#1629 - Added rllib test

tests/config/training_config_main_rllib.yaml

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+# Training Config File
+
+# Sets which agent algorithm framework will be used.
+# Options are:
+# "SB3" (Stable Baselines3)
+# "RLLIB" (Ray RLlib)
+# "CUSTOM" (Custom Agent)
+agent_framework: RLLIB
+
+# Sets which deep learning framework will be used (by RLlib ONLY).
+# Default is TF (Tensorflow).
+# Options are:
+# "TF" (Tensorflow)
+# TF2 (Tensorflow 2.X)
+# TORCH (PyTorch)
+deep_learning_framework: TF2
+
+# Sets which Agent class will be used.
+# Options are:
+# "A2C" (Advantage Actor Critic coupled with either SB3 or RLLIB agent_framework)
+# "PPO" (Proximal Policy Optimization coupled with either SB3 or RLLIB agent_framework)
+# "HARDCODED" (The HardCoded agents coupled with an ACL or NODE action_type)
+# "DO_NOTHING" (The DoNothing agents coupled with an ACL or NODE action_type)
+# "RANDOM" (primaite.agents.simple.RandomAgent)
+# "DUMMY" (primaite.agents.simple.DummyAgent)
+agent_identifier: PPO
+
+# Sets whether Red Agent POL and IER is randomised.
+# Options are:
+# True
+# False
+random_red_agent: False
+
+# The (integer) seed to be used in random number generation
+# Default is None (null)
+seed: null
+
+# Set whether the agent will be deterministic instead of stochastic
+# Options are:
+# True
+# False
+deterministic: False
+
+# Sets what view of the environment the deterministic hardcoded agent has. The default is BASIC.
+# Options are:
+# "BASIC" (The current observation space only)
+# "FULL" (Full environment view with actions taken and reward feedback)
+hard_coded_agent_view: FULL
+
+# Sets How the Action Space is defined:
+# "NODE"
+# "ACL"
+# "ANY" node and acl actions
+action_type: NODE
+# observation space
+observation_space:
+  # flatten: true
+  components:
+    - name: NODE_LINK_TABLE
+    # - name: NODE_STATUSES
+    # - name: LINK_TRAFFIC_LEVELS
+
+
+# Number of episodes for training to run per session
+num_train_episodes: 10
+
+# Number of time_steps for training per episode
+num_train_steps: 256
+
+# Number of episodes for evaluation to run per session
+num_eval_episodes: 1
+
+# Number of time_steps for evaluation per episode
+num_eval_steps: 256
+
+# Sets how often the agent will save a checkpoint (every n time episodes).
+# Set to 0 if no checkpoints are required. Default is 10
+checkpoint_every_n_episodes: 10
+
+# Time delay (milliseconds) between steps for CUSTOM agents.
+time_delay: 5
+
+# Type of session to be run. Options are:
+# "TRAIN" (Trains an agent)
+# "EVAL" (Evaluates an agent)
+# "TRAIN_EVAL" (Trains then evaluates an agent)
+session_type: TRAIN_EVAL
+
+# Environment config values
+# The high value for the observation space
+observation_space_high_value: 1000000000
+
+# The Stable Baselines3 learn/eval output verbosity level:
+# Options are:
+# "NONE" (No Output)
+# "INFO" (Info Messages (such as devices and wrappers used))
+# "DEBUG" (All Messages)
+sb3_output_verbose_level: NONE
+
+# Reward values
+# Generic
+all_ok: 0
+# Node Hardware State
+off_should_be_on: -0.001
+off_should_be_resetting: -0.0005
+on_should_be_off: -0.0002
+on_should_be_resetting: -0.0005
+resetting_should_be_on: -0.0005
+resetting_should_be_off: -0.0002
+resetting: -0.0003
+# Node Software or Service State
+good_should_be_patching: 0.0002
+good_should_be_compromised: 0.0005
+good_should_be_overwhelmed: 0.0005
+patching_should_be_good: -0.0005
+patching_should_be_compromised: 0.0002
+patching_should_be_overwhelmed: 0.0002
+patching: -0.0003
+compromised_should_be_good: -0.002
+compromised_should_be_patching: -0.002
+compromised_should_be_overwhelmed: -0.002
+compromised: -0.002
+overwhelmed_should_be_good: -0.002
+overwhelmed_should_be_patching: -0.002
+overwhelmed_should_be_compromised: -0.002
+overwhelmed: -0.002
+# Node File System State
+good_should_be_repairing: 0.0002
+good_should_be_restoring: 0.0002
+good_should_be_corrupt: 0.0005
+good_should_be_destroyed: 0.001
+repairing_should_be_good: -0.0005
+repairing_should_be_restoring: 0.0002
+repairing_should_be_corrupt: 0.0002
+repairing_should_be_destroyed: 0.0000
+repairing: -0.0003
+restoring_should_be_good: -0.001
+restoring_should_be_repairing: -0.0002
+restoring_should_be_corrupt: 0.0001
+restoring_should_be_destroyed: 0.0002
+restoring: -0.0006
+corrupt_should_be_good: -0.001
+corrupt_should_be_repairing: -0.001
+corrupt_should_be_restoring: -0.001
+corrupt_should_be_destroyed: 0.0002
+corrupt: -0.001
+destroyed_should_be_good: -0.002
+destroyed_should_be_repairing: -0.002
+destroyed_should_be_restoring: -0.002
+destroyed_should_be_corrupt: -0.002
+destroyed: -0.002
+scanning: -0.0002
+# IER status
+red_ier_running: -0.0005
+green_ier_blocked: -0.001
+
+# Patching / Reset durations
+os_patching_duration: 5            # The time taken to patch the OS
+node_reset_duration: 5             # The time taken to reset a node (hardware)
+service_patching_duration: 5       # The time taken to patch a service
+file_system_repairing_limit: 5      # The time take to repair the file system
+file_system_restoring_limit: 5      # The time take to restore the file system
+file_system_scanning_limit: 5       # The time taken to scan the file system

tests/test_rllib_agent.py

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+import pytest
+
+from primaite import getLogger
+from primaite.config.lay_down_config import dos_very_basic_config_path
+from tests import TEST_CONFIG_ROOT
+
+_LOGGER = getLogger(__name__)
+
+
+@pytest.mark.parametrize(
+    "temp_primaite_session",
+    [[TEST_CONFIG_ROOT / "training_config_main_rllib.yaml", dos_very_basic_config_path()]],
+    indirect=True,
+)
+def test_primaite_session(temp_primaite_session):
+    """Test the training_config_main_rllib.yaml training config file."""
+    with temp_primaite_session as session:
+        session_path = session.session_path
+        assert session_path.exists()
+        session.learn()
+
+        assert len(session.learn_av_reward_per_episode().keys()) == 10