Eng/doc nits (#650)

cleanup install

docs/developer_guides/config.md

@@ -83,23 +83,33 @@ After placing your new `Config` class into the `model_configs` dictionary, you c
 ### Modifying from CLI
 Often times, you just want to play with the parameters of an existing model without having to specify a new one. You can easily do so via CLI. Below, we showcase some useful CLI commands.
 
-```bash
-# list out all existing models
-ns-train --help
+- List out all existing models
+    ```bash
+    ns-train --help
+    ```
 
-# list out all exist configurable parameters for {MODEL_NAME}
-ns-train {MODEL_NAME} --help
+- List out all exist configurable parameters for `{MODEL_NAME}`
+    ```bash
+    ns-train {MODEL_NAME} --help
+    ```
 
-# change the train/eval dataset
-ns-train {MODEL_NAME} --data DATA_PATH
+- Change the train/eval dataset
+    ```bash
+    ns-train {MODEL_NAME} --data DATA_PATH
+    ```
 
-# enable the viewer
-ns-train {MODEL_NAME} --vis viewer
+- Enable the viewer
+    ```bash
+    ns-train {MODEL_NAME} --vis viewer
+    ```
 
-# see what options are available for the specified dataparser (e.g. blender-data)
-ns-train {MODEL_NAME} {DATA_PARSER} --help
+- See what options are available for the specified dataparser (e.g. blender-data)
+    ```bash
+    ns-train {MODEL_NAME} {DATA_PARSER} --help
+    ```
 
-# run with changed dataparser attributes and viewer on
-# NOTE: the dataparser and associated configurations go at the end of the command
-ns-train {MODEL_NAME} --vis viewer {DATA_PARSER} --scale-factor 0.5
-```
+- Run with changed dataparser attributes and viewer on
+    ```bash
+    # NOTE: the dataparser and associated configurations go at the end of the command
+    ns-train {MODEL_NAME} --vis viewer {DATA_PARSER} --scale-factor 0.5
+    ```

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
 

docs/quickstart/installation.md

@@ -23,13 +23,13 @@ pip install git+https://github.com/NVlabs/tiny-cuda-nn/#subdirectory=bindings/to
 
 ## Installing nerfstudio
 
-Pip package:
+**From pip**
 
 ```bash
 pip install nerfstudio
 ```
 
-If you want the latest and greatest:
+**From source**
 
 ```bash
 git clone git@github.com:nerfstudio-project/nerfstudio.git
@@ -38,9 +38,12 @@ pip install -e .
 
 ```
 
-### Optional
+:::{admonition} Note
+:class: info
+Below are optional installations, but makes developing with nerfstudio much more convenient.
+:::
 
-#### Tab completion (bash & zsh)
+**Tab completion (bash & zsh)**
 
 This needs to be rerun when the CLI changes, for example if nerfstudio is updated.
 
@@ -48,7 +51,7 @@ This needs to be rerun when the CLI changes, for example if nerfstudio is update
 ns-install-cli
 ```
 
-### Development packages
+**Development packages**
 
 ```bash
 pip install -e.[dev]
@@ -61,9 +64,11 @@ pip install -e.[docs]
 - [Installation errors, File "setup.py" not found](pip-install-error)
 - [Runtime errors, "len(sources) > 0".](cuda-sources-error)
 
+ <br />
+
 (tiny-cuda-error)=
 
-#### TinyCUDA installation errors out with cuda mismatch
+**TinyCUDA installation errors out with cuda mismatch**
 
 While installing tiny-cuda, you run into: `The detected CUDA version mismatches the version that was used to compile PyTorch (10.2). Please make sure to use the same CUDA versions.`
 
@@ -73,9 +78,11 @@ While installing tiny-cuda, you run into: `The detected CUDA version mismatches
 pip install torch==1.12.1+cu113 torchvision==0.13.1+cu113 -f https://download.pytorch.org/whl/torch_stable.html
 ```
 
+ <br />
+
 (pip-install-error)=
 
-#### Installation errors, File "setup.py" not found
+**Installation errors, File "setup.py" not found**
 
 When installing dependencies and nerfstudio with `pip install -e .`, you run into: `ERROR: File "setup.py" not found. Directory cannot be installed in editable mode`
 
@@ -86,9 +93,11 @@ This can be fixed by upgrading pip to the latest version:
 python -m pip install --upgrade pip
 ```
 
+ <br />
+
 (cuda-sources-error)=
 
-#### Runtime errors: "len(sources) > 0", "ctype = \_C.ContractionType(type.value) ; TypeError: 'NoneType' object is not callable".
+**Runtime errors: "len(sources) > 0", "ctype = \_C.ContractionType(type.value) ; TypeError: 'NoneType' object is not callable".**
 
 When running `train.py `, an error occurs when installing cuda files in the backend code.