(self, x, y, **kwargs)
| 259 | super(PLD_SimpleModel, self).__init__(hidden_dim, empty_grad) |
| 260 | |
| 261 | def forward(self, x, y, **kwargs): |
| 262 | pld = kwargs.get('progressive_layer_drop', False) |
| 263 | theta = kwargs.get('pld_theta', 1.0) |
| 264 | hidden_dim = super(PLD_SimpleModel, self).forward(x, y) |
| 265 | return hidden_dim |
| 266 | |
| 267 | |
| 268 | def random_dataset(total_samples, hidden_dim, device, dtype=preferred_dtype()): |