fix setup.cfg (fix #889)

docs/tutorial/save-load.md

 
 # Save and Load models
 
-## Work with TF Checkpoint
+## Inspect a TF Checkpoint
 
 The `ModelSaver` callback saves the model to the directory defined by `logger.get_logger_dir()`,
 in TensorFlow checkpoint format.
@@ -21,9 +21,9 @@ demos how to print all variables and their shapes in a checkpoint.
 It takes a metagraph file (which is also saved by `ModelSaver`) and only saves variables that the model needs at inference time.
 It can dump the model to a `var-name: value` dict saved in npz format.
 
-## Load a Model
+## Load a Model to a Session
 
-Model loading (in either training or testing) is through the `session_init` interface.
+Model loading (in either training or inference) is through the `session_init` interface.
 Currently there are two ways a session can be restored:
 [session_init=SaverRestore(...)](../modules/tfutils.html#tensorpack.tfutils.sessinit.SaverRestore)
 which restores a TF checkpoint,

setup.cfg

@@ -7,7 +7,8 @@ license = Apache
 
 [options]
 zip_safe = False		    # dataset and __init__ use file
-packages = find:				# will call find_packages()
+# will call find_packages()
+packages = find:
 
 [wheel]
 universal = 1