refactoring configs; pulled network out of graph; created trainer heirarchy (#51)

* changed config graph structure

* removed network udner graphs; added new heirarchy trainer

* fixed callback in occupancy graph

* lint

* changed register callback to setter method

docs/tooling/logging.md

@@ -11,9 +11,9 @@ logging:
     max_buffer_size: 20     # defines how many steps to average over (if reporting averages)
     writer:                 # definition of all writers you want to use
         TensorboardWriter:  
-            save_dir: "./"  # must specify the output path for all writers
+            log_dir: "./"  # must specify the output path for all writers
         LocalWriter:
-            save_dir: "./"
+            log_dir: "./"
             stats_to_track:
                 [ITER_LOAD_TIME, ITER_TRAIN_TIME, RAYS_PER_SEC, CURR_TEST_PSNR]
             max_log_size: 10 

docs/tutorials/creating_graphs.md

@@ -115,20 +115,27 @@ To set up the graph config, create a new yaml under `configs/`.
 # configs/vanilla_nerf.yaml
 
 defaults:
-  - default_setup # inherit the basic yaml heirarchy
+  - graph_default # inherit the basic yaml heirarchy
   - _self_
 
+logging:
+  # <insert logging definitions here>
+
+trainer:
+  # <override configurations for loading/training/saving model here>
+
 experiment_name: blender_lego
 method_name: vanilla_nerf
 
-graph:
-    network:
-        _target_: pyrad.graph.vanilla_nerf.NeRFGraph # set the target to the graph you defined
-
-    # <insert any additional graph related overrides here>
-
 data:
-    # <insert any additional dataset related overrides here>
+  # <insert any dataset related overrides here>
+
+graph:
+   _target_: pyrad.graph.vanilla_nerf.NeRFGraph # set the target to the graph you defined
+  # <insert any graph related overrides here>
+
+optimizers:
+  # <insert any optimizer related overrides here>
 ```
 
 ## Training and testing