(self, closure=None)
| 246 | |
| 247 | class FullModelGradientClippingOptimizer(optim): |
| 248 | def step(self, closure=None): |
| 249 | all_params = itertools.chain(*[x["params"] for x in self.param_groups]) |
| 250 | torch.nn.utils.clip_grad_norm_(all_params, clip_norm_val) |
| 251 | super().step(closure=closure) |
| 252 | |
| 253 | return FullModelGradientClippingOptimizer if enable else optim |
| 254 |
nothing calls this directly
no outgoing calls
no test coverage detected