diff options
Diffstat (limited to 'arm_compute/runtime/CL')
-rw-r--r-- | arm_compute/runtime/CL/functions/CLBatchNormalizationLayer.h | 6 | ||||
-rw-r--r-- | arm_compute/runtime/CL/functions/CLNormalizationLayer.h | 4 |
2 files changed, 5 insertions, 5 deletions
diff --git a/arm_compute/runtime/CL/functions/CLBatchNormalizationLayer.h b/arm_compute/runtime/CL/functions/CLBatchNormalizationLayer.h index 70a201a1f8..d84ba69da2 100644 --- a/arm_compute/runtime/CL/functions/CLBatchNormalizationLayer.h +++ b/arm_compute/runtime/CL/functions/CLBatchNormalizationLayer.h @@ -54,8 +54,8 @@ public: * @param[out] output Destination tensor. Output will have the same number of dimensions as input. Data type supported: same as @p input * @param[in] mean Mean values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input * @param[in] var Variance values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input - * @param[in] gamma Gamma values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input * @param[in] beta Beta values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input + * @param[in] gamma Gamma values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input * @param[in] epsilon Small value to avoid division with zero. */ void configure(ICLTensor *input, ICLTensor *output, const ICLTensor *mean, const ICLTensor *var, const ICLTensor *beta, const ICLTensor *gamma, float epsilon); @@ -63,12 +63,12 @@ public: * * @param[in] input Source tensor info. In case of @p output tensor info = nullptr, this tensor will store the result. * 3 lower dimensions represent a single input with dimensions [width, height, FM]. - * @param[in] output Destination tensor info. Output will have the same number of dimensions as input. Data type supported: same as @p input * The rest are optional and used for representing batches. Data types supported: QS8/QS16/F16/F32. + * @param[in] output Destination tensor info. Output will have the same number of dimensions as input. Data type supported: same as @p input * @param[in] mean Mean values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input * @param[in] var Variance values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input - * @param[in] gamma Gamma values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input * @param[in] beta Beta values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input + * @param[in] gamma Gamma values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input * @param[in] epsilon Small value to avoid division with zero. * * @return an error status diff --git a/arm_compute/runtime/CL/functions/CLNormalizationLayer.h b/arm_compute/runtime/CL/functions/CLNormalizationLayer.h index 0818cec2e5..1e0b27ae43 100644 --- a/arm_compute/runtime/CL/functions/CLNormalizationLayer.h +++ b/arm_compute/runtime/CL/functions/CLNormalizationLayer.h @@ -37,7 +37,7 @@ namespace arm_compute { class ICLTensor; -/** Basic function to simulate a normalization layer. This function calls the following CL kernels: +/** Basic function to compute a normalization layer. This function calls the following CL kernels: * * -# @ref CLFillBorderKernel * -# @ref CLNormalizationLayerKernel @@ -55,7 +55,7 @@ public: * @param[out] output Destination tensor. Dimensions, data type and number of channels must match the input ones. * @param[in] norm_info Normalization layer information like the normalization type, normalization size and other parameters. */ - void configure(ICLTensor *input, ICLTensor *output, NormalizationLayerInfo norm_info); + void configure(ICLTensor *input, ICLTensor *output, const NormalizationLayerInfo &norm_info); // Inherited methods overridden: void run() override; |