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path: root/arm_compute/core/CL/kernels/CLNormalizationLayerKernel.h
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Diffstat (limited to 'arm_compute/core/CL/kernels/CLNormalizationLayerKernel.h')
-rw-r--r--arm_compute/core/CL/kernels/CLNormalizationLayerKernel.h8
1 files changed, 4 insertions, 4 deletions
diff --git a/arm_compute/core/CL/kernels/CLNormalizationLayerKernel.h b/arm_compute/core/CL/kernels/CLNormalizationLayerKernel.h
index 132fcc4a12..5eedc31486 100644
--- a/arm_compute/core/CL/kernels/CLNormalizationLayerKernel.h
+++ b/arm_compute/core/CL/kernels/CLNormalizationLayerKernel.h
@@ -49,10 +49,10 @@ public:
/** Set the input and output tensors.
*
* @param[in] input Source tensor. 3 lower dims represent a single input with dimensions [width, height, IFM],
- * and an optional 4th dimension for batch of inputs. Data types supported: F16, F32.
- * @param[in] squared_input Source with each element has been squared. 3 lower dims represent a single input with dimensions [width, height, IFM],
- * Data types should match the input type.
- * @param[out] output Destination tensor. Output will have the same number of dimensions as input. Data types should match the input type.
+ * and an optional 4th dimension for batch of inputs. Data types supported: QS8/QS16/F16/F32.
+ * @param[in] squared_input Source with each element has been squared. 3 lower dims represent a single input with dimensions [width, height, IFM].
+ * Data types supported: same as @p input.
+ * @param[out] output Destination tensor. Output will have the same number of dimensions as input. Data types supported: same as @p input.
* @param[in] norm_info Normalization layer information like the normalization type, normalization size and other parameters.
*/
void configure(const ICLTensor *input, const ICLTensor *squared_input, ICLTensor *output, NormalizationLayerInfo norm_info);