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-rw-r--r--arm_compute/core/NEON/kernels/NEBatchNormalizationLayerKernel.h21
1 files changed, 3 insertions, 18 deletions
diff --git a/arm_compute/core/NEON/kernels/NEBatchNormalizationLayerKernel.h b/arm_compute/core/NEON/kernels/NEBatchNormalizationLayerKernel.h
index 2d33f87dfa..2a540c151b 100644
--- a/arm_compute/core/NEON/kernels/NEBatchNormalizationLayerKernel.h
+++ b/arm_compute/core/NEON/kernels/NEBatchNormalizationLayerKernel.h
@@ -57,7 +57,7 @@ public:
*
* @param[in, out] input Source tensor. In case of @p output tensor = nullptr, this tensor will store the result.
* 3 lower dimensions represent a single input with dimensions [width, height, FM].
- * The rest are optional and used for representing batches. Data types supported: QS8/QS16/F16/F32.
+ * The rest are optional and used for representing batches. Data types supported: F16/F32.
* @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
@@ -72,7 +72,7 @@ public:
*
* @param[in] input Source tensor info. In case of @p output tensor = nullptr, this tensor will store the result.
* 3 lower dimensions represent a single input with dimensions [width, height, FM].
- * The rest are optional and used for representing batches. Data types supported: QS8/QS16/F16/F32.
+ * The rest are optional and used for representing batches. Data types supported: 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
@@ -96,22 +96,7 @@ private:
void configure_non_fused();
/** Configure execution function in case of fused activation **/
void configure_fused();
- /** Template function to run batch normalization on 8-bit fixed point
- *
- * @tparam fused_activation Boolean that flags if its a fused activation or not
- *
- * @param[in] window Region on which to execute the kernel. (Must be a valid region of the window returned by window()).
- */
- template <bool fused_activation>
- void batch_normalization_qs8(const Window &window);
- /** Template function to run batch normalization on 16-bit fixed point
- *
- * @tparam fused_activation Boolean that flags if its a fused activation or not
- *
- * @param[in] window Region on which to execute the kernel. (Must be a valid region of the window returned by window()).
- */
- template <bool fused_activation>
- void batch_normalization_qs16(const Window &window);
+
/** Template function to run batch normalization on fp16
*
* @tparam fused_activation Boolean that flags if its a fused activation or not