diff options
Diffstat (limited to 'arm_compute/core/NEON/kernels/NENormalizationLayerKernel.h')
-rw-r--r-- | arm_compute/core/NEON/kernels/NENormalizationLayerKernel.h | 14 |
1 files changed, 7 insertions, 7 deletions
diff --git a/arm_compute/core/NEON/kernels/NENormalizationLayerKernel.h b/arm_compute/core/NEON/kernels/NENormalizationLayerKernel.h index 92086437a6..533335f9af 100644 --- a/arm_compute/core/NEON/kernels/NENormalizationLayerKernel.h +++ b/arm_compute/core/NEON/kernels/NENormalizationLayerKernel.h @@ -54,20 +54,20 @@ 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: FP16/F32. + * and an optional 4th dimension for batch of inputs. Data types supported: FP16/F32. Data layouts supported: NCHW/NHWC. * @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 + * Data type and layout supported: same as @p input. + * @param[out] output Destination tensor. Output will have the same number of dimensions as input. Data type and layout supported: same as @p input. * @param[in] norm_info Normalization layer information like the normalization type, normalization size and other parameters. */ void configure(const ITensor *input, const ITensor *input_squared, ITensor *output, NormalizationLayerInfo norm_info); /** 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: FP16/F32. + * and an optional 4th dimension for batch of inputs. Data types supported: FP16/F32. Data layouts supported: NCHW/NHWC. * @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 + * Data type and layout supported: same as @p input. + * @param[in] output Destination tensor. Output will have the same number of dimensions as input. Data type and layout supported: same as @p input. * @param[in] norm_info Normalization layer information like the normalization type, normalization size and other parameters. * * @return a status @@ -89,7 +89,7 @@ private: * * @param[in] window Region on which to execute the kernel. */ - template <DataType dt, unsigned int dim, bool do_2D_norm> + template <typename T, unsigned int S, unsigned int dim, bool do_2D_norm> void normalize_float(const Window &window); /** Common signature for all the specialised normalization functions |