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56 | mjames | 1 | /* |
2 | * Copyright (C) 2010-2018 Arm Limited or its affiliates. All rights reserved. |
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3 | * |
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4 | * SPDX-License-Identifier: Apache-2.0 |
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5 | * |
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6 | * Licensed under the Apache License, Version 2.0 (the License); you may |
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7 | * not use this file except in compliance with the License. |
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8 | * You may obtain a copy of the License at |
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9 | * |
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10 | * www.apache.org/licenses/LICENSE-2.0 |
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11 | * |
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12 | * Unless required by applicable law or agreed to in writing, software |
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13 | * distributed under the License is distributed on an AS IS BASIS, WITHOUT |
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14 | * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
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15 | * See the License for the specific language governing permissions and |
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16 | * limitations under the License. |
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17 | */ |
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18 | |||
19 | /* ---------------------------------------------------------------------- |
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20 | * Project: CMSIS NN Library |
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21 | * Title: arm_softmax_q15.c |
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22 | * Description: Q15 softmax function |
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23 | * |
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24 | * $Date: 20. February 2018 |
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25 | * $Revision: V.1.0.0 |
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26 | * |
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27 | * Target Processor: Cortex-M cores |
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28 | * |
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29 | * -------------------------------------------------------------------- */ |
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30 | |||
31 | #include "arm_math.h" |
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32 | #include "arm_nnfunctions.h" |
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33 | |||
34 | /** |
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35 | * @ingroup groupNN |
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36 | */ |
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37 | |||
38 | /** |
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39 | * @addtogroup Softmax |
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40 | * @{ |
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41 | */ |
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42 | |||
43 | /** |
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44 | * @brief Q15 softmax function |
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45 | * @param[in] vec_in pointer to input vector |
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46 | * @param[in] dim_vec input vector dimention |
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47 | * @param[out] p_out pointer to output vector |
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48 | * @return none. |
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49 | * |
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50 | * @details |
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51 | * |
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52 | * Here, instead of typical e based softmax, we use |
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53 | * 2-based softmax, i.e.,: |
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54 | * |
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55 | * y_i = 2^(x_i) / sum(2^x_j) |
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56 | * |
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57 | * The relative output will be different here. |
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58 | * But mathematically, the gradient will be the same |
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59 | * with a log(2) scaling factor. |
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60 | * |
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61 | */ |
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62 | |||
63 | void arm_softmax_q15(const q15_t * vec_in, const uint16_t dim_vec, q15_t * p_out) |
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64 | { |
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65 | q31_t sum; |
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66 | int16_t i; |
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67 | uint8_t shift; |
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68 | q31_t base; |
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69 | base = -1 * 0x100000; |
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70 | for (i = 0; i < dim_vec; i++) |
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71 | { |
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72 | if (vec_in[i] > base) |
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73 | { |
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74 | base = vec_in[i]; |
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75 | } |
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76 | } |
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77 | |||
78 | /* we ignore really small values |
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79 | * anyway, they will be 0 after shrinking |
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80 | * to q15_t |
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81 | */ |
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82 | base = base - 16; |
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83 | |||
84 | sum = 0; |
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85 | |||
86 | for (i = 0; i < dim_vec; i++) |
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87 | { |
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88 | if (vec_in[i] > base) |
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89 | { |
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90 | shift = (uint8_t)__USAT(vec_in[i] - base, 5); |
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91 | sum += 0x1 << shift; |
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92 | } |
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93 | } |
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94 | |||
95 | /* This is effectively (0x1 << 32) / sum */ |
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96 | int64_t div_base = 0x100000000LL; |
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97 | int output_base = (int32_t)(div_base / sum); |
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98 | |||
99 | /* Final confidence will be output_base >> ( 17 - (vec_in[i] - base) ) |
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100 | * so 32768 (0x1<<15) -> 100% confidence when sum = 0x1 << 16, output_base = 0x1 << 16 |
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101 | * and vec_in[i]-base = 16 |
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102 | */ |
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103 | for (i = 0; i < dim_vec; i++) |
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104 | { |
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105 | if (vec_in[i] > base) |
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106 | { |
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107 | /* Here minimum value of 17+base-vec[i] will be 1 */ |
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108 | shift = (uint8_t)__USAT(17+base-vec_in[i], 5); |
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109 | p_out[i] = (q15_t) __SSAT((output_base >> shift), 16); |
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110 | } else |
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111 | { |
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112 | p_out[i] = 0; |
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113 | } |
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114 | } |
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115 | |||
116 | } |
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117 | |||
118 | /** |
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119 | * @} end of Softmax group |
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120 | */ |