src/markov/rollout_worker.py (9 lines):
	- line 140: #TODO change agent to specific agent name for multip agent case
	- line 312: # TODO: replace 'agent' with name of each agent for multi-agent training
	- line 327: # TODO: replace 'agent' with name of each agent
	- line 357: #! TODO each agent should have own s3 bucket
	- line 372: #TODO: replace agent for multi agent training
	- line 374: # TODO replace agent with agent_0 and so on for multiagent case
	- line 407: #TODO: replace 'agent' with 'agent_0' for multi agent training and
	- line 434: # TODO: replace 'agent' with specific agent name for multi agent training
	- line 442: # TODO: replace 'agent' with name of each agent


src/markov/training_worker.py (5 lines):
	- line 86: # TODO: Refactor the flow to remove conditional checks for specific algorithms
	- line 103: # TODO: Refactor the flow to remove conditional checks for specific algorithms
	- line 227: # TODO: replace 'agent' with name of each agent
	- line 275: #! TODO each agent should have own config
	- line 324: # TODO: replace 'agent' for multiagent training


common/sagemaker_rl/orchestrator/clients/ddb/model_db_client.py (5 lines):
	- line 11: TODO: Deprecate and embed this class in ModelRecord.
	- line 54: # TODO: a model can only be put to pending, from pending state.
	- line 61: # TODO: conditional check to verify model is in *ing state while updating...
	- line 66: # TODO: a model eval_state can only be put to pending, from pending state
	- line 71: # TODO: conditional check to verify model is in *ing state while updating...


src/markov/boto/s3/files/yaml_file.py (4 lines):
	- line 149: # TODO: THIS CHECK IS VERY UGLY
	- line 153: # TODO: delete upload_body_shell if body shell type is past in by cloud service
	- line 159: # TODO: delete after car_color is a mandatory yaml key
	- line 212: #TODO: delete this logic if cloud service team can always pass model metadata


src/markov/log_handler/exception_handler.py (4 lines):
	- line 43: #TODO: Find an atomic way to check if file is present else create
	- line 65: #TODO: Include fault_code in the json schema to track faults - pending cloud team assistance
	- line 87: #TODO: Include fault_code in the json schema to track faults - pending cloud team assistance
	- line 209: # TODO: refactor this when we migrate entirely to python 3


src/markov/metrics/s3_metrics.py (4 lines):
	- line 37: #! TODO this needs to be removed after muti part is fixed, note we don't have
	- line 104: # TODO: change this to os.makedirs(simtrace_dirname, exist_ok=True) when we migrate off python 2.7
	- line 289: # TODO: change this to os.makedirs(simtrace_dirname, exist_ok=True) when we migrate off python 2.7
	- line 387: # TODO: Service team can't handle "version" key in Evaluation Metrics due to


common/sagemaker_rl/ray_launcher.py (3 lines):
	- line 94: # TODO: use ConfigList from Coach launcher, and share customization code.
	- line 98: # TODO: move this to before customer-specified so they can override
	- line 103: self.hyperparameters = ConfigurationList()  # TODO: move to shared


src/markov/sensors/utils.py (3 lines):
	- line 55: #! TODO currently left and front camera use the same embedders, this is how it is wired up
	- line 167: #! TODO decide if we want to have a deep-deep topology that differes from deep
	- line 188: #! TODO decide whether we need lidar layers for different network types


src/markov/cameras/frustum.py (2 lines):
	- line 24: # TODO: Hard coding the frustum values for now. These values need to be loaded from SDF directly
	- line 30: # TODO: Remove below camera_offsets and camera_pitch variables if we can get Camera pose directly


src/markov/multi_agent_coach/multi_agent_graph_manager.py (2 lines):
	- line 50: self.num_checkpoints_to_keep = 4 # TODO: make this a parameter
	- line 542: # TODO: find better way to load checkpoints that were saved with a global network into the online network


src/markov/utils.py (2 lines):
	- line 156: # TODO: This code should be removed when the cloud service starts providing VIDEO_JOB_TYPE YAML parameter
	- line 221: # TODO:


src/markov/sagemaker_graph_manager.py (2 lines):
	- line 158: # % TODO - refactor this module to be more modular based on the training algorithm and avoid if-else
	- line 214: # TODO: clean these lines up when we support multi-agent training.


src/markov/evaluation_worker.py (2 lines):
	- line 55: MIN_RESET_COUNT = 10000 #TODO: change when console passes float("inf")
	- line 89: # TODO: Since we are not running Grand Prix in RoboMaker,


common/sagemaker_rl/coach_launcher.py (2 lines):
	- line 124: #TODO: remove this after converting all samples.
	- line 268: #TODO: Remove this whole class when nobody's using it any more.


src/markov/s3_boto_data_store.py (1 line):
	- line 39: #! TODO remove ignore_lock after refactoring this class


src/lib/sagemaker_bootstrap.py (1 line):
	- line 141: TODO: remove this when we fully deprecate the RoboMaker + SageMaker jobs.


src/markov/virtual_event/virtual_event_agent_data.py (1 line):
	- line 108: # TODO: this is temp solution only. After cloud service backend completely migrate to


src/markov/agent_ctrl/rollout_agent_ctrl.py (1 line):
	- line 152: #! TODO evaluate if this is the best way to reset the car


src/markov/virtual_event/constants.py (1 line):
	- line 53: # TODO: figure out what display name to use during wait


common/sagemaker_rl/orchestrator/workflow/manager/experiment_manager.py (1 line):
	- line 1125: # TODO: add validation/instructions if multiple deployment


src/markov/multi_agent_coach/architectures/tensorflow_components/heads/sac_head.py (1 line):
	- line 44: # DH TODO: check shape of self.num_actions. It should be int


src/markov/log_handler/deepracer_exceptions.py (1 line):
	- line 214: TODO: implemement logic here if we decide to log non fatal error metrics


src/markov/track_geom/utils.py (1 line):
	- line 154: # TODO: Maybe implement some logic to make sure the park postion is always outside of the race track


src/markov/multi_agent_coach/multi_agent_environment.py (1 line):
	- line 71: self.reward_space = RewardSpace(1, reward_success_threshold=self.reward_success_threshold)  # TODO: add a getter and setter