = act_info;
- configure_common(compile_context, input1, input2, output);
- ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info));
-}
-
-Status CLSaturatedArithmeticOperationKernel::validate(ArithmeticOperation op, const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, const ConvertPolicy &policy,
- const ActivationLayerInfo &act_info)
-{
- ARM_COMPUTE_UNUSED(op, policy);
- ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input1, input2, output);
- ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_with_arithmetic_rules(*input1, *input2, *output));
- ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window_for_arithmetic_operators(*input1->clone(), *input2->clone(), *output->clone()).first);
- ARM_COMPUTE_RETURN_ERROR_ON(act_info.enabled() && !is_data_type_float(output->data_type()));
-
- return Status{};
-}
-
-std::pair<Status, Window> CLSaturatedArithmeticOperationKernel::validate_and_configure_window(ITensorInfo &input1, ITensorInfo &input2, ITensorInfo &output)
-{
- return validate_and_configure_window_for_arithmetic_operators(input1, input2, output);
-}
-
-CLBuildOptions CLSaturatedArithmeticOperationKernel::generate_build_options(const ITensorInfo &input1, const ITensorInfo &input2, const ITensorInfo &output)
-{
- const bool has_float_out = is_data_type_float(output.data_type());
- auto build_options = generate_build_options_with_arithmetic_rules(input1, input2, output, name());
- build_options.add_option((_policy == ConvertPolicy::WRAP || has_float_out) ? "-DWRAP" : "-DSATURATE");
- return build_options;
-}
-std::string CLSaturatedArithmeticOperationKernel::generate_id_for_tuning(const std::string &kernel_name, const ITensorInfo &input1, const ITensorInfo &output)
-{
- auto config_id = generate_id_for_tuning_common(kernel_name, input1, output);
- config_id += (_policy == ConvertPolicy::WRAP) ? "_wrap_" : "_saturate_";
- config_id += lower_string(string_from_data_layout(input1.data_layout()));
- return config_id;
-}
-
-std::string CLSaturatedArithmeticOperationKernel::name()
-{
- return supported_sat_arithmetic_ops[_op];
-}
-
-/** Arithmetic operations*/
-
-void CLArithmeticOperationKernel::configure(ArithmeticOperation op, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output, const ActivationLayerInfo &act_info)
-{
- configure(CLKernelLibrary::get().get_compile_context(), op, input1, input2, output, act_info);
-}
-
-void CLArithmeticOperationKernel::configure(const CLCompileContext &compile_context, ArithmeticOperation op, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output,
- const ActivationLayerInfo &act_info)
-{
- ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output);
- ARM_COMPUTE_ERROR_THROW_ON(CLArithmeticOperationKernel::validate(op, input1, input2, output, act_info));
- auto padding_info = get_padding_info({ input1, input2, output });
-
- _op = op;
- _act_info = act_info;
- configure_common(compile_context, input1, input2, output);
- ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info));
-}
-
-Status CLArithmeticOperationKernel::validate(ArithmeticOperation op, const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, const ActivationLayerInfo &act_info)
-{
- ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input1, input2, output);
- if(op == ArithmeticOperation::DIV || op == ArithmeticOperation::POWER)
- {
- // Division and Power operators don't support integer arithmetic
- ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_with_float_only_supported_rules(*input1, *input2, *output));
- ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window_for_division(*input1->clone(), *input2->clone(), *output->clone()).first);
- }
- else
- {
- ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_with_arithmetic_rules(*input1, *input2, *output));
- ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window_for_arithmetic_operators(*input1->clone(), *input2->clone(), *output->clone()).first);
- }
- ARM_COMPUTE_RETURN_ERROR_ON(act_info.enabled() && !is_data_type_float(output->data_type()));
-
- return Status{};
-}
-std::pair<Status, Window> CLArithmeticOperationKernel::validate_and_configure_window(ITensorInfo &input1, ITensorInfo &input2, ITensorInfo &output)
-{
- if(_op == ArithmeticOperation::DIV || _op == ArithmeticOperation::POWER)
- {
- // Division and Power operators don't support integer arithmetic
- return validate_and_configure_window_for_division(input1, input2, output);
- }
- else
- {
- return validate_and_configure_window_for_arithmetic_operators(input1, input2, output);
- }
-}
-
-CLBuildOptions CLArithmeticOperationKernel::generate_build_options(const ITensorInfo &input1, const ITensorInfo &input2, const ITensorInfo &output)
-{
- return generate_build_options_with_arithmetic_rules(input1, input2, output, name());
-}
-std::string CLArithmeticOperationKernel::generate_id_for_tuning(const std::string &kernel_name, const ITensorInfo &input1, const ITensorInfo &output)
-{
- return generate_id_for_tuning_common(kernel_name, input1, output);
-}
-
-std::string CLArithmeticOperationKernel::name()
-{
- return supported_arithmetic_ops[_op];
-}
-} // namespace arm_compute
diff --git a/src/core/CL/kernels/CLElementwiseOperationKernel.h b/src/core/CL/kernels/CLElementwiseOperationKernel.h
deleted file mode 100644
index dd04a03..0000000
--- a/src/core/CL/kernels/CLElementwiseOperationKernel.h
+++ /dev/null
@@ -1,256 +0,0 @@
-/*
- * Copyright (c) 2018-2020 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 ARM_COMPUTE_CLELEMENTWISEOPERATIONKERNEL_H
-#define ARM_COMPUTE_CLELEMENTWISEOPERATIONKERNEL_H
-
-#include "arm_compute/core/Types.h"
-#include "src/core/CL/ICLKernel.h"
-#include "src/core/KernelTypes.h"
-
-namespace arm_compute
-{
-class ICLTensor;
-
-/** Interface for an element-wise operation kernel
- *
- * Element-wise operation is computed by:
- * @f[ output(x,y) = OP(input1(x,y), input2(x,y))@f]
- *
- */
-class CLElementwiseOperationKernel : public ICLKernel
-{
-public:
- /** Default constructor */
- CLElementwiseOperationKernel();
- /** Prevent instances of this class from being copied (As this class contains pointers) */
- CLElementwiseOperationKernel(const CLElementwiseOperationKernel &) = delete;
- /** Prevent instances of this class from being copied (As this class contains pointers) */
- CLElementwiseOperationKernel &operator=(const CLElementwiseOperationKernel &) = delete;
- /** Allow instances of this class to be moved */
- CLElementwiseOperationKernel(CLElementwiseOperationKernel &&) = default;
- /** Allow instances of this class to be moved */
- CLElementwiseOperationKernel &operator=(CLElementwiseOperationKernel &&) = default;
- /** Default destructor */
- ~CLElementwiseOperationKernel() = default;
-
- // Inherited methods overridden:
- void run_op(ITensorPack &tensors, const Window &window, cl::CommandQueue &queue) override;
-
-protected:
- /** The name of the operation */
- virtual std::string name() = 0;
-
- /** Initialise the kernel's output.
- *
- * @param[in] input1 First tensor input info. Data types supported: U8/S8/QASYMM8/QASYMM8_SIGNED/U16/S16/F16/U32/S32/F32.
- * @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 pair of Status and Window
- */
- virtual std::pair<Status, Window> validate_and_configure_window(ITensorInfo &input1, ITensorInfo &input2, ITensorInfo &output) = 0;
-
- /** Generate the build options for the specific kernel
- *
- * @reutrn a CLBuildOptions struct
- */
- virtual CLBuildOptions generate_build_options(const ITensorInfo &input1, const ITensorInfo &input2, const ITensorInfo &output) = 0;
-
- /** Generate the identifier for tuning
- *
- * @reutrn a string
- */
- virtual std::string generate_id_for_tuning(const std::string &kernel_name, const ITensorInfo &input1, const ITensorInfo &output) = 0;
-
- /** Commmon configure function for element-wise operators with no additional options (e.g., Div, Min, Max, SquaredDiff)
- *
- */
- void configure_common(ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output);
- /** Commmon configure function for element-wise operators with no additional options (e.g., Div, Min, Max, SquaredDiff)
- *
- */
- void configure_common(const CLCompileContext &compile_context, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output);
-
- ActivationLayerInfo _act_info;
-
-private:
- const ITensorInfo *_input1; /**< Source tensor info 1 */
- const ITensorInfo *_input2; /**< Source tensor info 2 */
- ITensorInfo *_output; /**< Destination tensor info */
-};
-
-class CLLogicalBinaryKernel : public CLElementwiseOperationKernel
-{
-public:
- /** Default constructor */
- CLLogicalBinaryKernel() = default;
- /** Prevent instances of this class from being copied (As this class contains pointers) */
- CLLogicalBinaryKernel(const CLLogicalBinaryKernel &) = delete;
- /** Prevent instances of this class from being copied (As this class contains pointers) */
- CLLogicalBinaryKernel &operator=(const CLLogicalBinaryKernel &) = delete;
- /** Allow instances of this class to be moved */
- CLLogicalBinaryKernel(CLLogicalBinaryKernel &&) = default;
- /** Allow instances of this class to be moved */
- CLLogicalBinaryKernel &operator=(CLLogicalBinaryKernel &&) = default;
- /** Default destructor */
- ~CLLogicalBinaryKernel() = default;
- /** Function to configure kernel
- *
- * @param[in] compile_context The compile context to be used.
- * @param[in] op Logical binary operation to be executed.
- * @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.
- */
- void configure(const CLCompileContext &compile_context, kernels::LogicalOperation op, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output);
- /** Static function to check if the given configuration is valid for this kernel
- *
- * @param[in] op Logical binary operation to be executed.
- * @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.
- */
- static Status validate(kernels::LogicalOperation op, const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output);
-
-private:
- // Inherited methods overridden:
- std::string name() override;
- std::pair<Status, Window> validate_and_configure_window(ITensorInfo &input1, ITensorInfo &input2, ITensorInfo &output) override;
- CLBuildOptions generate_build_options(const ITensorInfo &input1, const ITensorInfo &input2, const ITensorInfo &output) override;
- std::string generate_id_for_tuning(const std::string &kernel_name, const ITensorInfo &input1, const ITensorInfo &output) override;
-
- kernels::LogicalOperation _op{ kernels::LogicalOperation::Unknown };
-};
-
-/** Addition operation */
-class CLSaturatedArithmeticOperationKernel : public CLElementwiseOperationKernel
-{
-public:
- CLSaturatedArithmeticOperationKernel()
- : CLElementwiseOperationKernel(), _policy(), _op()
- {
- }
-
- /** Static function to check if given info will lead to a valid configuration of @ref CLSaturatedArithmeticOperationKernel
- *
- * @param[in] op Arithmetic operation to be executed.
- * @param[in] input1 First tensor input info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/F16/S32/F32.
- * @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.
- * @param[in] policy Policy to use to handle overflow.
- * @param[in] act_info (Optional) Activation layer information in case of a fused activation.
- */
- void configure(ArithmeticOperation op, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output, const ConvertPolicy &policy, const ActivationLayerInfo &act_info = ActivationLayerInfo());
- /** Static function to check if given info will lead to a valid configuration of @ref CLSaturatedArithmeticOperationKernel
- *
- * @param[in] compile_context The compile context to be used.
- * @param[in] op Arithmetic operation to be executed.
- * @param[in] input1 First tensor input info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/F16/S32/F32.
- * @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.
- * @param[in] policy Policy to use to handle overflow.
- * @param[in] act_info (Optional) Activation layer information in case of a fused activation.
- */
- void configure(const CLCompileContext &compile_context, ArithmeticOperation op, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output, const ConvertPolicy &policy,
- const ActivationLayerInfo &act_info = ActivationLayerInfo());
-
- /** Static function to check if given info will lead to a valid configuration of @ref CLSaturatedArithmeticOperationKernel
- *
- * @param[in] op Arithmetic operation to be executed.
- * @param[in] input1 First tensor input info info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/F16/S32/F32.
- * @param[in] input2 Second tensor input info info. Data types supported: Same as @p input1.
- * @param[in] output Output tensor info info. Data types supported: Same as @p input1.
- * @param[in] policy Policy to use to handle overflow.
- * @param[in] act_info (Optional) Activation layer information in case of a fused activation.
- *
- * @return a Status
- */
- static Status validate(ArithmeticOperation op, const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, const ConvertPolicy &policy,
- const ActivationLayerInfo &act_info = ActivationLayerInfo());
-
-protected:
- // Inherited methods overridden:
- std::string name() override;
- std::pair<Status, Window> validate_and_configure_window(ITensorInfo &input1, ITensorInfo &input2, ITensorInfo &output) override;
- CLBuildOptions generate_build_options(const ITensorInfo &input1, const ITensorInfo &input2, const ITensorInfo &output) override;
- std::string generate_id_for_tuning(const std::string &kernel_name, const ITensorInfo &input1, const ITensorInfo &output) override;
-
-private:
- ConvertPolicy _policy;
- ArithmeticOperation _op;
-};
-
-class CLArithmeticOperationKernel : public CLElementwiseOperationKernel
-{
-public:
- CLArithmeticOperationKernel()
- : CLElementwiseOperationKernel(), _op()
- {
- }
-
- /** Static function to check if given info will lead to a valid configuration of @ref CLArithmeticOperationKernel
- *
- * @param[in] op Arithmetic operation to be executed.
- * @param[in] input1 First tensor input info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/F16/S32/F32.
- * @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.
- * @param[in] act_info (Optional) Activation layer information in case of a fused activation.
- */
- void configure(ArithmeticOperation op, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output, const ActivationLayerInfo &act_info = ActivationLayerInfo());
- /** Static function to check if given info will lead to a valid configuration of @ref CLArithmeticOperationKernel
- *
- * @param[in] compile_context The compile context to be used.
- * @param[in] op Arithmetic operation to be executed.
- * @param[in] input1 First tensor input info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/F16/S32/F32.
- * @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.
- * @param[in] act_info (Optional) Activation layer information in case of a fused activation.
- */
- void configure(const CLCompileContext &compile_context, ArithmeticOperation op, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output,
- const ActivationLayerInfo &act_info = ActivationLayerInfo());
-
- /** Static function to check if given info will lead to a valid configuration of @ref CLArithmeticOperationKernel
- *
- * @param[in] op Arithmetic operation to be executed.
- * @param[in] input1 First tensor input info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/F16/S32/F32.
- * @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.
- * @param[in] act_info (Optional) Activation layer information in case of a fused activation.
- *
- * @return a Status
- */
- static Status validate(ArithmeticOperation op, const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, const ActivationLayerInfo &act_info = ActivationLayerInfo());
-
-protected:
- // Inherited methods overridden:
- std::string name() override;
- std::pair<Status, Window> validate_and_configure_window(ITensorInfo &input1, ITensorInfo &input2, ITensorInfo &output) override;
- CLBuildOptions generate_build_options(const ITensorInfo &input1, const ITensorInfo &input2, const ITensorInfo &output) override;
- std::string generate_id_for_tuning(const std::string &kernel_name, const ITensorInfo &input1, const ITensorInfo &output) override;
-
-private:
- ArithmeticOperation _op;
-};
-} // namespace arm_compute
-#endif /* ARM_COMPUTE_CLELEMENTWISEOPERATIONKERNEL_H */
diff --git a/src/core/KernelTypes.h b/src/core/KernelTypes.h
index 12e6bc9..a32f5db 100644
--- a/src/core/KernelTypes.h
+++ b/src/core/KernelTypes.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2020 Arm Limited.
+ * Copyright (c) 2020-2021 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -26,8 +26,6 @@
namespace arm_compute
{
-namespace kernels
-{
/** List of supported logical operations */
enum class LogicalOperation
{
@@ -36,6 +34,5 @@
Or, /**< Logical Or || */
Not, /**< Logical Not ! */
};
-} // namespace kernels
} // namespace arm_compute
#endif /* ARM_COMPUTE_KERNEL_TYPES_H */
diff --git a/src/core/gpu/cl/kernels/ClElementwiseKernel.cpp b/src/core/gpu/cl/kernels/ClElementwiseKernel.cpp
new file mode 100644
index 0000000..7d204b1
--- /dev/null
+++ b/src/core/gpu/cl/kernels/ClElementwiseKernel.cpp
@@ -0,0 +1,505 @@
+/*
+ * Copyright (c) 2018-2021 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/core/gpu/cl/kernels/ClElementwiseKernel.h"
+
+#include "arm_compute/core/CL/CLHelpers.h"
+#include "arm_compute/core/CL/ICLTensor.h"
+#include "src/core/CL/CLValidate.h"
+#include "src/core/common/Validate.h"
+#include "src/core/helpers/AutoConfiguration.h"
+#include "src/core/helpers/WindowHelpers.h"
+#include "support/Cast.h"
+#include "support/StringSupport.h"
+#include <map>
+
+namespace arm_compute
+{
+namespace opencl
+{
+namespace kernels
+{
+namespace
+{
+constexpr unsigned int vector_size_byte_opencl = 16;
+
+std::map<ArithmeticOperation, std::string> supported_arithmetic_ops =
+{
+ { ArithmeticOperation::ADD, "ADD" },
+ { ArithmeticOperation::SUB, "SUB" },
+ { ArithmeticOperation::DIV, "DIV" },
+ { ArithmeticOperation::SQUARED_DIFF, "SQUARED_DIFF" },
+ { ArithmeticOperation::MIN, "MIN" },
+ { ArithmeticOperation::MAX, "MAX" },
+ { ArithmeticOperation::POWER, "POWER" },
+ { ArithmeticOperation::PRELU, "PRELU" },
+};
+
+std::map<ArithmeticOperation, std::string> supported_sat_arithmetic_ops =
+{
+ { ArithmeticOperation::ADD, "ADD" },
+ { ArithmeticOperation::SUB, "SUB" },
+};
+
+std::string generate_id_for_tuning_common(const std::string &kernel_name, const ITensorInfo &src1, const ITensorInfo &dst)
+{
+ std::string config_id;
+ // Set config_id for enabling LWS tuning
+ config_id = kernel_name;
+ config_id += "_";
+ config_id += lower_string(string_from_data_type(src1.data_type()));
+ config_id += "_";
+ config_id += support::cpp11::to_string(dst.dimension(0));
+ config_id += "_";
+ config_id += support::cpp11::to_string(dst.dimension(1));
+ return config_id;
+}
+
+Status validate_arguments_with_float_only_supported_rules(const ITensorInfo &src1, const ITensorInfo &src2, const ITensorInfo &dst)
+{
+ ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(&src1, &src2, &dst);
+ ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(&src1);
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&src1, 1, DataType::F16, DataType::F32);
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(&src1, &src2);
+
+ const TensorShape out_shape = TensorShape::broadcast_shape(src1.tensor_shape(), src2.tensor_shape());
+
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(out_shape.total_size() == 0, "Inputs are not broadcast compatible");
+
+ // Validate in case of configured dst
+ if(dst.total_size() > 0)
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&dst, 1, DataType::F16, DataType::F32);
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(&src1, &dst);
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(detail::have_different_dimensions(out_shape, dst.tensor_shape(), 0),
+ "Wrong shape for dst");
+ }
+
+ return Status{};
+}
+
+Status validate_arguments_with_arithmetic_rules(const ITensorInfo &src1, const ITensorInfo &src2, const ITensorInfo &dst)
+{
+ ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(&src1);
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&src1, 1, DataType::U8, DataType::QASYMM8, DataType::QASYMM8_SIGNED,
+ DataType::S16, DataType::QSYMM16, DataType::F16,
+ DataType::S32, DataType::F32);
+ ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(&src2);
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&src2, 1, DataType::U8, DataType::QASYMM8, DataType::QASYMM8_SIGNED,
+ DataType::S16, DataType::QSYMM16, DataType::F16,
+ DataType::S32, DataType::F32);
+
+ const bool is_quantized = is_data_type_quantized(src1.data_type()) || is_data_type_quantized(src2.data_type());
+ if(is_quantized)
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(&src1, &src2);
+
+ if(is_data_type_quantized_symmetric(src1.data_type()))
+ {
+ const int32_t in1_offset = src1.quantization_info().uniform().offset;
+ const int32_t in2_offset = src2.quantization_info().uniform().offset;
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(in1_offset != 0, "For quantized symmetric, offset must be zero");
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(in2_offset != 0, "For quantized symmetric, offset must be zero");
+ }
+ }
+
+ const TensorShape out_shape = TensorShape::broadcast_shape(src1.tensor_shape(), src2.tensor_shape());
+
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(out_shape.total_size() == 0, "Inputs are not broadcast compatible");
+
+ // Validate in case of configured dst
+ if(dst.total_size() > 0)
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(&dst);
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&dst, 1, DataType::U8, DataType::QASYMM8, DataType::QASYMM8_SIGNED,
+ DataType::S16, DataType::QSYMM16, DataType::F16,
+ DataType::S32, DataType::F32);
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG((dst.data_type() == DataType::U8) && ((src1.data_type() != DataType::U8) || (src2.data_type() != DataType::U8)),
+ "dst can only be U8 if both inputs are U8");
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(detail::have_different_dimensions(out_shape, dst.tensor_shape(), 0),
+ "Wrong shape for dst");
+
+ if(is_quantized)
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(&src1, &dst);
+
+ if(is_data_type_quantized_symmetric(dst.data_type()))
+ {
+ const int32_t offset = dst.quantization_info().uniform().offset;
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(offset != 0, "For quantized symmetric, offset must be zero");
+ }
+ }
+ }
+ return Status{};
+}
+
+CLBuildOptions generate_build_options_with_arithmetic_rules(const ITensorInfo &src1, const ITensorInfo &src2, const ITensorInfo &dst, const std::string &operation_string)
+{
+ CLBuildOptions build_opts;
+
+ const unsigned int num_elems_processed_per_iteration = adjust_vec_size(vector_size_byte_opencl / dst.element_size(), dst.dimension(0));
+
+ build_opts.add_option("-DDATA_TYPE_IN1=" + get_cl_type_from_data_type(src1.data_type()));
+ build_opts.add_option("-DDATA_TYPE_IN2=" + get_cl_type_from_data_type(src2.data_type()));
+ build_opts.add_option("-DDATA_TYPE_OUT=" + get_cl_type_from_data_type(dst.data_type()));
+ build_opts.add_option("-DVEC_SIZE_IN1=" + support::cpp11::to_string(src1.dimension(0) == 1 ? 1 : num_elems_processed_per_iteration));
+ build_opts.add_option("-DVEC_SIZE_IN2=" + support::cpp11::to_string(src2.dimension(0) == 1 ? 1 : num_elems_processed_per_iteration));
+ build_opts.add_option("-DVEC_SIZE_OUT=" + support::cpp11::to_string(num_elems_processed_per_iteration));
+ build_opts.add_option("-DVEC_SIZE_LEFTOVER=" + support::cpp11::to_string(dst.dimension(0) % num_elems_processed_per_iteration));
+ build_opts.add_option("-DOP=" + operation_string);
+ if(is_data_type_quantized(src1.data_type()))
+ {
+ const UniformQuantizationInfo iq1info = src1.quantization_info().uniform();
+ const UniformQuantizationInfo iq2info = src2.quantization_info().uniform();
+ const UniformQuantizationInfo oqinfo = dst.quantization_info().uniform();
+
+ build_opts.add_option("-DOFFSET_IN1=" + support::cpp11::to_string(iq1info.offset));
+ build_opts.add_option("-DOFFSET_IN2=" + support::cpp11::to_string(iq2info.offset));
+ build_opts.add_option("-DOFFSET_OUT=" + support::cpp11::to_string(oqinfo.offset));
+ build_opts.add_option("-DSCALE_IN1=" + float_to_string_with_full_precision(iq1info.scale));
+ build_opts.add_option("-DSCALE_IN2=" + float_to_string_with_full_precision(iq2info.scale));
+ build_opts.add_option("-DSCALE_OUT=" + float_to_string_with_full_precision(oqinfo.scale));
+ }
+ return build_opts;
+}
+
+std::pair<Status, Window> configure_window_arithmetic_common(ITensorInfo &dst)
+{
+ const unsigned int num_elems_processed_per_iteration = adjust_vec_size(vector_size_byte_opencl / dst.element_size(), dst.dimension(0));
+ Window win = calculate_max_window(dst, Steps(num_elems_processed_per_iteration));
+ return std::make_pair(Status{}, win);
+}
+
+std::pair<Status, Window> validate_and_configure_window_for_arithmetic_operators(ITensorInfo &src1, ITensorInfo &src2, ITensorInfo &dst)
+{
+ const std::pair<TensorShape, ValidRegion> broadcast_pair = ITensorInfo::broadcast_shape_and_valid_region(src1, src2);
+ const TensorShape &out_shape = broadcast_pair.first;
+
+ set_shape_if_empty(dst, out_shape);
+
+ if(src1.data_type() == DataType::S16 || src2.data_type() == DataType::S16)
+ {
+ set_format_if_unknown(dst, Format::S16);
+ }
+ else if(src1.data_type() == DataType::F16 || src2.data_type() == DataType::F16)
+ {
+ set_format_if_unknown(dst, Format::F16);
+ }
+ else if(src1.data_type() == DataType::F32 || src2.data_type() == DataType::F32)
+ {
+ set_format_if_unknown(dst, Format::F32);
+ }
+ else if(src1.data_type() == DataType::QASYMM8 || src2.data_type() == DataType::QASYMM8)
+ {
+ set_data_type_if_unknown(dst, DataType::QASYMM8);
+ }
+ else if(src1.data_type() == DataType::QASYMM8_SIGNED || src2.data_type() == DataType::QASYMM8_SIGNED)
+ {
+ set_data_type_if_unknown(dst, DataType::QASYMM8_SIGNED);
+ }
+ else if(src1.data_type() == DataType::QSYMM16 || src2.data_type() == DataType::QSYMM16)
+ {
+ set_data_type_if_unknown(dst, DataType::QSYMM16);
+ }
+
+ return configure_window_arithmetic_common(dst);
+}
+
+std::pair<Status, Window> validate_and_configure_window_for_logical_binary_operators(ITensorInfo &src1, ITensorInfo &src2, ITensorInfo &dst)
+{
+ const std::pair<TensorShape, ValidRegion> broadcast_pair = ITensorInfo::broadcast_shape_and_valid_region(src1, src2);
+ const TensorShape &out_shape = broadcast_pair.first;
+
+ set_shape_if_empty(dst, out_shape);
+ set_data_type_if_unknown(dst, DataType::U8);
+
+ // The arithmetic utility functions can be share
+ return configure_window_arithmetic_common(dst);
+}
+
+std::pair<Status, Window> validate_and_configure_window_for_division(ITensorInfo &src1, ITensorInfo &src2, ITensorInfo &dst)
+{
+ const std::pair<TensorShape, ValidRegion> broadcast_pair = ITensorInfo::broadcast_shape_and_valid_region(src1, src2);
+ const TensorShape &out_shape = broadcast_pair.first;
+ auto_init_if_empty(dst, out_shape, 1, src1.data_type());
+ return configure_window_arithmetic_common(dst);
+}
+} // namespace
+
+void ClElementwiseKernel::configure_common(ITensorInfo *src1, ITensorInfo *src2, ITensorInfo *dst)
+{
+ configure_common(CLKernelLibrary::get().get_compile_context(), src1, src2, dst);
+}
+
+void ClElementwiseKernel::configure_common(const ClCompileContext &compile_context, ITensorInfo *src1, ITensorInfo *src2, ITensorInfo *dst)
+{
+ // Configure kernel window
+ auto win_config = validate_and_configure_window(*src1, *src2, *dst);
+ ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
+
+ _src1 = src1;
+ _src2 = src2;
+ _dst = dst;
+
+ std::string kernel_name = "elementwise_operation_" + name();
+ if(is_data_type_quantized(src1->data_type()))
+ {
+ kernel_name += "_quantized";
+ }
+
+ // Set kernel build options
+ CLBuildOptions build_opts = generate_build_options(*src1, *src2, *dst);
+ if(_act_info.enabled())
+ {
+ build_opts.add_option("-DACTIVATION_TYPE=" + lower_string(string_from_activation_func(_act_info.activation())));
+ build_opts.add_option("-DA_VAL=" + float_to_string_with_full_precision(_act_info.a()));
+ build_opts.add_option("-DB_VAL=" + float_to_string_with_full_precision(_act_info.b()));
+ }
+
+ // Create kernel
+ _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
+
+ ICLKernel::configure_internal(win_config.second);
+
+ _config_id = generate_id_for_tuning(kernel_name, *src1, *dst);
+}
+
+void ClElementwiseKernel::run_op(ITensorPack &tensors, const Window &window, ::cl::CommandQueue &queue)
+{
+ ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
+ ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window);
+
+ const auto src_0 = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC_0));
+ const auto src_1 = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC_1));
+ auto dst = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_DST));
+
+ const TensorShape &in_shape1 = src_0->info()->tensor_shape();
+ const TensorShape &in_shape2 = src_1->info()->tensor_shape();
+ const TensorShape &out_shape = dst->info()->tensor_shape();
+
+ bool can_collapse = true;
+ const bool is_vector = in_shape1.num_dimensions() == 1 || in_shape2.num_dimensions() == 1;
+ if(std::min(in_shape1.total_size(), in_shape2.total_size()) > 1 && !is_vector)
+ {
+ can_collapse = (std::min(in_shape1.num_dimensions(), in_shape2.num_dimensions()) > Window::DimZ);
+ for(size_t d = Window::DimZ; can_collapse && (d < out_shape.num_dimensions()); d++)
+ {
+ can_collapse = (in_shape1[d] == in_shape2[d]);
+ }
+ }
+
+ bool has_collapsed = false;
+ Window collapsed = can_collapse ? window.collapse_if_possible(ICLKernel::window(), Window::DimZ, &has_collapsed) : window;
+
+ const TensorShape &in_shape1_collapsed = has_collapsed ? in_shape1.collapsed_from(Window::DimZ) : in_shape1;
+ const TensorShape &in_shape2_collapsed = has_collapsed ? in_shape2.collapsed_from(Window::DimZ) : in_shape2;
+
+ Window slice = collapsed.first_slice_window_3D();
+ Window slice_src1 = slice.broadcast_if_dimension_le_one(in_shape1_collapsed);
+ Window slice_src2 = slice.broadcast_if_dimension_le_one(in_shape2_collapsed);
+ do
+ {
+ unsigned int idx = 0;
+ add_3D_tensor_argument(idx, src_0, slice_src1);
+ add_3D_tensor_argument(idx, src_1, slice_src2);
+ add_3D_tensor_argument(idx, dst, slice);
+
+ enqueue(queue, *this, slice, lws_hint());
+ ARM_COMPUTE_UNUSED(collapsed.slide_window_slice_3D(slice_src1));
+ ARM_COMPUTE_UNUSED(collapsed.slide_window_slice_3D(slice_src2));
+ }
+ while(collapsed.slide_window_slice_3D(slice));
+}
+
+/** Logical binary */
+
+void ClLogicalBinaryKernel::configure(const ClCompileContext &compile_context, LogicalOperation op, ITensorInfo *src1, ITensorInfo *src2, ITensorInfo *dst)
+{
+ ARM_COMPUTE_ERROR_ON_NULLPTR(src1, src2, dst);
+ ARM_COMPUTE_ERROR_THROW_ON(ClLogicalBinaryKernel::validate(op, src1, src2, dst));
+ _op = op;
+ configure_common(compile_context, src1, src2, dst);
+}
+
+Status ClLogicalBinaryKernel::validate(LogicalOperation op, const ITensorInfo *src1, const ITensorInfo *src2, const ITensorInfo *dst)
+{
+ ARM_COMPUTE_UNUSED(op);
+ ARM_COMPUTE_ASSERT(op != LogicalOperation::Unknown && op != LogicalOperation::Not);
+ ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src1, src2, dst);
+
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(src1, 1, DataType::U8);
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src1, src2);
+
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_with_arithmetic_rules(*src1, *src2, *dst));
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window_for_logical_binary_operators(*src1->clone(), *src2->clone(), *dst->clone()).first);
+
+ return Status{};
+}
+
+std::string ClLogicalBinaryKernel::name()
+{
+ switch(_op)
+ {
+ case LogicalOperation::And:
+ return "AND";
+ case LogicalOperation::Or:
+ return "OR";
+ case LogicalOperation::Not:
+ /* fall through */
+ default:
+ ARM_COMPUTE_ASSERT(true);
+ }
+ return "";
+}
+
+std::pair<Status, Window> ClLogicalBinaryKernel::validate_and_configure_window(ITensorInfo &src1, ITensorInfo &src2, ITensorInfo &dst)
+{
+ return validate_and_configure_window_for_logical_binary_operators(src1, src2, dst);
+}
+
+CLBuildOptions ClLogicalBinaryKernel::generate_build_options(const ITensorInfo &src1, const ITensorInfo &src2, const ITensorInfo &dst)
+{
+ // The arithmetic utility functions can be share
+ return generate_build_options_with_arithmetic_rules(src1, src2, dst, name());
+}
+
+std::string ClLogicalBinaryKernel::generate_id_for_tuning(const std::string &kernel_name, const ITensorInfo &src1, const ITensorInfo &dst)
+{
+ return generate_id_for_tuning_common(kernel_name, src1, dst);
+}
+
+/** Arithmetic operations with saturation*/
+void ClSaturatedArithmeticKernel::configure(const ClCompileContext &compile_context, ArithmeticOperation op, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output,
+ const ConvertPolicy &policy,
+ const ActivationLayerInfo &act_info)
+{
+ ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output);
+ ARM_COMPUTE_ERROR_THROW_ON(ClSaturatedArithmeticKernel::validate(op, input1, input2, output, policy, act_info));
+ auto padding_info = get_padding_info({ input1, input2, output });
+
+ _policy = policy;
+ _op = op;
+ _act_info = act_info;
+ configure_common(compile_context, input1, input2, output);
+ ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info));
+}
+
+Status ClSaturatedArithmeticKernel::validate(ArithmeticOperation op, const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, const ConvertPolicy &policy,
+ const ActivationLayerInfo &act_info)
+{
+ ARM_COMPUTE_UNUSED(op, policy);
+ ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input1, input2, output);
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_with_arithmetic_rules(*input1, *input2, *output));
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window_for_arithmetic_operators(*input1->clone(), *input2->clone(), *output->clone()).first);
+ ARM_COMPUTE_RETURN_ERROR_ON(act_info.enabled() && !is_data_type_float(output->data_type()));
+
+ return Status{};
+}
+
+std::pair<Status, Window> ClSaturatedArithmeticKernel::validate_and_configure_window(ITensorInfo &input1, ITensorInfo &input2, ITensorInfo &output)
+{
+ return validate_and_configure_window_for_arithmetic_operators(input1, input2, output);
+}
+
+CLBuildOptions ClSaturatedArithmeticKernel::generate_build_options(const ITensorInfo &input1, const ITensorInfo &input2, const ITensorInfo &output)
+{
+ const bool has_float_out = is_data_type_float(output.data_type());
+ auto build_options = generate_build_options_with_arithmetic_rules(input1, input2, output, name());
+ build_options.add_option((_policy == ConvertPolicy::WRAP || has_float_out) ? "-DWRAP" : "-DSATURATE");
+ return build_options;
+}
+
+std::string ClSaturatedArithmeticKernel::generate_id_for_tuning(const std::string &kernel_name, const ITensorInfo &input1, const ITensorInfo &output)
+{
+ auto config_id = generate_id_for_tuning_common(kernel_name, input1, output);
+ config_id += (_policy == ConvertPolicy::WRAP) ? "_wrap_" : "_saturate_";
+ config_id += lower_string(string_from_data_layout(input1.data_layout()));
+ return config_id;
+}
+
+std::string ClSaturatedArithmeticKernel::name()
+{
+ return supported_sat_arithmetic_ops[_op];
+}
+
+/** Arithmetic operations*/
+void ClArithmeticKernel::configure(const ClCompileContext &compile_context, ArithmeticOperation op, ITensorInfo *src1, ITensorInfo *src2, ITensorInfo *dst,
+ const ActivationLayerInfo &act_info)
+{
+ ARM_COMPUTE_ERROR_ON_NULLPTR(src1, src2, dst);
+ ARM_COMPUTE_ERROR_THROW_ON(ClArithmeticKernel::validate(op, src1, src2, dst, act_info));
+ auto padding_info = get_padding_info({ src1, src2, dst });
+
+ _op = op;
+ _act_info = act_info;
+ configure_common(compile_context, src1, src2, dst);
+ ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info));
+}
+
+Status ClArithmeticKernel::validate(ArithmeticOperation op, const ITensorInfo *src1, const ITensorInfo *src2, const ITensorInfo *dst, const ActivationLayerInfo &act_info)
+{
+ ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src1, src2, dst);
+ if(op == ArithmeticOperation::DIV || op == ArithmeticOperation::POWER)
+ {
+ // Division and Power operators don't support integer arithmetic
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_with_float_only_supported_rules(*src1, *src2, *dst));
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window_for_division(*src1->clone(), *src2->clone(), *dst->clone()).first);
+ }
+ else
+ {
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_with_arithmetic_rules(*src1, *src2, *dst));
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window_for_arithmetic_operators(*src1->clone(), *src2->clone(), *dst->clone()).first);
+ }
+ ARM_COMPUTE_RETURN_ERROR_ON(act_info.enabled() && !is_data_type_float(dst->data_type()));
+
+ return Status{};
+}
+std::pair<Status, Window> ClArithmeticKernel::validate_and_configure_window(ITensorInfo &src1, ITensorInfo &src2, ITensorInfo &dst)
+{
+ if(_op == ArithmeticOperation::DIV || _op == ArithmeticOperation::POWER)
+ {
+ // Division and Power operators don't support integer arithmetic
+ return validate_and_configure_window_for_division(src1, src2, dst);
+ }
+ else
+ {
+ return validate_and_configure_window_for_arithmetic_operators(src1, src2, dst);
+ }
+}
+
+CLBuildOptions ClArithmeticKernel::generate_build_options(const ITensorInfo &src1, const ITensorInfo &src2, const ITensorInfo &dst)
+{
+ return generate_build_options_with_arithmetic_rules(src1, src2, dst, name());
+}
+std::string ClArithmeticKernel::generate_id_for_tuning(const std::string &kernel_name, const ITensorInfo &src1, const ITensorInfo &dst)
+{
+ return generate_id_for_tuning_common(kernel_name, src1, dst);
+}
+
+std::string ClArithmeticKernel::name()
+{
+ return supported_arithmetic_ops[_op];
+}
+} // namespace kernels
+} // namespace opencl
+} // namespace arm_compute
diff --git a/src/core/gpu/cl/kernels/ClElementwiseKernel.h b/src/core/gpu/cl/kernels/ClElementwiseKernel.h
new file mode 100644
index 0000000..4ed8ae7
--- /dev/null
+++ b/src/core/gpu/cl/kernels/ClElementwiseKernel.h
@@ -0,0 +1,219 @@
+/*
+ * Copyright (c) 2018-2021 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 ARM_COMPUTE_CL_ELEMENTWISE_KERNEL_H
+#define ARM_COMPUTE_CL_ELEMENTWISE_KERNEL_H
+
+#include "src/core/KernelTypes.h"
+#include "src/core/common/Macros.h"
+#include "src/core/gpu/cl/ClCompileContext.h"
+#include "src/core/gpu/cl/IClKernel.h"
+
+namespace arm_compute
+{
+namespace opencl
+{
+namespace kernels
+{
+/** Interface for an element-wise operation kernel
+ *
+ * Element-wise operation is computed by:
+ * @f[ dst(x,y) = OP(src1(x,y), src2(x,y))@f]
+ *
+ */
+class ClElementwiseKernel : public IClKernel
+{
+public:
+ /** Default constructor */
+ ClElementwiseKernel() = default;
+ ARM_COMPUTE_DISALLOW_COPY_ALLOW_MOVE(ClElementwiseKernel);
+
+ // Inherited methods overridden:
+ void run_op(ITensorPack &tensors, const Window &window, ::cl::CommandQueue &queue) override;
+
+protected:
+ /** The name of the operation */
+ virtual std::string name() = 0;
+
+ /** Configure kernel for a given list of arguments
+ *
+ * @param[in] src1 First source tensor info. Data types supported: U8/S8/QASYMM8/QASYMM8_SIGNED/U16/S16/F16/U32/S32/F32.
+ * @param[in] src2 Second source tensor info. Data types supported: same as @p src1.
+ * @param[in] dst Destination tensor info. Data types supported: same as @p src1.
+ *
+ * @return a pair of Status and Window
+ */
+ virtual std::pair<Status, Window> validate_and_configure_window(ITensorInfo &src1, ITensorInfo &src2, ITensorInfo &dst) = 0;
+
+ /** Generate the build options for the specific kernel
+ *
+ * @reutrn a CLBuildOptions struct
+ */
+ virtual CLBuildOptions generate_build_options(const ITensorInfo &src1, const ITensorInfo &src2, const ITensorInfo &dst) = 0;
+
+ /** Generate the identifier for tuning
+ *
+ * @reutrn a string
+ */
+ virtual std::string generate_id_for_tuning(const std::string &kernel_name, const ITensorInfo &src1, const ITensorInfo &dst) = 0;
+
+ /** Commmon configure function for element-wise operators with no additional options (e.g., Div, Min, Max, SquaredDiff)
+ *
+ */
+ void configure_common(ITensorInfo *src1, ITensorInfo *src2, ITensorInfo *dst);
+ /** Commmon configure function for element-wise operators with no additional options (e.g., Div, Min, Max, SquaredDiff)
+ *
+ */
+ void configure_common(const ClCompileContext &compile_context, ITensorInfo *src1, ITensorInfo *src2, ITensorInfo *dst);
+
+ ActivationLayerInfo _act_info{};
+
+private:
+ const ITensorInfo *_src1{ nullptr }; /**< Source tensor info 1 */
+ const ITensorInfo *_src2{ nullptr }; /**< Source tensor info 2 */
+ ITensorInfo *_dst{ nullptr }; /**< Destination tensor info */
+};
+
+class ClLogicalBinaryKernel : public ClElementwiseKernel
+{
+public:
+ /** Default constructor */
+ ClLogicalBinaryKernel() = default;
+ ARM_COMPUTE_DISALLOW_COPY_ALLOW_MOVE(ClLogicalBinaryKernel);
+ /** Function to configure kernel
+ *
+ * @param[in] compile_context The compile context to be used.
+ * @param[in] op Logical binary operation to be executed.
+ * @param[in] src1 First source tensor info. Data types supported: U8.
+ * @param[in] src2 Second source tensor info. Data types supported: same as @p src1.
+ * @param[in] dst Destination tensor info. Data types supported: same as @p src1.
+ */
+ void configure(const ClCompileContext &compile_context, LogicalOperation op, ITensorInfo *src1, ITensorInfo *src2, ITensorInfo *dst);
+ /** Static function to check if the given configuration is valid for this kernel
+ *
+ * @param[in] op Logical binary operation to be executed.
+ * @param[in] src1 First source tensor info. Data types supported: U8.
+ * @param[in] src2 Second source tensor info. Data types supported: same as @p src1.
+ * @param[in] dst Destination tensor info. Data types supported: same as @p src1.
+ */
+ static Status validate(LogicalOperation op, const ITensorInfo *src1, const ITensorInfo *src2, const ITensorInfo *dst);
+
+private:
+ // Inherited methods overridden:
+ std::string name() override;
+ std::pair<Status, Window> validate_and_configure_window(ITensorInfo &src1, ITensorInfo &src2, ITensorInfo &dst) override;
+ CLBuildOptions generate_build_options(const ITensorInfo &src1, const ITensorInfo &src2, const ITensorInfo &dst) override;
+ std::string generate_id_for_tuning(const std::string &kernel_name, const ITensorInfo &src1, const ITensorInfo &dst) override;
+
+ LogicalOperation _op{ LogicalOperation::Unknown };
+};
+
+/** Addition operation */
+class ClSaturatedArithmeticKernel : public ClElementwiseKernel
+{
+public:
+ ClSaturatedArithmeticKernel() = default;
+ ARM_COMPUTE_DISALLOW_COPY_ALLOW_MOVE(ClSaturatedArithmeticKernel);
+ /** Static function to check if given info will lead to a valid configuration of @ref ClSaturatedArithmeticKernel
+ *
+ * @param[in] compile_context The compile context to be used.
+ * @param[in] op Arithmetic operation to be executed.
+ * @param[in] input1 First tensor input info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/F16/S32/F32.
+ * @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.
+ * @param[in] policy Policy to use to handle overflow.
+ * @param[in] act_info (Optional) Activation layer information in case of a fused activation.
+ */
+ void configure(const ClCompileContext &compile_context, ArithmeticOperation op, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output, const ConvertPolicy &policy,
+ const ActivationLayerInfo &act_info = ActivationLayerInfo());
+
+ /** Static function to check if given info will lead to a valid configuration of @ref ClSaturatedArithmeticKernel
+ *
+ * @param[in] op Arithmetic operation to be executed.
+ * @param[in] input1 First tensor input info info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/F16/S32/F32.
+ * @param[in] input2 Second tensor input info info. Data types supported: Same as @p input1.
+ * @param[in] output Output tensor info info. Data types supported: Same as @p input1.
+ * @param[in] policy Policy to use to handle overflow.
+ * @param[in] act_info (Optional) Activation layer information in case of a fused activation.
+ *
+ * @return a Status
+ */
+ static Status validate(ArithmeticOperation op, const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, const ConvertPolicy &policy,
+ const ActivationLayerInfo &act_info = ActivationLayerInfo());
+
+protected:
+ // Inherited methods overridden:
+ std::string name() override;
+ std::pair<Status, Window> validate_and_configure_window(ITensorInfo &input1, ITensorInfo &input2, ITensorInfo &output) override;
+ CLBuildOptions generate_build_options(const ITensorInfo &input1, const ITensorInfo &input2, const ITensorInfo &output) override;
+ std::string generate_id_for_tuning(const std::string &kernel_name, const ITensorInfo &input1, const ITensorInfo &output) override;
+
+private:
+ ConvertPolicy _policy{};
+ ArithmeticOperation _op{};
+};
+
+class ClArithmeticKernel : public ClElementwiseKernel
+{
+public:
+ ClArithmeticKernel() = default;
+ ARM_COMPUTE_DISALLOW_COPY_ALLOW_MOVE(ClArithmeticKernel);
+
+ /** Static function to check if given info will lead to a valid configuration of @ref ClArithmeticKernel
+ *
+ * @param[in] compile_context The compile context to be used.
+ * @param[in] op Arithmetic operation to be executed.
+ * @param[in] src1 First source tensor info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/F16/S32/F32.
+ * @param[in] src2 Second source tensor info. Data types supported: same as @p src1.
+ * @param[in] dst Destination tensor info. Data types supported: same as @p src1.
+ * @param[in] act_info (Optional) Activation layer information in case of a fused activation.
+ */
+ void configure(const ClCompileContext &compile_context, ArithmeticOperation op, ITensorInfo *src1, ITensorInfo *src2, ITensorInfo *dst,
+ const ActivationLayerInfo &act_info = ActivationLayerInfo());
+
+ /** Static function to check if given info will lead to a valid configuration of @ref ClArithmeticKernel
+ *
+ * @param[in] op Arithmetic operation to be executed.
+ * @param[in] src1 First source tensor info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/F16/S32/F32.
+ * @param[in] src2 Second source tensor info. Data types supported: same as @p src1.
+ * @param[in] dst Destination tensor info. Data types supported: same as @p src1.
+ * @param[in] act_info (Optional) Activation layer information in case of a fused activation.
+ *
+ * @return a Status
+ */
+ static Status validate(ArithmeticOperation op, const ITensorInfo *src1, const ITensorInfo *src2, const ITensorInfo *dst, const ActivationLayerInfo &act_info = ActivationLayerInfo());
+
+protected:
+ // Inherited methods overridden:
+ std::string name() override;
+ std::pair<Status, Window> validate_and_configure_window(ITensorInfo &src1, ITensorInfo &src2, ITensorInfo &dst) override;
+ CLBuildOptions generate_build_options(const ITensorInfo &src1, const ITensorInfo &src2, const ITensorInfo &dst) override;
+ std::string generate_id_for_tuning(const std::string &kernel_name, const ITensorInfo &src1, const ITensorInfo &dst) override;
+
+private:
+ ArithmeticOperation _op{};
+};
+} // namespace kernels
+} // namespace opencl
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_CL_ELEMENTWISE_KERNEL_H */
diff --git a/src/runtime/CL/functions/CLElementwiseOperations.cpp b/src/runtime/CL/functions/CLElementwiseOperations.cpp
index a72e957..638990e 100644
--- a/src/runtime/CL/functions/CLElementwiseOperations.cpp
+++ b/src/runtime/CL/functions/CLElementwiseOperations.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2018-2020 Arm Limited.
+ * Copyright (c) 2018-2021 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -25,7 +25,9 @@
#include "arm_compute/core/CL/ICLTensor.h"
#include "arm_compute/runtime/CL/CLScheduler.h"
-#include "src/core/CL/kernels/CLElementwiseOperationKernel.h"
+#include "src/core/gpu/cl/kernels/ClElementwiseKernel.h"
+
+#include "src/runtime/gpu/cl/operators/ClAdd.h"
#include <utility>
@@ -33,34 +35,13 @@
{
namespace experimental
{
-CLArithmeticAddition::CLArithmeticAddition()
-{
-}
-
-void CLArithmeticAddition::configure(const CLCompileContext &compile_context, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output, ConvertPolicy policy, const ActivationLayerInfo &act_info)
-{
- auto k = std::make_unique<CLSaturatedArithmeticOperationKernel>();
- k->configure(compile_context, ArithmeticOperation::ADD, input1, input2, output, policy, act_info);
- _kernel = std::move(k);
-}
-
-Status CLArithmeticAddition::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, ConvertPolicy policy, const ActivationLayerInfo &act_info)
-{
- return CLSaturatedArithmeticOperationKernel::validate(ArithmeticOperation::ADD, input1, input2, output, policy, act_info);
-}
-
-void CLArithmeticAddition::run(ITensorPack &tensors)
-{
- ICLOperator::run(tensors);
-}
-
CLArithmeticSubtraction::CLArithmeticSubtraction()
{
}
void CLArithmeticSubtraction::configure(const CLCompileContext &compile_context, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output, ConvertPolicy policy,
const ActivationLayerInfo &act_info)
{
- auto k = std::make_unique<CLSaturatedArithmeticOperationKernel>();
+ auto k = std::make_unique<arm_compute::opencl::kernels::ClSaturatedArithmeticKernel>();
k->configure(compile_context, ArithmeticOperation::SUB, input1, input2, output, policy, act_info);
_kernel = std::move(k);
}
@@ -68,7 +49,7 @@
Status CLArithmeticSubtraction::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, ConvertPolicy policy, const ActivationLayerInfo &act_info)
{
ARM_COMPUTE_UNUSED(policy);
- return CLSaturatedArithmeticOperationKernel::validate(ArithmeticOperation::SUB, input1, input2, output, policy, act_info);
+ return arm_compute::opencl::kernels::ClSaturatedArithmeticKernel::validate(ArithmeticOperation::SUB, input1, input2, output, policy, act_info);
}
void CLArithmeticSubtraction::run(ITensorPack &tensors)
@@ -82,14 +63,14 @@
void CLArithmeticDivision::configure(const CLCompileContext &compile_context, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output, const ActivationLayerInfo &act_info)
{
- auto k = std::make_unique<CLArithmeticOperationKernel>();
+ auto k = std::make_unique<arm_compute::opencl::kernels::ClArithmeticKernel>();
k->configure(compile_context, ArithmeticOperation::DIV, input1, input2, output, act_info);
_kernel = std::move(k);
}
Status CLArithmeticDivision::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, const ActivationLayerInfo &act_info)
{
- return CLArithmeticOperationKernel::validate(ArithmeticOperation::DIV, input1, input2, output, act_info);
+ return arm_compute::opencl::kernels::ClArithmeticKernel::validate(ArithmeticOperation::DIV, input1, input2, output, act_info);
}
void CLArithmeticDivision::run(ITensorPack &tensors)
@@ -103,14 +84,14 @@
void CLElementwiseMax::configure(const CLCompileContext &compile_context, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output, const ActivationLayerInfo &act_info)
{
- auto k = std::make_unique<CLArithmeticOperationKernel>();
+ auto k = std::make_unique<arm_compute::opencl::kernels::ClArithmeticKernel>();
k->configure(compile_context, ArithmeticOperation::MAX, input1, input2, output, act_info);
_kernel = std::move(k);
}
Status CLElementwiseMax::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, const ActivationLayerInfo &act_info)
{
- return CLArithmeticOperationKernel::validate(ArithmeticOperation::MAX, input1, input2, output, act_info);
+ return arm_compute::opencl::kernels::ClArithmeticKernel::validate(ArithmeticOperation::MAX, input1, input2, output, act_info);
}
void CLElementwiseMax::run(ITensorPack &tensors)
@@ -124,14 +105,14 @@
void CLElementwiseMin::configure(const CLCompileContext &compile_context, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output, const ActivationLayerInfo &act_info)
{
- auto k = std::make_unique<CLArithmeticOperationKernel>();
+ auto k = std::make_unique<arm_compute::opencl::kernels::ClArithmeticKernel>();
k->configure(compile_context, ArithmeticOperation::MIN, input1, input2, output, act_info);
_kernel = std::move(k);
}
Status CLElementwiseMin::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, const ActivationLayerInfo &act_info)
{
- return CLArithmeticOperationKernel::validate(ArithmeticOperation::MIN, input1, input2, output, act_info);
+ return arm_compute::opencl::kernels::ClArithmeticKernel::validate(ArithmeticOperation::MIN, input1, input2, output, act_info);
}
void CLElementwiseMin::run(ITensorPack &tensors)
@@ -145,14 +126,14 @@
void CLElementwiseSquaredDiff::configure(const CLCompileContext &compile_context, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output, const ActivationLayerInfo &act_info)
{
- auto k = std::make_unique<CLArithmeticOperationKernel>();
+ auto k = std::make_unique<arm_compute::opencl::kernels::ClArithmeticKernel>();
k->configure(compile_context, ArithmeticOperation::SQUARED_DIFF, input1, input2, output, act_info);
_kernel = std::move(k);
}
Status CLElementwiseSquaredDiff::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, const ActivationLayerInfo &act_info)
{
- return CLArithmeticOperationKernel::validate(ArithmeticOperation::SQUARED_DIFF, input1, input2, output, act_info);
+ return arm_compute::opencl::kernels::ClArithmeticKernel::validate(ArithmeticOperation::SQUARED_DIFF, input1, input2, output, act_info);
}
void CLElementwiseSquaredDiff::run(ITensorPack &tensors)
@@ -166,14 +147,14 @@
void CLElementwisePower::configure(const CLCompileContext &compile_context, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output, const ActivationLayerInfo &act_info)
{
- auto k = std::make_unique<CLArithmeticOperationKernel>();
+ auto k = std::make_unique<arm_compute::opencl::kernels::ClArithmeticKernel>();
k->configure(compile_context, ArithmeticOperation::POWER, input1, input2, output, act_info);
_kernel = std::move(k);
}
Status CLElementwisePower::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, const ActivationLayerInfo &act_info)
{
- return CLArithmeticOperationKernel::validate(ArithmeticOperation::POWER, input1, input2, output, act_info);
+ return arm_compute::opencl::kernels::ClArithmeticKernel::validate(ArithmeticOperation::POWER, input1, input2, output, act_info);
}
void CLElementwisePower::run(ITensorPack &tensors)
@@ -181,13 +162,12 @@
ICLOperator::run(tensors);
}
} // namespace experimental
-
struct CLArithmeticAddition::Impl
{
- const ICLTensor *src_0{ nullptr };
- const ICLTensor *src_1{ nullptr };
- ICLTensor *dst{ nullptr };
- std::unique_ptr<experimental::CLArithmeticAddition> op{ nullptr };
+ const ICLTensor *src_0{ nullptr };
+ const ICLTensor *src_1{ nullptr };
+ ICLTensor *dst{ nullptr };
+ std::unique_ptr<opencl::ClAdd> op{ nullptr };
};
CLArithmeticAddition::CLArithmeticAddition()
@@ -209,13 +189,13 @@
_impl->src_0 = input1;
_impl->src_1 = input2;
_impl->dst = output;
- _impl->op = std::make_unique<experimental::CLArithmeticAddition>();
+ _impl->op = std::make_unique<opencl::ClAdd>();
_impl->op->configure(compile_context, input1->info(), input2->info(), output->info(), policy, act_info);
}
Status CLArithmeticAddition::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, ConvertPolicy policy, const ActivationLayerInfo &act_info)
{
- return experimental::CLArithmeticAddition::validate(input1, input2, output, policy, act_info);
+ return opencl::ClAdd::validate(input1, input2, output, policy, act_info);
}
void CLArithmeticAddition::run()
diff --git a/src/runtime/CL/functions/CLLogicalAnd.cpp b/src/runtime/CL/functions/CLLogicalAnd.cpp
index f1c5365..98c98ab 100644
--- a/src/runtime/CL/functions/CLLogicalAnd.cpp
+++ b/src/runtime/CL/functions/CLLogicalAnd.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2020 Arm Limited.
+ * Copyright (c) 2020-2021 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -23,7 +23,7 @@
*/
#include "arm_compute/runtime/CL/functions/CLLogicalAnd.h"
#include "arm_compute/core/CL/ICLTensor.h"
-#include "src/core/CL/kernels/CLElementwiseOperationKernel.h"
+#include "src/core/gpu/cl/kernels/ClElementwiseKernel.h"
#include <utility>
@@ -33,14 +33,14 @@
{
void CLLogicalAnd::configure(const CLCompileContext &compile_context, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output)
{
- auto k = std::make_unique<CLLogicalBinaryKernel>();
- k->configure(compile_context, kernels::LogicalOperation::And, input1, input2, output);
+ auto k = std::make_unique<arm_compute::opencl::kernels::ClLogicalBinaryKernel>();
+ k->configure(compile_context, LogicalOperation::And, input1, input2, output);
_kernel = std::move(k);
}
Status CLLogicalAnd::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output)
{
- return CLLogicalBinaryKernel::validate(kernels::LogicalOperation::And, input1, input2, output);
+ return arm_compute::opencl::kernels::ClLogicalBinaryKernel::validate(LogicalOperation::And, input1, input2, output);
}
void CLLogicalAnd::run(ITensorPack &tensors)
diff --git a/src/runtime/CL/functions/CLLogicalOr.cpp b/src/runtime/CL/functions/CLLogicalOr.cpp
index 8c6087e..897963a 100644
--- a/src/runtime/CL/functions/CLLogicalOr.cpp
+++ b/src/runtime/CL/functions/CLLogicalOr.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2020 Arm Limited.
+ * Copyright (c) 2020-2021 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -23,7 +23,7 @@
*/
#include "arm_compute/runtime/CL/functions/CLLogicalOr.h"
#include "arm_compute/core/CL/ICLTensor.h"
-#include "src/core/CL/kernels/CLElementwiseOperationKernel.h"
+#include "src/core/gpu/cl/kernels/ClElementwiseKernel.h"
#include <utility>
@@ -33,14 +33,14 @@
{
void CLLogicalOr::configure(const CLCompileContext &compile_context, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output)
{
- auto k = std::make_unique<CLLogicalBinaryKernel>();
- k->configure(compile_context, kernels::LogicalOperation::Or, input1, input2, output);
+ auto k = std::make_unique<arm_compute::opencl::kernels::ClLogicalBinaryKernel>();
+ k->configure(compile_context, LogicalOperation::Or, input1, input2, output);
_kernel = std::move(k);
}
Status CLLogicalOr::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output)
{
- return CLLogicalBinaryKernel::validate(kernels::LogicalOperation::Or, input1, input2, output);
+ return arm_compute::opencl::kernels::ClLogicalBinaryKernel::validate(LogicalOperation::Or, input1, input2, output);
}
void CLLogicalOr::run(ITensorPack &tensors)
diff --git a/src/runtime/CL/functions/CLPReluLayer.cpp b/src/runtime/CL/functions/CLPReluLayer.cpp
index 876b5de..74286d4 100644
--- a/src/runtime/CL/functions/CLPReluLayer.cpp
+++ b/src/runtime/CL/functions/CLPReluLayer.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2019-2020 Arm Limited.
+ * Copyright (c) 2019-2021 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -21,7 +21,7 @@
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
-#include "src/core/CL/kernels/CLElementwiseOperationKernel.h"
+#include "src/core/gpu/cl/kernels/ClElementwiseKernel.h"
#include "arm_compute/core/CL/ICLTensor.h"
#include "arm_compute/runtime/CL/CLScheduler.h"
@@ -37,14 +37,14 @@
void CLPReluLayer::configure(const CLCompileContext &compile_context, ITensorInfo *input, ITensorInfo *alpha, ITensorInfo *output)
{
- auto k = std::make_unique<CLArithmeticOperationKernel>();
+ auto k = std::make_unique<arm_compute::opencl::kernels::ClArithmeticKernel>();
k->configure(compile_context, ArithmeticOperation::PRELU, input, alpha, output);
_kernel = std::move(k);
}
Status CLPReluLayer::validate(const ITensorInfo *input, const ITensorInfo *alpha, const ITensorInfo *output)
{
- return CLArithmeticOperationKernel::validate(ArithmeticOperation::PRELU, input, alpha, output);
+ return arm_compute::opencl::kernels::ClArithmeticKernel::validate(ArithmeticOperation::PRELU, input, alpha, output);
}
void CLPReluLayer::run(ITensorPack &tensors)
diff --git a/src/runtime/NEON/functions/NELogical.cpp b/src/runtime/NEON/functions/NELogical.cpp
index 190998b..674ba40 100644
--- a/src/runtime/NEON/functions/NELogical.cpp
+++ b/src/runtime/NEON/functions/NELogical.cpp
@@ -50,7 +50,7 @@
ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output);
_impl->kernel = std::make_unique<kernels::NELogicalKernel>();
- _impl->kernel->configure(input1->info(), input2->info(), output->info(), kernels::LogicalOperation::And);
+ _impl->kernel->configure(input1->info(), input2->info(), output->info(), LogicalOperation::And);
_impl->pack = ITensorPack();
_impl->pack.add_tensor(TensorType::ACL_SRC_0, input1);
@@ -60,7 +60,7 @@
Status NELogicalAnd::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output)
{
- return kernels::NELogicalKernel::validate(input1, input2, output, kernels::LogicalOperation::And);
+ return kernels::NELogicalKernel::validate(input1, input2, output, LogicalOperation::And);
}
void NELogicalAnd::run()
@@ -83,7 +83,7 @@
ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output);
_impl->kernel = std::make_unique<kernels::NELogicalKernel>();
- _impl->kernel->configure(input1->info(), input2->info(), output->info(), kernels::LogicalOperation::Or);
+ _impl->kernel->configure(input1->info(), input2->info(), output->info(), LogicalOperation::Or);
_impl->pack = ITensorPack();
_impl->pack.add_tensor(TensorType::ACL_SRC_0, input1);
@@ -93,7 +93,7 @@
Status NELogicalOr::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output)
{
- return kernels::NELogicalKernel::validate(input1, input2, output, kernels::LogicalOperation::Or);
+ return kernels::NELogicalKernel::validate(input1, input2, output, LogicalOperation::Or);
}
void NELogicalOr::run()
@@ -116,7 +116,7 @@
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
_impl->kernel = std::make_unique<kernels::NELogicalKernel>();
- _impl->kernel->configure(input->info(), nullptr, output->info(), kernels::LogicalOperation::Not);
+ _impl->kernel->configure(input->info(), nullptr, output->info(), LogicalOperation::Not);
_impl->pack = ITensorPack();
_impl->pack.add_tensor(TensorType::ACL_SRC_0, input);
@@ -125,7 +125,7 @@
Status NELogicalNot::validate(const ITensorInfo *input, const ITensorInfo *output)
{
- return kernels::NELogicalKernel::validate(input, nullptr, output, kernels::LogicalOperation::Not);
+ return kernels::NELogicalKernel::validate(input, nullptr, output, LogicalOperation::Not);
}
void NELogicalNot::run()
diff --git a/src/runtime/gpu/cl/operators/ClAdd.cpp b/src/runtime/gpu/cl/operators/ClAdd.cpp
new file mode 100644
index 0000000..01f550f
--- /dev/null
+++ b/src/runtime/gpu/cl/operators/ClAdd.cpp
@@ -0,0 +1,47 @@
+/*
+ * Copyright (c) 2021 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/runtime/gpu/cl/operators/ClAdd.h"
+
+#include "src/core/gpu/cl/ClCompileContext.h"
+#include "src/core/gpu/cl/kernels/ClElementwiseKernel.h"
+
+namespace arm_compute
+{
+namespace opencl
+{
+void ClAdd::configure(const ClCompileContext &compile_context, ITensorInfo *src1, ITensorInfo *src2, ITensorInfo *dst,
+ ConvertPolicy policy, const ActivationLayerInfo &act_info)
+{
+ auto k = std::make_unique<kernels::ClSaturatedArithmeticKernel>();
+ k->configure(compile_context, ArithmeticOperation::ADD, src1, src2, dst, policy, act_info);
+ _kernel = std::move(k);
+}
+
+Status ClAdd::validate(const ITensorInfo *src1, const ITensorInfo *src2, const ITensorInfo *dst,
+ ConvertPolicy policy, const ActivationLayerInfo &act_info)
+{
+ return kernels::ClSaturatedArithmeticKernel::validate(ArithmeticOperation::ADD, src1, src2, dst, policy, act_info);
+}
+} // namespace opencl
+} // namespace arm_compute
diff --git a/src/runtime/gpu/cl/operators/ClAdd.h b/src/runtime/gpu/cl/operators/ClAdd.h
new file mode 100644
index 0000000..2854c16
--- /dev/null
+++ b/src/runtime/gpu/cl/operators/ClAdd.h
@@ -0,0 +1,100 @@
+/*
+ * Copyright (c) 2021 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 ARM_COMPUTE_CL_ADD_H
+#define ARM_COMPUTE_CL_ADD_H
+
+#include "src/core/gpu/cl/ClCompileContext.h"
+#include "src/runtime/gpu/cl/IClOperator.h"
+
+namespace arm_compute
+{
+namespace opencl
+{
+/** Basic function to run arithmetic addition
+ *
+ * @note The tensor data type for the inputs must be U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/S32/F16/F32.
+ * @note The function performs an arithmetic addition between two tensors.
+ */
+class ClAdd : public IClOperator
+{
+public:
+ /** Default Constructor */
+ ClAdd() = default;
+ /** Configure function for a given list of arguments.
+ *
+ * Valid configurations (src1,src2) -> dst :
+ *
+ * - (U8,U8) -> U8
+ * - (U8,U8) -> S16
+ * - (S16,U8) -> S16
+ * - (U8,S16) -> S16
+ * - (S16,S16) -> S16
+ * - (S32,S32) -> S32
+ * - (F16,F16) -> F16
+ * - (F32,F32) -> F32
+ * - (QASYMM8,QASYMM8) -> QASYMM8
+ * - (QASYMM8_SIGNED,QASYMM8_SIGNED) -> QASYMM8_SIGNED
+ * - (QSYMM16,QSYMM16) -> QSYMM16
+ *
+ * @param[in] compile_context The compile context to be used.
+ * @param[in, out] src1 First source tensor. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/S32/F16/F32.
+ * The source tensor is [in, out] because its TensorInfo might be modified inside the kernel in case of broadcasting of dimension 0.
+ * @param[in, out] src2 Second source tensor. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/S32/F16/F32.
+ * The source tensor is [in, out] because its TensorInfo might be modified inside the kernel in case of broadcasting of dimension 0.
+ * @param[out] dst Destination tensor. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/S32/F16/F32.
+ * @param[in] policy Policy to use to handle overflow.
+ * @param[in] act_info (Optional) Activation layer information in case of a fused activation.
+ */
+ void configure(const ClCompileContext &compile_context, ITensorInfo *src1, ITensorInfo *src2, ITensorInfo *dst, ConvertPolicy policy,
+ const ActivationLayerInfo &act_info = ActivationLayerInfo());
+ /** Static function to check if given info will lead to a valid configuration of @ref ClAdd
+ *
+ * Valid configurations (src1,src2) -> dst :
+ *
+ * - (U8,U8) -> U8
+ * - (U8,U8) -> S16
+ * - (S16,U8) -> S16
+ * - (U8,S16) -> S16
+ * - (S16,S16) -> S16
+ * - (S32,S32) -> S32
+ * - (F16,F16) -> F16
+ * - (F32,F32) -> F32
+ * - (QASYMM8,QASYMM8) -> QASYMM8
+ * - (QASYMM8_SIGNED,QASYMM8_SIGNED) -> QASYMM8_SIGNED
+ * - (QSYMM16,QSYMM16) -> QSYMM16
+ *
+ * @param[in] src1 First source tensor info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/S32/F16/F32.
+ * @param[in] src2 Second source tensor info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/S32/F16/F32.
+ * @param[in] dst Destination tensor info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/S32/F16/F32.
+ * @param[in] policy Policy to use to handle overflow.
+ * @param[in] act_info (Optional) Activation layer information in case of a fused activation.
+ *
+ * @return a status
+ */
+ static Status validate(const ITensorInfo *src1, const ITensorInfo *src2, const ITensorInfo *dst, ConvertPolicy policy,
+ const ActivationLayerInfo &act_info = ActivationLayerInfo());
+};
+} // namespace opencl
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_CL_ADD_H */
diff --git a/tests/validation/reference/Logical.cpp b/tests/validation/reference/Logical.cpp
index 099abf6..aab57d9 100644
--- a/tests/validation/reference/Logical.cpp
+++ b/tests/validation/reference/Logical.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2020 Arm Limited.
+ * Copyright (c) 2020-2021 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -34,18 +34,18 @@
namespace reference
{
template <typename T>
-T logical_binary_op(arm_compute::kernels::LogicalOperation op, T src1, T src2)
+T logical_binary_op(arm_compute::LogicalOperation op, T src1, T src2)
{
switch(op)
{
- case arm_compute::kernels::LogicalOperation::And:
+ case arm_compute::LogicalOperation::And:
return src1 && src2;
- case arm_compute::kernels::LogicalOperation::Or:
+ case arm_compute::LogicalOperation::Or:
return src1 || src2;
// The following operators are either invalid or not binary operator
- case arm_compute::kernels::LogicalOperation::Not:
+ case arm_compute::LogicalOperation::Not:
// fall through
- case arm_compute::kernels::LogicalOperation::Unknown:
+ case arm_compute::LogicalOperation::Unknown:
// fall through
default:
ARM_COMPUTE_ASSERT(true);
@@ -57,7 +57,7 @@
struct BroadcastUnroll
{
template <typename T>
- static void unroll(arm_compute::kernels::LogicalOperation op, const SimpleTensor<T> &src1, const SimpleTensor<T> &src2, SimpleTensor<T> &dst,
+ static void unroll(arm_compute::LogicalOperation op, const SimpleTensor<T> &src1, const SimpleTensor<T> &src2, SimpleTensor<T> &dst,
Coordinates &id_src1, Coordinates &id_src2, Coordinates &id_dst)
{
const bool src1_is_broadcast = (src1.shape()[dim - 1] != dst.shape()[dim - 1]);
@@ -84,7 +84,7 @@
struct BroadcastUnroll<0>
{
template <typename T>
- static void unroll(arm_compute::kernels::LogicalOperation op, const SimpleTensor<T> &src1, const SimpleTensor<T> &src2, SimpleTensor<T> &dst,
+ static void unroll(arm_compute::LogicalOperation op, const SimpleTensor<T> &src1, const SimpleTensor<T> &src2, SimpleTensor<T> &dst,
Coordinates &id_src1, Coordinates &id_src2, Coordinates &id_dst)
{
dst[coord2index(dst.shape(), id_dst)] = logical_binary_op(op, src1[coord2index(src1.shape(), id_src1)], src2[coord2index(src2.shape(), id_src2)]);
@@ -99,7 +99,7 @@
Coordinates id_dst{};
SimpleTensor<T> dst{ TensorShape::broadcast_shape(src1.shape(), src2.shape()), src1.data_type() };
- BroadcastUnroll<Coordinates::num_max_dimensions>::unroll(arm_compute::kernels::LogicalOperation::Or, src1, src2, dst, id_src1, id_src2, id_dst);
+ BroadcastUnroll<Coordinates::num_max_dimensions>::unroll(arm_compute::LogicalOperation::Or, src1, src2, dst, id_src1, id_src2, id_dst);
return dst;
}
@@ -112,7 +112,7 @@
Coordinates id_dst{};
SimpleTensor<T> dst{ TensorShape::broadcast_shape(src1.shape(), src2.shape()), src1.data_type() };
- BroadcastUnroll<Coordinates::num_max_dimensions>::unroll(arm_compute::kernels::LogicalOperation::And, src1, src2, dst, id_src1, id_src2, id_dst);
+ BroadcastUnroll<Coordinates::num_max_dimensions>::unroll(arm_compute::LogicalOperation::And, src1, src2, dst, id_src1, id_src2, id_dst);
return dst;
}