Setting near and far with scene bounds collider. Also LR schedules. (#74)

* some initial cuda code as I learn. using git to save progress.

* first cuda kernel for ray sampling that mostly works

* cleaning up code. working on lr. structs for scene bounds aabb

* added scene bounds collider code

* updated setup

* setup

* setup

* black

* including some files

* exporting env variable

* new file

* git workflows

* github actions

* github actions

* github actions

* removing env var

scripts/run_train.py

@@ -18,6 +18,7 @@ from omegaconf import DictConfig
 
 from mattport.nerf.trainer import Trainer
 from mattport.utils import comms, profiler
+from time import time
 
 logging.basicConfig(format="[%(filename)s:%(lineno)d] %(message)s", level=logging.DEBUG)
 
@@ -99,7 +100,7 @@ def _distributed_worker(
 
     assert num_gpus_per_machine <= torch.cuda.device_count()
     torch.cuda.set_device(local_rank)
-    _set_random_seed(1234 + local_rank)  # NOTE(ethan): will this work for multiple machines? should we use global_rank?
+    _set_random_seed(1234 + global_rank)
     comms.synchronize(world_size)
 
     output = main_func(local_rank, world_size, config)
@@ -148,9 +149,11 @@ def launch(
     world_size = num_machines * num_gpus_per_machine
     if world_size == 0:
         # Using only CPU and one process.
+        _set_random_seed(0)
         main_func(local_rank=0, world_size=0, config=config)
     elif world_size == 1:
         # Using one gpu and one process.
+        _set_random_seed(0)
         try:
             main_func(local_rank=0, world_size=1, config=config)
         except KeyboardInterrupt: