Update scheduler for nerfacto

Add scheduler (lr decay) in nerfacto is also effective for preventing long-time training nan and good for convergence

nerfstudio/configs/method_configs.py

@@ -92,7 +92,8 @@ method_configs["nerfacto"] = TrainerConfig(
             train_num_rays_per_batch=4096,
             eval_num_rays_per_batch=4096,
             camera_optimizer=CameraOptimizerConfig(
-                mode="SO3xR3", optimizer=AdamOptimizerConfig(lr=6e-4, eps=1e-8, weight_decay=1e-2)
+                mode="SO3xR3", optimizer=AdamOptimizerConfig(lr=6e-4, eps=1e-8, weight_decay=1e-2),
+                scheduler = ExponentialDecaySchedulerConfig(lr_final=6e-6, max_steps=200000)
             ),
         ),
         model=NerfactoModelConfig(eval_num_rays_per_chunk=1 << 15),
@@ -100,11 +101,11 @@ method_configs["nerfacto"] = TrainerConfig(
     optimizers={
         "proposal_networks": {
             "optimizer": AdamOptimizerConfig(lr=1e-2, eps=1e-15),
-            "scheduler": None,
+            "scheduler": ExponentialDecaySchedulerConfig(lr_final=0.0001, max_steps=200000),
         },
         "fields": {
             "optimizer": AdamOptimizerConfig(lr=1e-2, eps=1e-15),
-            "scheduler": None,
+            "scheduler": ExponentialDecaySchedulerConfig(lr_final=0.0001, max_steps=200000),
         },
     },
     viewer=ViewerConfig(num_rays_per_chunk=1 << 15),