COMPMID-3639: (3RDPARTY_UPDATE) Move CL kernels to src
Change-Id: I10d27db788e5086adae1841e3e2441cd9b76ef84
Signed-off-by: Sang-Hoon Park <sang-hoon.park@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/4310
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
diff --git a/src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.h b/src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.h
new file mode 100644
index 0000000..71d223b
--- /dev/null
+++ b/src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.h
@@ -0,0 +1,122 @@
+/*
+ * Copyright (c) 2017-2020 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_CLGEMMMATRIXMULTIPLYKERNEL_H
+#define ARM_COMPUTE_CLGEMMMATRIXMULTIPLYKERNEL_H
+
+#include "src/core/CL/ICLKernel.h"
+
+namespace arm_compute
+{
+class ICLTensor;
+
+/** OpenCL kernel to multiply two input matrices "A" and "B" and add a martix "C" if provided. All elements of the output matrix will be multiplied by alpha. In case matrix C is passed, it will be added to the previous result.
+ * For the matrix C, the broadcast addition is supported if the flag "broadcast_bias" is set in the GEMMReshapeInfo object
+ *
+ * @note If the input tensors @p input0 and @p input1 have been reshaped respectively with @ref CLGEMMReshapeLHSMatrixKernel" and @ref CLGEMMReshapeRHSMatrixKernel,
+ * the flag @p is_interleaved_transposed must be set to true
+ *
+ * @attention @p input1 tensor must have at least 2 dimensions (matrix)
+ *
+ */
+class CLGEMMMatrixMultiplyKernel : public ICLKernel
+{
+public:
+ /** Default constructor */
+ CLGEMMMatrixMultiplyKernel();
+ /** Prevent instances of this class from being copied (As this class contains pointers) */
+ CLGEMMMatrixMultiplyKernel(const CLGEMMMatrixMultiplyKernel &) = delete;
+ /** Prevent instances of this class from being copied (As this class contains pointers) */
+ CLGEMMMatrixMultiplyKernel &operator=(const CLGEMMMatrixMultiplyKernel &) = delete;
+ /** Allow instances of this class to be moved */
+ CLGEMMMatrixMultiplyKernel(CLGEMMMatrixMultiplyKernel &&) = default;
+ /** Allow instances of this class to be moved */
+ CLGEMMMatrixMultiplyKernel &operator=(CLGEMMMatrixMultiplyKernel &&) = default;
+ /** Initialise the kernel's input, output and alpha
+ *
+ * @param[in] input0 Input tensor containing the Matrix A. Data types supported: F16/F32
+ * @param[in] input1 Input tensor containing the Matrix B. Data type supported: same as @p input0
+ * @param[in] input2 Input tensor containing the Matrix C (bias). Can be nullptr. Data type supported: same as @p input0
+ * @param[out] output Output tensor to store the result of matrix multiplication. Data type supported: same as @p input0
+ * @param[in] alpha Weight of the matrix product
+ * @param[in] beta (Optional) Weight of vector C. Default value is 0. Only beta = 1 is currently supported.
+ * @param[in] is_interleaved_transposed (Optional) True if input0 and input1 have been reshaped respectively using @ref CLGEMMReshapeLHSMatrixKernel and @ref CLGEMMReshapeRHSMatrixKernel
+ * @param[in] reshape_info (Optional) GEMM reshape info. If is_interleaved_transposed = true, this object must contain the information to understand how the matrix A and matrix B have been reshaped
+ * @param[in] fp_mixed_precision (Optional) Use wider accumulators (32 bit instead of 16 for FP16) to improve accuracy
+ * @param[in] activation_info (Optional) Activation to apply after the matrix multiplication
+ *
+ */
+ void configure(const ICLTensor *input0, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, float alpha, float beta = 0.f,
+ bool is_interleaved_transposed = true, const GEMMReshapeInfo &reshape_info = GEMMReshapeInfo(), bool fp_mixed_precision = false, const ActivationLayerInfo &activation_info = ActivationLayerInfo());
+ /** Initialise the kernel's input, output and alpha
+ *
+ * @param[in] compile_context The compile context to be used.
+ * @param[in] input0 Input tensor containing the Matrix A. Data types supported: F16/F32
+ * @param[in] input1 Input tensor containing the Matrix B. Data type supported: same as @p input0
+ * @param[in] input2 Input tensor containing the Matrix C (bias). Can be nullptr. Data type supported: same as @p input0
+ * @param[out] output Output tensor to store the result of matrix multiplication. Data type supported: same as @p input0
+ * @param[in] alpha Weight of the matrix product
+ * @param[in] beta (Optional) Weight of vector C. Default value is 0. Only beta = 1 is currently supported.
+ * @param[in] is_interleaved_transposed (Optional) True if input0 and input1 have been reshaped respectively using @ref CLGEMMReshapeLHSMatrixKernel and @ref CLGEMMReshapeRHSMatrixKernel
+ * @param[in] reshape_info (Optional) GEMM reshape info. If is_interleaved_transposed = true, this object must contain the information to understand how the matrix A and matrix B have been reshaped
+ * @param[in] fp_mixed_precision (Optional) Use wider accumulators (32 bit instead of 16 for FP16) to improve accuracy
+ * @param[in] activation_info (Optional) Activation to apply after the matrix multiplication
+ *
+ */
+ void configure(const CLCompileContext &compile_context, const ICLTensor *input0, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, float alpha, float beta = 0.f,
+ bool is_interleaved_transposed = true, const GEMMReshapeInfo &reshape_info = GEMMReshapeInfo(), bool fp_mixed_precision = false, const ActivationLayerInfo &activation_info = ActivationLayerInfo());
+ /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMMatrixMultiplyKernel
+ *
+ * @param[in] input0 Input tensor containing the Matrix A info. Data types supported: F16/F32
+ * @param[in] input1 Input tensor containing the Matrix B info. Data type supported: same as @p input0
+ * @param[in] input2 Input tensor containing the Matrix C (bias) info. Can be nullptr. Data type supported: same as @p input0
+ * @param[in] output Output tensor to store the result of matrix multiplication. Data type supported: same as @p input0
+ * @param[in] alpha Weight of the matrix product
+ * @param[in] beta Weight of vector C. Default value is 0. Only beta = 1 is currently supported.
+ * @param[in] is_interleaved_transposed True if input0 and input1 have been reshaped respectively using @ref CLGEMMReshapeLHSMatrixKernel and @ref CLGEMMReshapeRHSMatrixKernel
+ * @param[in] reshape_info GEMM reshape info. If is_interleaved_transposed = true, this object must contain the information to understand how the matrix A and matrix B have been reshaped
+ * @param[in] gpu_target GPU Target
+ * @param[in] fp_mixed_precision (Optional) Use wider accumulators (32 bit instead of 16 for FP16) to improve accuracy
+ * @param[in] activation_info (Optional) Activation to apply after the matrix multiplication
+ *
+ * @return a status
+ */
+ static Status validate(const ITensorInfo *input0, const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, float alpha, float beta,
+ bool is_interleaved_transposed, const GEMMReshapeInfo &reshape_info, GPUTarget gpu_target, bool fp_mixed_precision = false, const ActivationLayerInfo &activation_info = ActivationLayerInfo());
+
+ // Inherited methods overridden:
+ void run(const Window &window, cl::CommandQueue &queue) override;
+
+public:
+ const ICLTensor *_input0;
+ const ICLTensor *_input1;
+ const ICLTensor *_input2;
+ ICLTensor *_output;
+ bool _slide_matrix_b;
+ bool _reinterpret_input_as_3d;
+ bool _reinterpret_output_as_3d;
+ bool _add_bias;
+ bool _broadcast_bias;
+};
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_CLGEMMMATRIXMULTIPLYKERNEL_H */