2 files changed, 15 insertions, 13 deletions
diff --git a/arm_compute/runtime/NEON/functions/NEDequantizationLayer.h b/arm_compute/runtime/NEON/functions/NEDequantizationLayer.h
index 7cd8360713..898586190e 100644
--- a/arm_compute/runtime/NEON/functions/NEDequantizationLayer.h
+++ b/arm_compute/runtime/NEON/functions/NEDequantizationLayer.h
@@ -27,7 +27,6 @@
 #include "arm_compute/runtime/IFunction.h"
 
 #include "arm_compute/core/NEON/kernels/NEDequantizationLayerKernel.h"
-#include "arm_compute/runtime/Tensor.h"
 
 #include "arm_compute/core/Types.h"
 
@@ -37,6 +36,8 @@ class ITensor;
 
 /** Basic function to simulate a dequantization layer. This function calls the following NEON kernels:
  *
+ * @note The implementation supports only 3D input tensors
+ *
  * -# @ref NEDequantizationLayerKernel
  *
  */
@@ -47,12 +48,12 @@ public:
     NEDequantizationLayer();
     /** Configure the kernel.
      *
-     * @param[in]  input  Source tensor. Data types supported: U8.
-     * @param[out] output Destination tensor. Data types supported: F32.
-     * @param[in]  min    Minimum value of the input tensor.
-     * @param[in]  max    Maximum value of the input tensor.
+     * @param[in]  input   Source tensor with at least 3 dimensions. The dimensions over the third will be interpreted as batches. Data types supported: U8.
+     * @param[out] output  Destination tensor with the same dimensions of input. Data type supported: F32.
+     * @param[in]  min_max Pointer to the tensor with shape [2, batches] which stores the minimum and maximum value for each 3D input tensor.
+     *                     The dimensions over the second must match the batched dimensions of the input tensor. Data type supported: F32
      */
-    void configure(const ITensor *input, ITensor *output, const float *min, const float *max);
+    void configure(const ITensor *input, ITensor *output, const ITensor *min_max);
 
     // Inherited methods overridden:
     void run() override;
diff --git a/arm_compute/runtime/NEON/functions/NEQuantizationLayer.h b/arm_compute/runtime/NEON/functions/NEQuantizationLayer.h
index ab189fe3a2..d91b4ad1ad 100644
--- a/arm_compute/runtime/NEON/functions/NEQuantizationLayer.h
+++ b/arm_compute/runtime/NEON/functions/NEQuantizationLayer.h
@@ -26,7 +26,7 @@
 
 #include "arm_compute/runtime/IFunction.h"
 
-#include "arm_compute/core/NEON/kernels/NEMinMaxLocationKernel.h"
+#include "arm_compute/core/NEON/kernels/NEMinMaxLayerKernel.h"
 #include "arm_compute/core/NEON/kernels/NEQuantizationLayerKernel.h"
 #include "arm_compute/runtime/Tensor.h"
 
@@ -38,7 +38,9 @@ class ITensor;
 
 /** Basic function to simulate a quantization layer. This function calls the following NEON kernels:
  *
- * -# @ref NEMinMaxKernel
+ * @note The implementation supports only 3D input tensors
+ *
+ * -# @ref NEMinMaxLayerKernel
  * -# @ref NEQuantizationLayerKernel
  *
  */
@@ -49,8 +51,8 @@ public:
     NEQuantizationLayer();
     /** Set the input and output tensors.
      *
-     * @param[in]  input  Source tensor. Data types supported: F32
-     * @param[out] output Destination tensor. Data types supported: U8
+     * @param[in]  input  Source tensor with at least 3 dimensions. The dimensions over the third will be interpreted as batches. Data types supported: F32
+     * @param[out] output Destination tensor with the same dimensions of input. Data types supported: U8
      */
     void configure(const ITensor *input, ITensor *output);
 
@@ -59,9 +61,8 @@ public:
 
 private:
     NEQuantizationLayerKernel _quantize_kernel;
-    NEMinMaxKernel            _min_max_kernel;
-    float                     _min;
-    float                     _max;
+    NEMinMaxLayerKernel       _min_max_kernel;
+    Tensor                    _min_max;
 };
 }
 #endif /* __ARM_COMPUTE_NEQUANTIZATIONLAYER_H__ */