Summary: 59 instances, 55 unique

Text	Count
# TODO: refactor this when we migrate entirely to python 3	1
# TODO: Maybe implement some logic to make sure the park postion is always outside of the race track	1
# TODO: move this to before customer-specified so they can override	1
TODO: Deprecate and embed this class in ModelRecord.	1
#TODO: Include fault_code in the json schema to track faults - pending cloud team assistance	1
# TODO: delete upload_body_shell if body shell type is past in by cloud service	1
#TODO: delete this logic if cloud service team can always pass model metadata	1
# TODO: clean these lines up when we support multi-agent training.	1
self.num_checkpoints_to_keep = 4 # TODO: make this a parameter	1
# TODO:	1
#! TODO this needs to be removed after muti part is fixed, note we don't have	1
self.hyperparameters = ConfigurationList()  # TODO: move to shared	1
# DH TODO: check shape of self.num_actions. It should be int	1
#TODO: replace agent for multi agent training	1
# TODO: a model can only be put to pending, from pending state.	1
# TODO: Service team can't handle "version" key in Evaluation Metrics due to	1
#! TODO each agent should have own config	1
# TODO: replace 'agent' for multiagent training	1
#! TODO currently left and front camera use the same embedders, this is how it is wired up	1
#! TODO each agent should have own s3 bucket	1
TODO: implemement logic here if we decide to log non fatal error metrics	1
# TODO: conditional check to verify model is in *ing state while updating...	2
# TODO: use ConfigList from Coach launcher, and share customization code.	1
#! TODO decide whether we need lidar layers for different network types	1
#TODO: Include fault_code in the json schema to track faults - pending cloud team assistance	1
#TODO: Remove this whole class when nobody's using it any more.	1
TODO: remove this when we fully deprecate the RoboMaker + SageMaker jobs.	1
#TODO change agent to specific agent name for multip agent case	1
# TODO replace agent with agent_0 and so on for multiagent case	1
# TODO: figure out what display name to use during wait	1
# TODO: change this to os.makedirs(simtrace_dirname, exist_ok=True) when we migrate off python 2.7	2
#! TODO remove ignore_lock after refactoring this class	1
#! TODO decide if we want to have a deep-deep topology that differes from deep	1
#TODO: replace 'agent' with 'agent_0' for multi agent training and	1
# TODO: this is temp solution only. After cloud service backend completely migrate to	1
# TODO: Refactor the flow to remove conditional checks for specific algorithms	1
# TODO: a model eval_state can only be put to pending, from pending state	1
# TODO: find better way to load checkpoints that were saved with a global network into the online network	1
# TODO: delete after car_color is a mandatory yaml key	1
# TODO: replace 'agent' with specific agent name for multi agent training	1
# TODO: Hard coding the frustum values for now. These values need to be loaded from SDF directly	1
# TODO: Remove below camera_offsets and camera_pitch variables if we can get Camera pose directly	1
#TODO: Find an atomic way to check if file is present else create	1
# TODO: This code should be removed when the cloud service starts providing VIDEO_JOB_TYPE YAML parameter	1
#! TODO evaluate if this is the best way to reset the car	1
# TODO: Refactor the flow to remove conditional checks for specific algorithms	1
# TODO: replace 'agent' with name of each agent for multi-agent training	1
#TODO: remove this after converting all samples.	1
# % TODO - refactor this module to be more modular based on the training algorithm and avoid if-else	1
# TODO: add validation/instructions if multiple deployment	1
# TODO: replace 'agent' with name of each agent	3
# TODO: Since we are not running Grand Prix in RoboMaker,	1
# TODO: THIS CHECK IS VERY UGLY	1
MIN_RESET_COUNT = 10000 #TODO: change when console passes float("inf")	1
self.reward_space = RewardSpace(1, reward_success_threshold=self.reward_success_threshold)  # TODO: add a getter and setter	1