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Diffstat (limited to 'arm_compute/core/NEON/kernels/NENormalizationLayerKernel.h')
-rw-r--r--arm_compute/core/NEON/kernels/NENormalizationLayerKernel.h16
1 files changed, 2 insertions, 14 deletions
diff --git a/arm_compute/core/NEON/kernels/NENormalizationLayerKernel.h b/arm_compute/core/NEON/kernels/NENormalizationLayerKernel.h
index 6ae7b73423..92086437a6 100644
--- a/arm_compute/core/NEON/kernels/NENormalizationLayerKernel.h
+++ b/arm_compute/core/NEON/kernels/NENormalizationLayerKernel.h
@@ -54,7 +54,7 @@ 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: QS8/QS16/FP16/F32.
+ * and an optional 4th dimension for batch of inputs. Data types supported: FP16/F32.
* @param[in] input_squared Source with each element has been squared. 3 lower dims represent a single input with dimensions [width, height, IFM],
* Data type supported: same as @p input
* @param[out] output Destination tensor. Output will have the same number of dimensions as input. Data type supported: same as @p input
@@ -64,7 +64,7 @@ public:
/** Static function to check if given info will lead to a valid configuration of @ref NENormalizationLayerKernel
*
* @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: QS8/QS16/FP16/F32.
+ * and an optional 4th dimension for batch of inputs. Data types supported: FP16/F32.
* @param[in] input_squared Source with each element has been squared. 3 lower dims represent a single input with dimensions [width, height, IFM],
* Data type supported: same as @p input
* @param[in] output Destination tensor. Output will have the same number of dimensions as input. Data type supported: same as @p input
@@ -92,18 +92,6 @@ private:
template <DataType dt, unsigned int dim, bool do_2D_norm>
void normalize_float(const Window &window);
- /** Function to perform normalization for fixed-point values depending on
- * the given template dimension. The second template parameter specifies
- * whether the normalization has to be 1D or 2D.
- *
- * @note Only supported normalizations are:
- * - 1D over X or Z
- * - 2D over X and Y
- *
- * @param[in] window Region on which to execute the kernel.
- */
- template <DataType dt, unsigned int dim, bool do_2D_norm>
- void normalize_fixed_point(const Window &window);
/** Common signature for all the specialised normalization functions
*
* @param[in] window Region on which to execute the kernel.