Add broadcast batched matmul validation cases
Related to: COMPMID-5660
Signed-off-by: SiCong Li <sicong.li@arm.com>
Change-Id: I2314c8b21acc638402c77080d59db2f3fed58fe2
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8911
Reviewed-by: Jakub Sujak <jakub.sujak@arm.com>
Reviewed-by: Mohmun02 <MohammedSuhail.Munshi@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
diff --git a/src/cpu/operators/CpuGemm.h b/src/cpu/operators/CpuGemm.h
index 031f02b..bc8adae 100644
--- a/src/cpu/operators/CpuGemm.h
+++ b/src/cpu/operators/CpuGemm.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2021-2022 Arm Limited.
+ * Copyright (c) 2021-2023 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -81,6 +81,8 @@
* @note GEMM: General Matrix Multiply - [alpha * A * B + beta * C].
* @note GEMM: The tensors a, b, c, d must have the same data type. You should not mix data types when calling this function.
*
+ * @note Batched GEMM only supports broadcasting cases where RHS rank < LHS rank but not the other way around
+ *
* @param[in] a First input tensor info (Matrix A or Vector A). Data type supported: BFLOAT16/F16/F32
* @param[in] b Second input tensor info (Matrix B). Data type supported: same as @p a
* @param[in] c Third input tensor info (Matrix C). It can be a nullptr if just the multiplication between @p a and @p b is needed. Data type supported: same as @p a