| 210 | return self._embeddings |
| 211 | |
| 212 | def train(self, batch_size=1024, epochs=1, initial_epoch=0, verbose=1, times=1): |
| 213 | self.reset_training_config(batch_size, times) |
| 214 | try: |
| 215 | hist = self.model.fit( |
| 216 | self.batch_it, |
| 217 | epochs=epochs, |
| 218 | initial_epoch=initial_epoch, |
| 219 | steps_per_epoch=self.steps_per_epoch, |
| 220 | verbose=verbose, |
| 221 | ) |
| 222 | except TypeError: |
| 223 | if not hasattr(self.model, "fit_generator"): |
| 224 | raise |
| 225 | hist = self.model.fit_generator( |
| 226 | self.batch_it, |
| 227 | epochs=epochs, |
| 228 | initial_epoch=initial_epoch, |
| 229 | steps_per_epoch=self.steps_per_epoch, |
| 230 | verbose=verbose, |
| 231 | ) |
| 232 | |
| 233 | return hist |