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hiyuchang merged 1 commit into from
Nov 18, 2025
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Add more useful options in OptimizerConfig #371

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18 changes: 16 additions & 2 deletions tests/common/config_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -141,18 +141,32 @@ def test_optimizer_config_propagation(self):
config = get_template_config()
config.algorithm.optimizer.lr = 1e-4
config.algorithm.optimizer.weight_decay = 0.05
config.algorithm.optimizer.clip_grad = 2.0
config.algorithm.optimizer.lr_decay_steps = 1000
config.algorithm.optimizer.lr_decay_style = "cosine"
config.algorithm.optimizer.lr_warmup_init = 1e-7
config.algorithm.optimizer.min_lr = 1e-6
config.check_and_update()
self.assertEqual(config.trainer.trainer_config.actor_rollout_ref.actor.optim.lr, 1e-4)
self.assertEqual(
config.trainer.trainer_config.actor_rollout_ref.actor.optim.weight_decay, 0.05
)
self.assertEqual(config.trainer.trainer_config.actor_rollout_ref.actor.optim.clip_grad, 2.0)
self.assertEqual(
config.trainer.trainer_config.actor_rollout_ref.actor.optim.lr_decay_style, "constant"
) # default value
config.trainer.trainer_config.actor_rollout_ref.actor.optim.lr_decay_steps, 1000
)
self.assertEqual(
config.trainer.trainer_config.actor_rollout_ref.actor.optim.lr_decay_style, "cosine"
)
self.assertEqual(
config.trainer.trainer_config.actor_rollout_ref.actor.optim.lr_warmup_init, 1e-7
)
self.assertEqual(config.trainer.trainer_config.actor_rollout_ref.actor.optim.min_lr, 1e-6)
# critic optimizer should not be affected
self.assertEqual(config.trainer.trainer_config.critic.optim.lr, 1e-5)
self.assertEqual(config.trainer.trainer_config.critic.optim.weight_decay, 0.01)
self.assertEqual(config.trainer.trainer_config.critic.optim.lr_decay_style, "constant")
self.assertEqual(config.trainer.trainer_config.critic.optim.clip_grad, 1.0)

def tearDown(self):
if os.path.exists(CHECKPOINT_ROOT_DIR):
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5 changes: 5 additions & 0 deletions trinity/common/config.py
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Original file line number Diff line number Diff line change
Expand Up @@ -98,6 +98,11 @@ class OptimizerConfig:
optimizer_type: str = "adam"
betas: List[float] = field(default_factory=lambda: [0.9, 0.999])
weight_decay: float = 0.01
clip_grad: float = 1.0
lr_warmup_init: float = 0.0
lr_decay_steps: Optional[int] = None
lr_decay_style: str = "constant"
min_lr: float = 0.0


@dataclass
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