1 | /* |
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2 | Copyright (C) 2018 Paul Brossier <piem@aubio.org> |
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3 | |
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4 | This file is part of aubio. |
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5 | |
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6 | aubio is free software: you can redistribute it and/or modify |
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7 | it under the terms of the GNU General Public License as published by |
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8 | the Free Software Foundation, either version 3 of the License, or |
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9 | (at your option) any later version. |
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10 | |
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11 | aubio is distributed in the hope that it will be useful, |
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12 | but WITHOUT ANY WARRANTY; without even the implied warranty of |
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13 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the |
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14 | GNU General Public License for more details. |
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15 | |
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16 | You should have received a copy of the GNU General Public License |
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17 | along with aubio. If not, see <http://www.gnu.org/licenses/>. |
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18 | |
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19 | */ |
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20 | |
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21 | #ifndef AUBIO_CONV1D_H |
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22 | #define AUBIO_CONV1D_H |
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23 | |
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24 | /** \file |
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25 | |
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26 | Convolutional layer (1D) |
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27 | |
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28 | Standard implementation of a 1D convolutional layer, partly optimized for |
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29 | CPU. |
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30 | |
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31 | Note |
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32 | ---- |
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33 | Only the forward pass is implemented for now. |
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34 | |
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35 | References |
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36 | ---------- |
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37 | Vincent Dumoulin, Francesco Visin - A guide to convolution arithmetic for |
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38 | deep learning. https://github.com/vdumoulin/conv_arithmetic |
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39 | |
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40 | */ |
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41 | |
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42 | #ifdef __cplusplus |
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43 | extern "C" { |
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44 | #endif |
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45 | |
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46 | /** conv1d layer */ |
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47 | typedef struct _aubio_conv1d_t aubio_conv1d_t; |
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48 | |
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49 | /** create a new conv1d layer |
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50 | |
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51 | \param n_filters number of filters |
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52 | \param kernel_shape length of each filter |
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53 | |
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54 | \return new conv1d layer |
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55 | |
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56 | */ |
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57 | aubio_conv1d_t *new_aubio_conv1d(uint_t n_filters, uint_t kernel_shape[1]); |
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58 | |
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59 | /** set padding mode |
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60 | |
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61 | \param c layer |
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62 | \param padding_mode padding mode |
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63 | |
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64 | \return 0 on success, non-zero otherwise |
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65 | |
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66 | Available padding: "same", and "valid". |
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67 | |
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68 | Todo: |
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69 | - add causal mode |
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70 | |
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71 | */ |
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72 | uint_t aubio_conv1d_set_padding_mode(aubio_conv1d_t *c, |
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73 | const char_t *padding_mode); |
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74 | |
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75 | /** set stride |
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76 | |
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77 | \param c layer |
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78 | \param stride array of length 1 containing the stride parameter |
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79 | |
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80 | \return 0 on success, non-zero otherwise |
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81 | |
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82 | */ |
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83 | uint_t aubio_conv1d_set_stride(aubio_conv1d_t *c, uint_t stride[1]); |
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84 | |
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85 | /** get current stride settings |
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86 | |
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87 | \param t layer |
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88 | |
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89 | \return array of length 1 containing the stride parameter |
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90 | |
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91 | */ |
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92 | uint_t *aubio_conv1d_get_stride(aubio_conv1d_t* t); |
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93 | |
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94 | /** get output shape |
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95 | |
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96 | \param t layer |
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97 | \param input_tensor input tensor |
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98 | \param shape output shape |
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99 | |
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100 | \return 0 on success, non-zero otherwise |
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101 | |
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102 | Upon return, `shape` will be filled with the output shape of the layer. This |
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103 | function should be called after ::aubio_conv1d_set_stride or |
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104 | ::aubio_conv1d_set_padding_mode, and before ::aubio_conv1d_get_kernel or |
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105 | ::aubio_conv1d_get_bias. |
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106 | |
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107 | */ |
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108 | uint_t aubio_conv1d_get_output_shape(aubio_conv1d_t *t, |
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109 | aubio_tensor_t *input_tensor, uint_t *shape); |
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110 | |
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111 | /** get kernel weights |
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112 | |
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113 | \param t ::aubio_conv1d_t layer |
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114 | |
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115 | \return tensor of weights |
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116 | |
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117 | When called after ::aubio_conv1d_get_output_shape, this function will return |
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118 | a pointer to the tensor holding the weights of this layer. |
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119 | |
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120 | */ |
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121 | aubio_tensor_t *aubio_conv1d_get_kernel(aubio_conv1d_t *t); |
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122 | |
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123 | /** get biases |
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124 | |
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125 | \param t layer |
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126 | |
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127 | \return vector of biases |
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128 | |
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129 | When called after ::aubio_conv1d_get_output_shape, this function will return |
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130 | a pointer to the vector holding the biases. |
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131 | |
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132 | */ |
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133 | fvec_t *aubio_conv1d_get_bias(aubio_conv1d_t *t); |
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134 | |
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135 | /** set kernel weights |
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136 | |
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137 | \param t layer |
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138 | \param kernel kernel weights |
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139 | |
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140 | \return 0 on success, non-zero otherwise |
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141 | |
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142 | Copy kernel weights into internal layer memory. This function should be |
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143 | called after ::aubio_conv1d_get_output_shape. |
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144 | |
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145 | */ |
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146 | uint_t aubio_conv1d_set_kernel(aubio_conv1d_t *t, aubio_tensor_t *kernel); |
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147 | |
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148 | /** set biases |
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149 | |
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150 | \param t layer |
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151 | \param bias biases |
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152 | |
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153 | \return 0 on success, non-zero otherwise |
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154 | |
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155 | Copy vector of biases into internal layer memory. This function should be |
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156 | called after ::aubio_conv1d_get_output_shape. |
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157 | |
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158 | */ |
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159 | uint_t aubio_conv1d_set_bias(aubio_conv1d_t *t, fvec_t *bias); |
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160 | |
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161 | /** compute layer output |
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162 | |
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163 | \param t layer |
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164 | \param input_tensor input tensor |
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165 | \param output_tensor output tensor |
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166 | |
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167 | Perform 1D convolution. |
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168 | |
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169 | */ |
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170 | void aubio_conv1d_do(aubio_conv1d_t *t, aubio_tensor_t *input_tensor, |
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171 | aubio_tensor_t *output_tensor); |
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172 | |
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173 | /** destroy conv1d layer |
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174 | |
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175 | \param t layer |
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176 | |
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177 | */ |
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178 | void del_aubio_conv1d(aubio_conv1d_t *t); |
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179 | |
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180 | #ifdef __cplusplus |
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181 | } |
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182 | #endif |
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183 | |
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184 | #endif /* AUBIO_CONV1D_H */ |
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