Eng/doc nits (#650)

cleanup install

docs/developer_guides/debugging_tools/benchmarking.md

@@ -26,14 +26,15 @@ To view all the arguments and annotations, you can run `./scripts/benchmarking/l
 
 A full example would be:
 
-```bash
+- With `-g` specifying gpus
+    ```bash
+    ./scripts/benchmarking/launch_train_blender.sh -m nerfacto -g 0 1 2 3
+    ```
 
-# with -g specifying gpus
-./scripts/benchmarking/launch_train_blender.sh -m nerfacto -g 0 1 2 3
-
-# without -g automatically finds available gpus
-./scripts/benchmarking/launch_train_blender.sh -m nerfacto
-```
+- Without `-g` automatically finds available gpus
+    ```bash
+    ./scripts/benchmarking/launch_train_blender.sh -m nerfacto
+    ```
 
 The script will automatically launch training on all of the items and save the checkpoints in an output directory with the experiment name and current timestamp.
 

docs/developer_guides/debugging_tools/local_logger.md

@@ -2,28 +2,26 @@
 
 The `LocalWriter` simply outputs numerical stats to the terminal.
 You can specify additional parameters to customize your logging experience.
+A skeleton of the local writer config is defined below.
 
 ```python
+"""nerfstudio/configs/base_config.py""""
+
 @dataclass
 class LocalWriterConfig(InstantiateConfig):
     """Local Writer config"""
 
     _target: Type = writer.LocalWriter
-    """target class to instantiate"""
     enable: bool = False
-    """if True enables local logging, else disables"""
     stats_to_track: Tuple[writer.EventName, ...] = (
         writer.EventName.ITER_TRAIN_TIME,
-        writer.EventName.TRAIN_RAYS_PER_SEC,
-        writer.EventName.CURR_TEST_PSNR,
-        writer.EventName.VIS_RAYS_PER_SEC,
-        writer.EventName.TEST_RAYS_PER_SEC,
+        ...
     )
-    """specifies which stats will be logged/printed to terminal"""
     max_log_size: int = 10
-    """maximum number of rows to print before wrapping. if 0, will print everything."""
+
 ```
 
+You can customize the local writer by editing the attributes:
 - `enable`: enable/disable the logger.
 - `stats_to_track`: all the stats that you want to print to the terminal (see list under `EventName` in `utils/writer.py`). You can add or remove any of the defined enums.
 - `max_log_size`: how much content to print onto the screen (By default, only print 10 lines onto the screen at a time). If 0, will print everything without deleting any previous lines.
@@ -39,10 +37,12 @@ If you want to create a new stat to track, simply add the stat name to the `Even
 The local writer is easily configurable via CLI.
 A few common commands to use:
 
-```bash
-# disable local writer
-ns-train {METHOD_NAME} --logging.local-writer.no-enable
+- Disable local writer
+    ```bash
+    ns-train {METHOD_NAME} --logging.local-writer.no-enable
+    ```
 
-# disable line wrapping
-ns-train {METHOD_NAME} --logging.local-writer.max-log-size=0
-```
+- Disable line wrapping
+    ```bash
+    ns-train {METHOD_NAME} --logging.local-writer.max-log-size=0
+    ```

docs/developer_guides/debugging_tools/profiling.md

@@ -44,16 +44,16 @@ pip install py-spy
 
 To perform the profiling, you can either specify that you want to generate a flame graph or generate a live-view of the profiler.
 
-```bash
-## flame graph: with wandb logging and our inhouse logging disabled
-program="ns-train nerfacto -- --vis=wandb --logging.no-enable-profiler blender-data"
-py-spy record -o {PATH_TO_OUTPUT_SVG} $program
-```
-
-```bash
-## top-down stats: running same program configuration as above
-py-spy top $program
-```
+- flame graph: with wandb logging and our inhouse logging disabled
+    ```bash
+    program="ns-train nerfacto -- --vis=wandb --logging.no-enable-profiler blender-data"
+    py-spy record -o {PATH_TO_OUTPUT_SVG} $program
+    ```
+- top-down stats: running same program configuration as above
+    ```bash
+    py-spy top $program
+    ```
+    
 :::{admonition} Attention
 :class: attention