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24 #ifndef __ARM_COMPUTE_NEDEQUANTIZATIONLAYER_H__
25 #define __ARM_COMPUTE_NEDEQUANTIZATIONLAYER_H__
27 #include "arm_compute/runtime/IFunction.h"
29 #include "arm_compute/core/NEON/kernels/NEDequantizationLayerKernel.h"
31 #include "arm_compute/core/Types.h"
37 /** Basic function to simulate a dequantization layer. This function calls the following NEON kernels:
39 * @note The implementation supports only 3D input tensors
41 * -# @ref NEDequantizationLayerKernel
44 class NEDequantizationLayer : public IFunction
47 /** Default constructor */
48 NEDequantizationLayer();
49 /** Configure the kernel.
51 * @param[in] input Source tensor with at least 3 dimensions. The dimensions over the third will be interpreted as batches. Data types supported: U8.
52 * @param[out] output Destination tensor with the same dimensions of input. Data type supported: F32.
53 * @param[in] min_max Pointer to the tensor with shape [2, batches] which stores the minimum and maximum value for each 3D input tensor.
54 * The dimensions over the second must match the batched dimensions of the input tensor. Data type supported: F32
56 void configure(const ITensor *input, ITensor *output, const ITensor *min_max);
57 /** Static function to check if given info will lead to a valid configuration of @ref NEDequantizationLayer
59 * @param[in] input Input tensor info. Data types supported: U8.
60 * @param[in] output Output tensor info. Data type supported: F32.
61 * @param[in] min_max Info for the tensor with shape [2, batches] which stores the minimum and maximum value for each 3D input tensor.
62 * The dimensions over the second must match the batched dimensions of the input tensor. Data type supported: F32.
66 static Status validate(const ITensorInfo *input, const ITensorInfo *output, const ITensorInfo *min_max);
68 // Inherited methods overridden:
72 NEDequantizationLayerKernel _dequantize_kernel;
75 #endif /* __ARM_COMPUTE_NEDEQUANTIZATIONLAYER_H__ */