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1 /*
2  * Copyright (c) 2017-2020 Arm Limited.
3  *
4  * SPDX-License-Identifier: MIT
5  *
6  * Permission is hereby granted, free of charge, to any person obtaining a copy
7  * of this software and associated documentation files (the "Software"), to
8  * deal in the Software without restriction, including without limitation the
9  * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
10  * sell copies of the Software, and to permit persons to whom the Software is
11  * furnished to do so, subject to the following conditions:
12  *
13  * The above copyright notice and this permission notice shall be included in all
14  * copies or substantial portions of the Software.
15  *
16  * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
17  * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
18  * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
19  * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
20  * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
21  * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
22  * SOFTWARE.
23  */
24 #ifndef ARM_COMPUTE_NEGEMMLOWPQUANTIZEDOWNINT32TOUINT8SCALEBYFIXEDPOINTKERNEL_H
25 #define ARM_COMPUTE_NEGEMMLOWPQUANTIZEDOWNINT32TOUINT8SCALEBYFIXEDPOINTKERNEL_H
26 
27 #include "src/core/NEON/INEKernel.h"
28 
29 namespace arm_compute
30 {
31 class ITensor;
32 
33 /** NEON kernel used to quantize down the int32 accumulator values of GEMMLowp to QASYMM8
34  *
35  * This kernel takes a final int32 accumulator value (the output of @ref NEGEMMLowpMatrixMultiplyKernel), and processes it to obtain the final QASYMM8 value.
36  * The following computations will be performed by the kernel:
37  *
38  *  -# Compute fixed point multiplication between each entry of input by result_fixedpoint_multiplier
39  *  -# Add bias to final result if bias tensor is not a nullptr
40  *  -# Round to nearest division by a power-of-two using result_shift
41  *  -# Add offset to each result
42  *  -# Clamp the value between the specified min and max bounds
43  *  -# Clamp the resulting int32 values to the [0..255] range and cast to QASYMM8.
44  *
45  */
46 class NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel : public INEKernel
47 {
48 public:
name()49     const char *name() const override
50     {
51         return "NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel";
52     }
53     /** Constructor */
54     NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel();
55     /** Prevent instances of this class from being copied (As this class contains pointers)*/
56     NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel(const NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel &) = delete;
57     /** Prevent instances of this class from being copied (As this class contains pointers)*/
58     NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel &operator=(const NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel &) = delete;
59     /** Allow instances of this class to be moved */
60     NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel(NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel &&) = default;
61     /** Allow instances of this class to be moved */
62     NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel &operator=(NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel &&) = default;
63     /** Default destructor */
64     ~NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel() = default;
65     /** Initialise the kernel's input and output.
66      *
67      * @param[in]  input                        Input tensor. Data type supported: S32
68      * @param[in]  bias                         Biases tensor. Only shared biases supported and it can be a nullptr if the biases addition is not required.
69      *                                          Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input.
70      * @param[out] output                       Output tensor. Data type supported: Data type supported: QASYMM8
71      * @param[in]  result_fixedpoint_multiplier Fixed point value to be multiplied to each element of the input matrix when once the result_offset has been add
72      * @param[in]  result_shift                 Integer value used to round to nearest division by a power-of-two the result after the fixed point multiplication
73      * @param[in]  result_offset_after_shift    Offset to be applied to result before converting it back to QASYMM8
74      * @param[in]  min                          (Optional) Min value used to saturate down the output result before converting back to QASYMM8
75      * @param[in]  max                          (Optional) Max value used to saturate up the output result before converting back to QASYMM8,
76      *                                          Along with @p min, this value can be used to implement "rectified linear unit" activation functions
77      */
78     void configure(const ITensor *input, const ITensor *bias, ITensor *output, int result_fixedpoint_multiplier, int result_shift, int result_offset_after_shift, int min = 0, int max = 0);
79     /** Static function to check if given info will lead to a valid configuration of @ref NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel
80      *
81      * @param[in] input  Input tensor. Data type supported: S32
82      * @param[in] bias   Biases tensor. Only shared biases supported and it can be a nullptr if the biases addition is not required.
83      *                   Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input.
84      * @param[in] output Output tensor. Data type supported: Data type supported: QASYMM8
85      * @param[in] min    (Optional) Min value used to saturate down the output result before converting back to QASYMM8
86      * @param[in] max    (Optional) Max value used to saturate up the output result before converting back to QASYMM8,
87      *                            Along with @p min, this value can be used to implement "rectified linear unit" activation functions
88      *
89      * @return a status
90      */
91     static Status validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, int min = 0, int max = 0);
92 
93     // Inherited methods overridden:
94     void run(const Window &window, const ThreadInfo &info) override;
95 
96 private:
97     /** Template function to run the NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel
98      *
99      * @param[in] window Region on which to execute the kernel. (Must be a valid region of the window returned by window()).
100      */
101     template <bool is_bounded_relu>
102     void run(const Window &window);
103 
104     /** Common signature for all the specialised NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel functions
105      *
106      * @param[in] window Region on which to execute the kernel.
107      */
108     using QuantizeDownFunctionPtr = void (NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel::*)(const Window &window);
109 
110     QuantizeDownFunctionPtr _func;
111     const ITensor          *_input;
112     const ITensor          *_bias;
113     ITensor                *_output;
114     int                     _result_fixedpoint_multiplier;
115     int                     _result_shift;
116     int                     _result_offset_after_shift;
117     int                     _min;
118     int                     _max;
119 };
120 } // namespace arm_compute
121 #endif /* ARM_COMPUTE_NEGEMMLOWPQUANTIZEDOWNINT32TOUINT8SCALEBYFIXEDPOINTKERNEL_H */
122