Tiny-cuda-nn and fixed logic for instant-ngp (#102)

* correcting implementation for instant ngp

* instant ngp with tcnn

* black and pylint

* merged master

scripts/run_train.py

@@ -100,7 +100,7 @@ def _distributed_worker(
 
     assert num_gpus_per_machine <= torch.cuda.device_count()
     torch.cuda.set_device(local_rank)
-    _set_random_seed(1234 + global_rank)
+    _set_random_seed(config.seed + global_rank)
     comms.synchronize(world_size)
 
     output = main_func(local_rank, world_size, config)
@@ -149,11 +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)
+        _set_random_seed(config.seed)
         main_func(local_rank=0, world_size=0, config=config)
     elif world_size == 1:
         # Using one gpu and one process.
-        _set_random_seed(0)
+        _set_random_seed(config.seed)
         try:
             main_func(local_rank=0, world_size=1, config=config)
         except KeyboardInterrupt: