Add default schedulers

1 files changed, 0 insertions, 34 deletions

diff --git a/simclr/main.py b/simclr/main.py
index b170355..b91b42b 100644
--- a/simclr/main.py
+++ b/simclr/main.py
@@ -131,11 +131,6 @@ class SimCLRConfig(BaseConfig):
         betas: tuple[float, float]
         weight_decay: float
 
-    @dataclass
-    class SchedConfig(BaseConfig.SchedConfig):
-        sched: str | None
-        warmup_iters: int
-
 
 class SimCLRTrainer(Trainer):
     def __init__(self, hid_dim, out_dim, **kwargs):
@@ -254,35 +249,6 @@ class SimCLRTrainer(Trainer):
 
             yield f"{model_name}_optim", optimizer
 
-    @staticmethod
-    def _configure_scheduler(
-            optims: Iterable[tuple[str, torch.optim.Optimizer]],
-            last_iter: int,
-            num_iters: int,
-            sched_config: SimCLRConfig.SchedConfig,
-    ) -> Iterable[tuple[str, torch.optim.lr_scheduler._LRScheduler]
-                  | tuple[str, None]]:
-        for optim_name, optim in optims:
-            if sched_config.sched == 'warmup-anneal':
-                scheduler = LinearWarmupAndCosineAnneal(
-                    optim,
-                    warm_up=sched_config.warmup_iters / num_iters,
-                    T_max=num_iters,
-                    last_epoch=last_iter,
-                )
-            elif sched_config.sched == 'linear':
-                scheduler = LinearLR(
-                    optim,
-                    num_epochs=num_iters,
-                    last_epoch=last_iter
-                )
-            elif sched_config.sched in {None, '', 'const'}:
-                scheduler = None
-            else:
-                raise NotImplementedError(f"Unimplemented scheduler: '{sched_config.sched}'")
-
-            yield f"{optim_name}_sched", scheduler
-
     def _custom_init_fn(self, config: SimCLRConfig):
         self.optims = {n: LARS(o) if config.optim_config.optim == 'lars' else o
                        for n, o in self.optims.items()}