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authorgiuros01 <giuseppe.rossini@arm.com>2019-01-11 14:04:43 +0000
committerGiuseppe Rossini <giuseppe.rossini@arm.com>2019-01-14 12:42:42 +0000
commit1c9efebf4344e8db97e6d9282b2bf48b52090b58 (patch)
tree40c8737a23ff289cb176618d7c16fd4b2d811689 /arm_compute/core/CL
parent685c181d5ac36948f8df22f627ef9b3a74b5f87e (diff)
downloadComputeLibrary-1c9efebf4344e8db97e6d9282b2bf48b52090b58.tar.gz
Issue COMPMID-1835: Remove CLGEMMInterleave4x4Kernel and replace with CLGEMMReshapeLHSMatrixKernel
Change-Id: Id6a1bd78f9b1698b64a004e4adebc41002b15745 Reviewed-on: https://review.mlplatform.org/496 Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Diffstat (limited to 'arm_compute/core/CL')
-rw-r--r--arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyKernel.h8
1 files changed, 4 insertions, 4 deletions
diff --git a/arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyKernel.h b/arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyKernel.h
index ce37787862..797bda86cf 100644
--- a/arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyKernel.h
+++ b/arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyKernel.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2018 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -32,7 +32,7 @@ class ICLTensor;
/** OpenCL kernel to multiply two input matrices "A" and "B" . All elements of the output matrix will be multiplied by alpha
*
- * @note If the input tensors @p input0 and @p input1 have been reshaped respectively with @ref CLGEMMInterleave4x4Kernel" and @ref CLGEMMReshapeRHSMatrixKernel,
+ * @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 The second input tensor must have at least 2 dimensions (matrix)
@@ -57,7 +57,7 @@ public:
* @param[in] input1 Input tensor containing the Matrix B. 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] is_interleaved_transposed (Optional) True if input0 and input1 have been reshaped respectively using @ref CLGEMMInterleave4x4Kernel and @ref CLGEMMReshapeRHSMatrixKernel
+ * @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
*
@@ -70,7 +70,7 @@ public:
* @param[in] input1 Input tensor containing the Matrix B. 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] is_interleaved_transposed True if input0 and input1 have been reshaped respectively using @ref CLGEMMInterleave4x4Kernel and @ref CLGEMMReshapeRHSMatrixKernel
+ * @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