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-rw-r--r--arm_compute/runtime/CL/functions/CLGEMM.h6
1 files changed, 3 insertions, 3 deletions
diff --git a/arm_compute/runtime/CL/functions/CLGEMM.h b/arm_compute/runtime/CL/functions/CLGEMM.h
index 043b2b8115..080f497b7b 100644
--- a/arm_compute/runtime/CL/functions/CLGEMM.h
+++ b/arm_compute/runtime/CL/functions/CLGEMM.h
@@ -36,7 +36,7 @@ namespace arm_compute
{
class ICLTensor;
-/** Basic function to execute GEMM on OpenCL. Data types supported: F32, F16. This function calls the following OpenCL kernels:
+/** Basic function to execute GEMM on OpenCL. This function calls the following OpenCL kernels:
*
* -# @ref CLGEMMInterleave4x4Kernel (if the output tensor is a matrix)
* -# @ref CLGEMMTranspose1xWKernel (if the output tensor is a matrix)
@@ -53,11 +53,11 @@ public:
*
* @note GEMM: General Matrix Multiply - [alpha * A * B + beta * C].
*
- * @note All tensors must have the same data type. Data types supported: F32, F16
+ * @note All tensors must have the same data type.
*
* @note Whilst the first input tensor can be a vector, the second input tensor must be at least a matrix
*
- * @param[in] a First input tensor (Matrix or Vector A). Data types supported: F32, F16
+ * @param[in] a First input tensor (Matrix or Vector A). Data types supported: QS8/F16/F32
* @param[in] b Second input tensor (Matrix B). Data type supported: same as @p a.
* @param[in] c Third input tensor (Matrix C). It can be a nullptr if just the multiplication between @p a and @p b is needed. Data type supported: same as @p a.
* @param[out] output Output tensor. Data type supported: same as @p a