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Merge remote-tracking branch 'origin/dev' into feature/901-change-functionality-acl-rules

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This commit is contained in:
SunilSamra
2023-07-13 16:48:02 +01:00
parent 771061a218 f3809054bf
commit 79d77c85c4
33 changed files with 677 additions and 260 deletions
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47
src/primaite/config/training_config.py
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@@ -61,11 +61,17 @@ class TrainingConfig:
action_type: ActionType = ActionType.ANY
"The ActionType to use"
num_episodes: int = 10
"The number of episodes to train over"
num_train_episodes: int = 10
"The number of episodes to train over during an training session"
num_steps: int = 256
"The number of steps in an episode"
num_train_steps: int = 256
"The number of steps in an episode during an training session"
num_eval_episodes: int = 1
"The number of episodes to train over during an evaluation session"
num_eval_steps: int = 256
"The number of steps in an episode during an evaluation session"
checkpoint_every_n_episodes: int = 5
"The agent will save a checkpoint every n episodes"
@@ -249,8 +255,17 @@ class TrainingConfig:
tc += f"{self.hard_coded_agent_view}, "
tc += f"{self.action_type}, "
tc += f"observation_space={self.observation_space}, "
tc += f"{self.num_episodes} episodes @ "
tc += f"{self.num_steps} steps"
if self.session_type is SessionType.TRAIN:
tc += f"{self.num_train_episodes} episodes @ "
tc += f"{self.num_train_steps} steps"
elif self.session_type is SessionType.EVAL:
tc += f"{self.num_eval_episodes} episodes @ "
tc += f"{self.num_eval_steps} steps"
else:
tc += f"Training: {self.num_eval_episodes} episodes @ "
tc += f"{self.num_eval_steps} steps"
tc += f"Evaluation: {self.num_eval_episodes} episodes @ "
tc += f"{self.num_eval_steps} steps"
return tc
@@ -298,24 +313,27 @@ def convert_legacy_training_config_dict(
agent_framework: AgentFramework = AgentFramework.SB3,
agent_identifier: AgentIdentifier = AgentIdentifier.PPO,
action_type: ActionType = ActionType.ANY,
num_steps: int = 256,
num_train_steps: int = 256,
) -> Dict[str, Any]:
"""
Convert a legacy training config dict to the new format.
:param legacy_config_dict: A legacy training config dict.
:param agent_framework: The agent framework to use as legacy training configs don't have agent_framework values.
:param agent_identifier: The red agent identifier to use as legacy training configs don't have agent_identifier
values.
:param action_type: The action space type to set as legacy training configs don't have action_type values.
:param num_steps: The number of steps to set as legacy training configs don't have num_steps values.
:param agent_framework: The agent framework to use as legacy training
configs don't have agent_framework values.
:param agent_identifier: The red agent identifier to use as legacy
training configs don't have agent_identifier values.
:param action_type: The action space type to set as legacy training configs
don't have action_type values.
:param num_train_steps: The number of steps to set as legacy training configs
don't have num_train_steps values.
:return: The converted training config dict.
"""
config_dict = {
"agent_framework": agent_framework.name,
"agent_identifier": agent_identifier.name,
"action_type": action_type.name,
"num_steps": num_steps,
"num_train_steps": num_train_steps,
"sb3_output_verbose_level": SB3OutputVerboseLevel.INFO.name,
}
session_type_map = {"TRAINING": "TRAIN", "EVALUATION": "EVAL"}
@@ -336,7 +354,8 @@ def _get_new_key_from_legacy(legacy_key: str) -> str:
"""
key_mapping = {
"agentIdentifier": None,
"numEpisodes": "num_episodes",
"numEpisodes": "num_train_episodes",
"numSteps": "num_train_steps",
"timeDelay": "time_delay",
"configFilename": None,
"sessionType": "session_type",