Merged PR 130: #1595: load session double run

## Summary
- Fixed the bug where session gets run twice when loading a session via CLI
- Added a test for the CLI run - xskipped while the bugfix for load session acting odd is tbd
- Fixed a minor bug in PrimAITE session where session_path is overwritten

## Test process
Added a new test for CLI, but xskipped while a different bug is tbd

Ran it locally and no longer runs another session after the loaded session
```
(venv) PS D:\Projects\ARCD\PrimAITE\PrimAITE> primaite session --load [REDACTED for security]\primaite\sessions\2023-07-20\2023-07-20_15-01-11
2023-07-20 15:04:21,320: Using: AgentFramework.SB3, AgentIdentifier.PPO, ActionType.NODE, observation_space=NODE_LINK_TABLE, Training: 5 episodes @ 256 stepsEvaluation: 5 episodes @ 256 steps
2023-07-20 15:04:21,335: Environment configuration loaded
Environment configuration loaded
2023-07-20 15:04:21,775: Welcome to the Primary-level AI Training Environment (PrimAITE) (version: 2.0.0rc1)
2023-07-20 15:04:21,775: The output directory for this session is: C:\Users\czar.echavez\primaite\sessions\2023-07-20\2023-07-20_15-04-21
2023-07-20 15:04:21,779: Beginning learning for 10 episodes @ 256 time steps...
2023-07-20 15:04:22,379: Episode: 1, Average Reward: -0.0020839843750000003
2023-07-20 15:04:23,137: Episode: 2, Average Reward: -0.0021933593750000004
2023-07-20 15:04:23,831: Episode: 3, Average Reward: -0.0022617187500000003
2023-07-20 15:04:24,486: Episode: 4, Average Reward: -0.002373046874999999
2023-07-20 15:04:25,125: Episode: 5, Average Reward: -0.0018066406250000014
2023-07-20 15:04:25,791: Episode: 6, Average Reward: -0.0017597656250000013
2023-07-20 15:04:26,415: Episode: 7, Average Reward: -0.0018437500000000014
2023-07-20 15:04:27,053: Episode: 8, Average Reward: -0.0019101562500000015
2023-07-20 15:04:27,715: Episode: 9, Average Reward: -0.0016777343750000013
2023-07-20 15:04:28,359: Episode: 10, Average Reward: -0.0015976562500000012
2023-07-20 15:04:28,550: Finished learning
2023-07-20 15:04:30,851: Beginning deterministic evaluation for 5 episodes @ 256 time steps...
2023-07-20 15:04:31,243: Episode: 1, Average Reward: -0.0018515625000000014
2023-07-20 15:04:31,663: Episode: 2, Average Reward: -0.0018515625000000014
2023-07-20 15:04:32,112: Episode: 3, Average Reward: -0.0018515625000000014
2023-07-20 15:04:32,505: Episode: 4, Average Reward: -0.0018515625000000014
2023-07-20 15:04:32,904: Episode: 5, Average Reward: -0.0018515625000000014
2023-07-20 15:04:32,998: Finished evaluation

```

Also fixed the xskipped tests, since the double running seems to have caused the issue of rewards not matching.

Added a test that runs the PrimAITE in CLI

## Checklist
- [x] This PR is linked to a **work item**
- [x] I have performed **self-review** of the code
- [x] I have written **tests** for any new functionality added with this PR
- [x] I have updated the **documentation** if this PR changes or adds functionality
- [x] I have run **pre-commit** checks for code style

#1595:
- Fixed the...

src/primaite/cli.py

@@ -173,15 +173,18 @@ def session(tc: Optional[str] = None, ldc: Optional[str] = None, load: Optional[
     from primaite.main import run
 
     if load is not None:
+        # run a loaded session
         run(session_path=load)
 
-    if not tc:
-        tc = main_training_config_path()
+    else:
+        # start a new session using tc and ldc
+        if not tc:
+            tc = main_training_config_path()
 
-    if not ldc:
-        ldc = dos_very_basic_config_path()
+        if not ldc:
+            ldc = dos_very_basic_config_path()
 
-    run(training_config_path=tc, lay_down_config_path=ldc)
+        run(training_config_path=tc, lay_down_config_path=ldc)
 
 
 @app.command()

src/primaite/primaite_session.py

@@ -72,13 +72,7 @@ class PrimaiteSession:
         if not isinstance(lay_down_config_path, Path):
             lay_down_config_path = Path(lay_down_config_path)
         self._lay_down_config_path: Final[Union[Path, str]] = lay_down_config_path
-        self._lay_down_config: Dict = lay_down_config.load(self._lay_down_config_path)
-
-        self._agent_session: AgentSessionABC = None  # noqa
-        self.session_path: Path = None  # noqa
-        self.timestamp_str: str = None  # noqa
-        self.learning_path: Path = None  # noqa
-        self.evaluation_path: Path = None  # noqa
+        self._lay_down_config: Dict = lay_down_config.load(self._lay_down_config_path)  # noqa
 
     def setup(self) -> None:
         """Performs the session setup."""