(self)
| 262 | self.af2_to_esm = af2_to_esm |
| 263 | |
| 264 | def initialize_others(self): |
| 265 | # prepare data tokenizer, featurizer, and processor |
| 266 | self.tokenizer = BoltzTokenizer() |
| 267 | self.featurizer = BoltzFeaturizer() |
| 268 | self.processor = ProteinDataProcessor( |
| 269 | device=self.device, |
| 270 | scale=16.0, |
| 271 | ref_scale=5.0, |
| 272 | multiplicity=1, |
| 273 | inference_multiplicity=self.nsample_per_protein, |
| 274 | backend=self.backend, |
| 275 | ) |
| 276 | |
| 277 | # define flow process and sampler |
| 278 | self.flow = LinearPath() |
| 279 | |
| 280 | if self.backend == "torch": |
| 281 | sampler_cls = EMSampler |
| 282 | elif self.backend == "mlx": |
| 283 | sampler_cls = EMSamplerMLX |
| 284 | |
| 285 | self.sampler = sampler_cls( |
| 286 | num_timesteps=self.num_steps, |
| 287 | t_start=1e-4, |
| 288 | tau=self.tau, |
| 289 | log_timesteps=True, |
| 290 | w_cutoff=0.99, |
| 291 | ) |
| 292 | |
| 293 | def process_input(self, aa_seq): |
| 294 | # process fasta files to input format |
no test coverage detected