COMPMID-439 - Refactored NEQuantizationLayer and NEQuantizationLayer in order to support 3D input tensors
Change-Id: I03eac2108a30bed56d40dfd52e75577a35d492e0
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/85783
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>
Reviewed-by: Michele DiGiorgio <michele.digiorgio@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
diff --git a/arm_compute/runtime/NEON/functions/NEDequantizationLayer.h b/arm_compute/runtime/NEON/functions/NEDequantizationLayer.h
index 7cd8360..8985861 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 @@
/** 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 @@
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 ab189fe..d91b4ad 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 @@
/** 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 @@
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 @@
private:
NEQuantizationLayerKernel _quantize_kernel;
- NEMinMaxKernel _min_max_kernel;
- float _min;
- float _max;
+ NEMinMaxLayerKernel _min_max_kernel;
+ Tensor _min_max;
};
}
#endif /* __ARM_COMPUTE_NEQUANTIZATIONLAYER_H__ */