• Home
  • Line#
  • Scopes#
  • Navigate#
  • Raw
  • Download
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_NESOFTMAXLAYER_H
25 #define ARM_COMPUTE_NESOFTMAXLAYER_H
26 
27 #include "arm_compute/runtime/IFunction.h"
28 #include "arm_compute/runtime/MemoryGroup.h"
29 #include "arm_compute/runtime/NEON/functions/NEPermute.h"
30 #include "arm_compute/runtime/Tensor.h"
31 #include <memory>
32 
33 namespace arm_compute
34 {
35 class ITensor;
36 class NELogits1DMaxKernel;
37 template <bool IS_LOG>
38 class NELogits1DSoftmaxKernel;
39 class NEFillBorderKernel;
40 
41 /** Basic function to compute a SoftmaxLayer and a Log SoftmaxLayer.
42  *
43  * Softmax is calculated by :
44  * @f[ out = exp((x - max(x)) * beta) / sum(exp((x - max(x)) * beta)) @f]
45  *
46  * Log Softmax is calculated by :
47  * @f[ out = (x - max(x) * beta) - log(\sum{e^{x - max(x) * beta}}) @f]
48  *
49  * This function runs the following function/kernels:
50  * -# If axis is not 0:
51  * -#   @ref NEPermute
52  * -# @ref NEFillBorderKernel
53  * -# @ref NELogits1DMaxKernel
54  * -# @ref NELogits1DSoftmaxKernel
55  */
56 template <bool IS_LOG = false>
57 class NESoftmaxLayerGeneric : public IFunction
58 {
59 public:
60     /** Constructor */
61     NESoftmaxLayerGeneric(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
62     /** Prevent instances of this class from being copied (As this class contains pointers) */
63     NESoftmaxLayerGeneric(const NESoftmaxLayerGeneric &) = delete;
64     /** Default move constructor */
65     NESoftmaxLayerGeneric(NESoftmaxLayerGeneric &&) = default;
66     /** Prevent instances of this class from being copied (As this class contains pointers) */
67     NESoftmaxLayerGeneric &operator=(const NESoftmaxLayerGeneric &) = delete;
68     /** Default move assignment operator */
69     NESoftmaxLayerGeneric &operator=(NESoftmaxLayerGeneric &&) = default;
70     /** Default destructor */
71     ~NESoftmaxLayerGeneric();
72     /** Set the input and output tensors.
73      *
74      * @param[in,out] input  Source tensor. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32. If the width is not a
75      *                       multiple of the internal processing block size, @ref NEFillBorderKernel replicates the
76      *                       last value of each row to the nearest multiple.
77      * @param[out]    output Destination tensor. Data types supported: same as @p input.
78      * @param[in]     beta   (Optional) A scaling factor for the exponent.
79      * @param[in]     axis   (Optional) The dimension in which to apply the function. E.g. for input of shape 4x5x6 and
80      *                       axis=1, softmax will be applied to 4x6=24 vectors of size 5. Defaults to 0
81      */
82     void configure(ITensor *input, ITensor *output, float beta = 1.0f, int32_t axis = 0);
83     /** Static function to check if given info will lead to a valid configuration of @ref NESoftmaxLayer
84      *
85      * @param[in] input  Source tensor info. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
86      * @param[in] output Destination tensor info. Data types supported: same as @p input
87      * @param[in] beta   (Optional) A scaling factor for the exponent.
88      * @param[in] axis   (Optional) The dimension in which to apply the function. E.g. for input of shape 4x5x6 and
89      *                       axis=1, softmax will be applied to 4x6=24 vectors of size 5. Defaults to 0
90      *
91      * @return a status
92      */
93     static Status validate(const ITensorInfo *input, const ITensorInfo *output, float beta = 1.0f, int32_t axis = 0);
94 
95     // Inherited methods overridden:
96     void run() override;
97 
98 private:
99     MemoryGroup                                      _memory_group;
100     NEPermute                                        _permute_input;
101     NEPermute                                        _permute_output;
102     std::unique_ptr<NELogits1DMaxKernel>             _max_kernel;
103     std::unique_ptr<NELogits1DSoftmaxKernel<IS_LOG>> _softmax_kernel;
104     std::unique_ptr<NEFillBorderKernel>              _fill_border_kernel;
105     Tensor                                           _max;
106     Tensor                                           _tmp;
107     Tensor                                           _input_permuted;
108     Tensor                                           _output_permuted;
109     bool                                             _needs_permute;
110 };
111 
112 using NESoftmaxLayer    = NESoftmaxLayerGeneric<false>;
113 using NELogSoftmaxLayer = NESoftmaxLayerGeneric<true>;
114 
115 } // namespace arm_compute
116 #endif /* ARM_COMPUTE_NESOFTMAXLAYER_H */
117