Eng/better configs (#113)

* update possible config setup

* finished porting remaning configs

* fix bugs

* change mattprot to radiance in config

configs/default_setup.yaml

@@ -1,7 +1,6 @@
 defaults:
   # This makes the logging module logs colorful
   - data: default_data.yaml
-  - graph: default_graph.yaml
   - logging: default_logging.yaml
   - override hydra/job_logging: colorlog
   - override hydra/hydra_logging: colorlog
@@ -15,12 +14,10 @@ hydra:
     # Example "outputs/mnist/classifier/baseline/2021-03-10-141516"
     dir: outputs/${experiment_name}/${method_name}/${now:%Y-%m-%d_%H%M%S}
 
-experiment_name: blender_lego
-method_name: vanilla_nerf
-
 # machine options
 machine_config:
   num_gpus: 1
   num_machines: 1
   machine_rank: 0
   dist_url: auto
+

configs/graph/default_graph.yaml

@@ -1,32 +0,0 @@
-# saving model specifications
-model_dir: /tmp/radiance_models/
-steps_per_save: null
-steps_per_test: 100
-max_num_iterations: 1000000
-
-# pretrained loading options
-resume_train:
-  load_dir: # pretrained model directory
-  load_step: # pretrained model's step number
-
-network:
-  _target_: radiance.nerf.graph.vanilla_nerf.NeRFGraph
-  near_plane: 2.0
-  far_plane: 6.0
-  num_coarse_samples: 64
-  num_importance_samples: 128
-
-  loss_coefficients: # loss coefficients
-    rgb_loss_coarse: 1.0
-    rgb_loss_fine: 1.0
-
-# optimizer options for network
-param_groups:
-  fields:
-    optimizer:
-      _target_: torch.optim.RAdam
-      lr: 0.0005
-    scheduler:
-      _target_: radiance.nerf.optimizers.ExponentialDecaySchedule
-      lr_final: 0.000005
-      max_steps: 1000000

configs/graph/instant_ngp_graph.yaml

@@ -1,15 +0,0 @@
-defaults:
-  - default_graph.yaml
-  - _self_
-
-network:
-  _target_: radiance.nerf.graph.instant_ngp.NGPGraph
-  field_implementation: torch # torch, tcnn, ...
-  loss_coefficients: # loss coefficients
-    rgb_loss: 1.0
-
-# optimizer options for network
-param_groups:
-  fields:
-    optimizer:
-      lr: 1e-2

configs/graph/nerfw_graph.yaml

@@ -1,11 +0,0 @@
-defaults:
-  - default_graph.yaml
-  - _self_
-
-network:
-  _target_: radiance.nerf.graph.nerfw.NerfWGraph
-  loss_coefficients: # loss coefficients
-    rgb_loss_coarse: 1.0
-    rgb_loss_fine: 1.0
-    uncertainty_loss: 1.0
-    density_loss: 0.01

configs/graph/semantic_nerf_graph.yaml

@@ -1,10 +0,0 @@
-defaults:
-  - default_graph.yaml
-  - _self_
-
-network:
-  _target_: radiance.nerf.graph.semantic_nerf.SemanticNerfGraph
-  loss_coefficients: # loss coefficients
-    rgb_loss_coarse: 1.0
-    rgb_loss_fine: 1.0
-    semantic_loss_fine: 0.05

configs/instant_ngp.yaml

@@ -1,7 +1,20 @@
 defaults:
-  - default
-  - override graph: instant_ngp_graph
+  - vanilla_nerf
   - _self_
+
 method_name: instant_ngp
 data.dataloader.num_rays_per_batch: 4096
-data.val_num_rays_per_chunk: 16384
+data.val_num_rays_per_chunk: 16384
+
+graph:
+  network:
+    _target_: radiance.nerf.graph.instant_ngp.NGPGraph
+    field_implementation: torch # torch, tcnn, ...
+    loss_coefficients: # loss coefficients
+      rgb_loss: 1.0
+
+  # optimizer options for network
+  param_groups:
+    fields:
+      optimizer:
+        lr: 1e-2

configs/instant_ngp_tcnn.yaml

@@ -1,7 +1,7 @@
 defaults:
-  - default
-  - override graph: instant_ngp_graph
+  - instant_ngp
   - _self_
+  
 method_name: instant_ngp
 data:
   dataloader:

configs/nerfw.yaml

@@ -1,14 +1,21 @@
 defaults:
-  - default
+  - vanilla_nerf
   - override data/dataset: friends_TBBT-big_living_room
-  - override graph: nerfw_graph
   - _self_
 
 experiment_name: friends_TBBT-big_living_room
 method_name: nerfw
 
-network:
-  near_plane: 0.1
-  far_plane: 10.0
-  num_coarse_samples: 64
-  num_importance_samples: 64
+graph:
+  network:
+    _target_: radiance.nerf.graph.nerfw.NerfWGraph
+    near_plane: 0.1
+    far_plane: 10.0
+    num_coarse_samples: 64
+    num_importance_samples: 64
+
+    loss_coefficients: # loss coefficients
+      rgb_loss_coarse: 1.0
+      rgb_loss_fine: 1.0
+      uncertainty_loss: 1.0
+      density_loss: 0.01

configs/semantic_nerf.yaml

@@ -1,14 +1,20 @@
 defaults:
-  - default
+  - vanilla_nerf
   - override data/dataset: friends_TBBT-big_living_room
-  - override graph: semantic_nerf_graph
   - _self_
 
 experiment_name: friends_TBBT-big_living_room
 method_name: semantic_nerf
 
-network:
-  near_plane: 0.1
-  far_plane: 10.0
-  num_coarse_samples: 64
-  num_importance_samples: 64
+graph:
+  network:
+    _target_: radiance.nerf.graph.semantic_nerf.SemanticNerfGraph
+    near_plane: 0.1
+    far_plane: 10.0
+    num_coarse_samples: 64
+    num_importance_samples: 64
+
+    loss_coefficients: # loss coefficients
+      rgb_loss_coarse: 1.0
+      rgb_loss_fine: 1.0
+      semantic_loss_fine: 0.05

configs/tests/test_dryrun.yaml

@@ -1,5 +1,5 @@
 defaults:
-  - default
+  - vanilla_nerf
 
 dry_run: true
 

configs/vanilla_nerf.yaml

@@ -0,0 +1,40 @@
+defaults:
+  - default_setup
+  - _self_
+
+experiment_name: blender_lego
+method_name: vanilla_nerf
+
+graph:
+  # saving model specifications
+  model_dir: /tmp/radiance_models/
+  steps_per_save: null
+  steps_per_test: 100
+  max_num_iterations: 1000000
+
+  # pretrained loading options
+  resume_train:
+    load_dir: # pretrained model directory
+    load_step: # pretrained model's step number
+
+  network:
+    _target_: radiance.nerf.graph.vanilla_nerf.NeRFGraph
+    near_plane: 2.0
+    far_plane: 6.0
+    num_coarse_samples: 64
+    num_importance_samples: 128
+
+    loss_coefficients: # loss coefficients
+      rgb_loss_coarse: 1.0
+      rgb_loss_fine: 1.0
+
+  # optimizer options for network
+  param_groups:
+    fields:
+      optimizer:
+        _target_: torch.optim.RAdam
+        lr: 0.0005
+      scheduler:
+        _target_: radiance.nerf.optimizers.ExponentialDecaySchedule
+        lr_final: 0.000005
+        max_steps: 1000000

scripts/benchmarking/run_benchmark.py

@@ -17,7 +17,7 @@ from radiance.nerf.trainer import Trainer
 BENCH = {
     "method": "vanilla_nerf",
     "hydra_base_dir": "outputs/",
-    "benchmark_date": "05-24-2022",
+    "benchmark_date": "05-26-2022",
     "object_list": ["mic", "ficus", "chair", "hotdog", "materials", "drums", "ship", "lego"],
 }
 

scripts/run_train.py

@@ -198,7 +198,7 @@ def launch(
             profiler.flush_profiler(config.logging)
 
 
-@hydra.main(config_path="../configs", config_name="default.yaml")
+@hydra.main(config_path="../configs", config_name="vanilla_nerf.yaml")
 def main(config: DictConfig):
     """Main function."""
     launch(