(self, text_size, input_size, output_size, hidden_size, n_layers)
| 122 | |
| 123 | class TextVAEDecoder(nn.Module): |
| 124 | def __init__(self, text_size, input_size, output_size, hidden_size, n_layers): |
| 125 | super(TextVAEDecoder, self).__init__() |
| 126 | self.input_size = input_size |
| 127 | self.output_size = output_size |
| 128 | self.hidden_size = hidden_size |
| 129 | self.n_layers = n_layers |
| 130 | self.emb = nn.Sequential( |
| 131 | nn.Linear(input_size, hidden_size), |
| 132 | nn.LayerNorm(hidden_size), |
| 133 | nn.LeakyReLU(0.2, inplace=True)) |
| 134 | |
| 135 | self.z2init = nn.Linear(text_size, hidden_size * n_layers) |
| 136 | self.gru = nn.ModuleList([nn.GRUCell(hidden_size, hidden_size) for i in range(self.n_layers)]) |
| 137 | self.positional_encoder = PositionalEncoding(hidden_size) |
| 138 | |
| 139 | |
| 140 | self.output = nn.Sequential( |
| 141 | nn.Linear(hidden_size, hidden_size), |
| 142 | nn.LayerNorm(hidden_size), |
| 143 | nn.LeakyReLU(0.2, inplace=True), |
| 144 | nn.Linear(hidden_size, output_size) |
| 145 | ) |
| 146 | |
| 147 | # |
| 148 | # self.output = nn.Sequential( |
| 149 | # nn.Linear(hidden_size, hidden_size), |
| 150 | # nn.LayerNorm(hidden_size), |
| 151 | # nn.LeakyReLU(0.2, inplace=True), |
| 152 | # nn.Linear(hidden_size, output_size-4) |
| 153 | # ) |
| 154 | |
| 155 | # self.contact_net = nn.Sequential( |
| 156 | # nn.Linear(output_size-4, 64), |
| 157 | # nn.LayerNorm(64), |
| 158 | # nn.LeakyReLU(0.2, inplace=True), |
| 159 | # nn.Linear(64, 4) |
| 160 | # ) |
| 161 | |
| 162 | self.output.apply(init_weight) |
| 163 | self.emb.apply(init_weight) |
| 164 | self.z2init.apply(init_weight) |
| 165 | # self.contact_net.apply(init_weight) |
| 166 | |
| 167 | def get_init_hidden(self, latent): |
| 168 | hidden = self.z2init(latent) |
nothing calls this directly
no test coverage detected