reinforcement_learning/rl_deepracer_robomaker_coach_gazebo/src/markov/rollout_worker.py (9 lines): - line 160: # TODO change agent to specific agent name for multip agent case - line 365: # TODO: replace 'agent' with name of each agent for multi-agent training - line 382: # TODO: replace 'agent' with name of each agent - line 418: #! TODO each agent should have own s3 bucket - line 433: # TODO: replace agent for multi agent training - line 435: # TODO replace agent with agent_0 and so on for multiagent case - line 478: # TODO: replace 'agent' with 'agent_0' for multi agent training and - line 517: # TODO: replace 'agent' with specific agent name for multi agent training - line 527: # TODO: replace 'agent' with name of each agent reinforcement_learning/rl_managed_spot_cartpole_coach/common/sagemaker_rl/orchestrator/clients/ddb/model_db_client.py (5 lines): - line 12: TODO: Deprecate and embed this class in ModelRecord. - line 56: # TODO: a model can only be put to pending, from pending state. - line 63: # TODO: conditional check to verify model is in *ing state while updating... - line 68: # TODO: a model eval_state can only be put to pending, from pending state - line 73: # TODO: conditional check to verify model is in *ing state while updating... reinforcement_learning/rl_deepracer_robomaker_coach_gazebo/common/sagemaker_rl/orchestrator/clients/ddb/model_db_client.py (5 lines): - line 12: TODO: Deprecate and embed this class in ModelRecord. - line 56: # TODO: a model can only be put to pending, from pending state. - line 63: # TODO: conditional check to verify model is in *ing state while updating... - line 68: # TODO: a model eval_state can only be put to pending, from pending state - line 73: # TODO: conditional check to verify model is in *ing state while updating... reinforcement_learning/rl_game_server_autopilot/sagemaker/common/sagemaker_rl/orchestrator/clients/ddb/model_db_client.py (5 lines): - line 12: TODO: Deprecate and embed this class in ModelRecord. - line 56: # TODO: a model can only be put to pending, from pending state. - line 63: # TODO: conditional check to verify model is in *ing state while updating... - line 68: # TODO: a model eval_state can only be put to pending, from pending state - line 73: # TODO: conditional check to verify model is in *ing state while updating... reinforcement_learning/rl_mountain_car_coach_gymEnv/common/sagemaker_rl/orchestrator/clients/ddb/model_db_client.py (5 lines): - line 12: TODO: Deprecate and embed this class in ModelRecord. - line 56: # TODO: a model can only be put to pending, from pending state. - line 63: # TODO: conditional check to verify model is in *ing state while updating... - line 68: # TODO: a model eval_state can only be put to pending, from pending state - line 73: # TODO: conditional check to verify model is in *ing state while updating... reinforcement_learning/rl_cartpole_coach/common/sagemaker_rl/orchestrator/clients/ddb/model_db_client.py (5 lines): - line 12: TODO: Deprecate and embed this class in ModelRecord. - line 56: # TODO: a model can only be put to pending, from pending state. - line 63: # TODO: conditional check to verify model is in *ing state while updating... - line 68: # TODO: a model eval_state can only be put to pending, from pending state - line 73: # TODO: conditional check to verify model is in *ing state while updating... reinforcement_learning/rl_portfolio_management_coach_customEnv/common/sagemaker_rl/orchestrator/clients/ddb/model_db_client.py (5 lines): - line 12: TODO: Deprecate and embed this class in ModelRecord. - line 56: # TODO: a model can only be put to pending, from pending state. - line 63: # TODO: conditional check to verify model is in *ing state while updating... - line 68: # TODO: a model eval_state can only be put to pending, from pending state - line 73: # TODO: conditional check to verify model is in *ing state while updating... reinforcement_learning/rl_unity_ray/common/sagemaker_rl/orchestrator/clients/ddb/model_db_client.py (5 lines): - line 12: TODO: Deprecate and embed this class in ModelRecord. - line 56: # TODO: a model can only be put to pending, from pending state. - line 63: # TODO: conditional check to verify model is in *ing state while updating... - line 68: # TODO: a model eval_state can only be put to pending, from pending state - line 73: # TODO: conditional check to verify model is in *ing state while updating... reinforcement_learning/rl_network_compression_ray_custom/common/sagemaker_rl/orchestrator/clients/ddb/model_db_client.py (5 lines): - line 12: TODO: Deprecate and embed this class in ModelRecord. - line 56: # TODO: a model can only be put to pending, from pending state. - line 63: # TODO: conditional check to verify model is in *ing state while updating... - line 68: # TODO: a model eval_state can only be put to pending, from pending state - line 73: # TODO: conditional check to verify model is in *ing state while updating... reinforcement_learning/rl_hvac_ray_energyplus/source/common/sagemaker_rl/orchestrator/clients/ddb/model_db_client.py (5 lines): - line 12: TODO: Deprecate and embed this class in ModelRecord. - line 56: # TODO: a model can only be put to pending, from pending state. - line 63: # TODO: conditional check to verify model is in *ing state while updating... - line 68: # TODO: a model eval_state can only be put to pending, from pending state - line 73: # TODO: conditional check to verify model is in *ing state while updating... reinforcement_learning/bandits_statlog_vw_customEnv/common/sagemaker_rl/orchestrator/clients/ddb/model_db_client.py (5 lines): - line 12: TODO: Deprecate and embed this class in ModelRecord. - line 56: # TODO: a model can only be put to pending, from pending state. - line 63: # TODO: conditional check to verify model is in *ing state while updating... - line 68: # TODO: a model eval_state can only be put to pending, from pending state - line 73: # TODO: conditional check to verify model is in *ing state while updating... reinforcement_learning/rl_knapsack_coach_custom/common/sagemaker_rl/orchestrator/clients/ddb/model_db_client.py (5 lines): - line 12: TODO: Deprecate and embed this class in ModelRecord. - line 56: # TODO: a model can only be put to pending, from pending state. - line 63: # TODO: conditional check to verify model is in *ing state while updating... - line 68: # TODO: a model eval_state can only be put to pending, from pending state - line 73: # TODO: conditional check to verify model is in *ing state while updating... reinforcement_learning/rl_hvac_coach_energyplus/common/sagemaker_rl/orchestrator/clients/ddb/model_db_client.py (5 lines): - line 12: TODO: Deprecate and embed this class in ModelRecord. - line 56: # TODO: a model can only be put to pending, from pending state. - line 63: # TODO: conditional check to verify model is in *ing state while updating... - line 68: # TODO: a model eval_state can only be put to pending, from pending state - line 73: # TODO: conditional check to verify model is in *ing state while updating... reinforcement_learning/rl_cartpole_batch_coach/common/sagemaker_rl/orchestrator/clients/ddb/model_db_client.py (5 lines): - line 12: TODO: Deprecate and embed this class in ModelRecord. - line 56: # TODO: a model can only be put to pending, from pending state. - line 63: # TODO: conditional check to verify model is in *ing state while updating... - line 68: # TODO: a model eval_state can only be put to pending, from pending state - line 73: # TODO: conditional check to verify model is in *ing state while updating... reinforcement_learning/rl_traveling_salesman_vehicle_routing_coach/common/sagemaker_rl/orchestrator/clients/ddb/model_db_client.py (5 lines): - line 12: TODO: Deprecate and embed this class in ModelRecord. - line 56: # TODO: a model can only be put to pending, from pending state. - line 63: # TODO: conditional check to verify model is in *ing state while updating... - line 68: # TODO: a model eval_state can only be put to pending, from pending state - line 73: # TODO: conditional check to verify model is in *ing state while updating... reinforcement_learning/rl_stock_trading_coach_customEnv/common/sagemaker_rl/orchestrator/clients/ddb/model_db_client.py (5 lines): - line 12: TODO: Deprecate and embed this class in ModelRecord. - line 56: # TODO: a model can only be put to pending, from pending state. - line 63: # TODO: conditional check to verify model is in *ing state while updating... - line 68: # TODO: a model eval_state can only be put to pending, from pending state - line 73: # TODO: conditional check to verify model is in *ing state while updating... reinforcement_learning/rl_roboschool_stable_baselines/common/sagemaker_rl/orchestrator/clients/ddb/model_db_client.py (5 lines): - line 12: TODO: Deprecate and embed this class in ModelRecord. - line 56: # TODO: a model can only be put to pending, from pending state. - line 63: # TODO: conditional check to verify model is in *ing state while updating... - line 68: # TODO: a model eval_state can only be put to pending, from pending state - line 73: # TODO: conditional check to verify model is in *ing state while updating... reinforcement_learning/common/sagemaker_rl/orchestrator/clients/ddb/model_db_client.py (5 lines): - line 12: TODO: Deprecate and embed this class in ModelRecord. - line 56: # TODO: a model can only be put to pending, from pending state. - line 63: # TODO: conditional check to verify model is in *ing state while updating... - line 68: # TODO: a model eval_state can only be put to pending, from pending state - line 73: # TODO: conditional check to verify model is in *ing state while updating... reinforcement_learning/rl_resource_allocation_ray_customEnv/common/sagemaker_rl/orchestrator/clients/ddb/model_db_client.py (5 lines): - line 12: TODO: Deprecate and embed this class in ModelRecord. - line 56: # TODO: a model can only be put to pending, from pending state. - line 63: # TODO: conditional check to verify model is in *ing state while updating... - line 68: # TODO: a model eval_state can only be put to pending, from pending state - line 73: # TODO: conditional check to verify model is in *ing state while updating... reinforcement_learning/rl_cartpole_ray/common/sagemaker_rl/orchestrator/clients/ddb/model_db_client.py (5 lines): - line 12: TODO: Deprecate and embed this class in ModelRecord. - line 56: # TODO: a model can only be put to pending, from pending state. - line 63: # TODO: conditional check to verify model is in *ing state while updating... - line 68: # TODO: a model eval_state can only be put to pending, from pending state - line 73: # TODO: conditional check to verify model is in *ing state while updating... reinforcement_learning/rl_predictive_autoscaling_coach_customEnv/common/sagemaker_rl/orchestrator/clients/ddb/model_db_client.py (5 lines): - line 12: TODO: Deprecate and embed this class in ModelRecord. - line 56: # TODO: a model can only be put to pending, from pending state. - line 63: # TODO: conditional check to verify model is in *ing state while updating... - line 68: # TODO: a model eval_state can only be put to pending, from pending state - line 73: # TODO: conditional check to verify model is in *ing state while updating... reinforcement_learning/rl_deepracer_robomaker_coach_gazebo/src/markov/training_worker.py (5 lines): - line 99: # TODO: Refactor the flow to remove conditional checks for specific algorithms - line 121: # TODO: Refactor the flow to remove conditional checks for specific algorithms - line 288: # TODO: replace 'agent' with name of each agent - line 342: #! TODO each agent should have own config - line 403: # TODO: replace 'agent' for multiagent training reinforcement_learning/rl_roboschool_ray/common/sagemaker_rl/orchestrator/clients/ddb/model_db_client.py (5 lines): - line 12: TODO: Deprecate and embed this class in ModelRecord. - line 56: # TODO: a model can only be put to pending, from pending state. - line 63: # TODO: conditional check to verify model is in *ing state while updating... - line 68: # TODO: a model eval_state can only be put to pending, from pending state - line 73: # TODO: conditional check to verify model is in *ing state while updating... reinforcement_learning/bandits_recsys_movielens_testbed/src/vw_agent.py (4 lines): - line 115: # TODO: Check for errors in CLI args by polling the process - line 161: # TODO: Error handling in parsing the given example - line 177: # TODO: Error handling in parsing the given example - line 184: # TODO: Write to stdin in chunks so that PIPE buffer never overflows reinforcement_learning/rl_deepracer_robomaker_coach_gazebo/src/markov/boto/s3/files/yaml_file.py (4 lines): - line 158: # TODO: THIS CHECK IS VERY UGLY - line 162: # TODO: delete upload_body_shell if body shell type is past in by cloud service - line 168: # TODO: delete after car_color is a mandatory yaml key - line 228: # TODO: delete this logic if cloud service team can always pass model metadata reinforcement_learning/rl_deepracer_robomaker_coach_gazebo/src/markov/log_handler/exception_handler.py (4 lines): - line 44: # TODO: Find an atomic way to check if file is present else create - line 66: # TODO: Include fault_code in the json schema to track faults - pending cloud team assistance - line 89: # TODO: Include fault_code in the json schema to track faults - pending cloud team assistance - line 137: # TODO: refactor this when we migrate entirely to python 3 reinforcement_learning/rl_deepracer_robomaker_coach_gazebo/src/markov/sensors/utils.py (3 lines): - line 56: #! TODO currently left and front camera use the same embedders, this is how it is wired up - line 177: #! TODO decide if we want to have a deep-deep topology that differes from deep - line 207: #! TODO decide whether we need lidar layers for different network types reinforcement_learning/bandits_statlog_vw_customEnv/common/sagemaker_rl/ray_launcher.py (3 lines): - line 101: # TODO: use ConfigList from Coach launcher, and share customization code. - line 105: # TODO: move this to before customer-specified so they can override - line 111: self.hyperparameters = ConfigurationList() # TODO: move to shared reinforcement_learning/rl_portfolio_management_coach_customEnv/common/sagemaker_rl/ray_launcher.py (3 lines): - line 101: # TODO: use ConfigList from Coach launcher, and share customization code. - line 105: # TODO: move this to before customer-specified so they can override - line 111: self.hyperparameters = ConfigurationList() # TODO: move to shared reinforcement_learning/common/sagemaker_rl/ray_launcher.py (3 lines): - line 101: # TODO: use ConfigList from Coach launcher, and share customization code. - line 105: # TODO: move this to before customer-specified so they can override - line 111: self.hyperparameters = ConfigurationList() # TODO: move to shared reinforcement_learning/rl_roboschool_ray/common/sagemaker_rl/ray_launcher.py (3 lines): - line 101: # TODO: use ConfigList from Coach launcher, and share customization code. - line 105: # TODO: move this to before customer-specified so they can override - line 111: self.hyperparameters = ConfigurationList() # TODO: move to shared reinforcement_learning/rl_cartpole_batch_coach/common/sagemaker_rl/ray_launcher.py (3 lines): - line 101: # TODO: use ConfigList from Coach launcher, and share customization code. - line 105: # TODO: move this to before customer-specified so they can override - line 111: self.hyperparameters = ConfigurationList() # TODO: move to shared reinforcement_learning/rl_cartpole_coach/common/sagemaker_rl/ray_launcher.py (3 lines): - line 101: # TODO: use ConfigList from Coach launcher, and share customization code. - line 105: # TODO: move this to before customer-specified so they can override - line 111: self.hyperparameters = ConfigurationList() # TODO: move to shared reinforcement_learning/rl_game_server_autopilot/sagemaker/common/sagemaker_rl/ray_launcher.py (3 lines): - line 101: # TODO: use ConfigList from Coach launcher, and share customization code. - line 105: # TODO: move this to before customer-specified so they can override - line 111: self.hyperparameters = ConfigurationList() # TODO: move to shared reinforcement_learning/rl_network_compression_ray_custom/common/sagemaker_rl/ray_launcher.py (3 lines): - line 101: # TODO: use ConfigList from Coach launcher, and share customization code. - line 105: # TODO: move this to before customer-specified so they can override - line 111: self.hyperparameters = ConfigurationList() # TODO: move to shared reinforcement_learning/rl_traveling_salesman_vehicle_routing_coach/common/sagemaker_rl/ray_launcher.py (3 lines): - line 101: # TODO: use ConfigList from Coach launcher, and share customization code. - line 105: # TODO: move this to before customer-specified so they can override - line 111: self.hyperparameters = ConfigurationList() # TODO: move to shared reinforcement_learning/rl_cartpole_ray/common/sagemaker_rl/ray_launcher.py (3 lines): - line 101: # TODO: use ConfigList from Coach launcher, and share customization code. - line 105: # TODO: move this to before customer-specified so they can override - line 111: self.hyperparameters = ConfigurationList() # TODO: move to shared reinforcement_learning/rl_hvac_ray_energyplus/source/common/sagemaker_rl/ray_launcher.py (3 lines): - line 101: # TODO: use ConfigList from Coach launcher, and share customization code. - line 105: # TODO: move this to before customer-specified so they can override - line 111: self.hyperparameters = ConfigurationList() # TODO: move to shared reinforcement_learning/rl_unity_ray/common/sagemaker_rl/ray_launcher.py (3 lines): - line 101: # TODO: use ConfigList from Coach launcher, and share customization code. - line 105: # TODO: move this to before customer-specified so they can override - line 111: self.hyperparameters = ConfigurationList() # TODO: move to shared reinforcement_learning/rl_managed_spot_cartpole_coach/common/sagemaker_rl/ray_launcher.py (3 lines): - line 101: # TODO: use ConfigList from Coach launcher, and share customization code. - line 105: # TODO: move this to before customer-specified so they can override - line 111: self.hyperparameters = ConfigurationList() # TODO: move to shared reinforcement_learning/rl_deepracer_robomaker_coach_gazebo/common/sagemaker_rl/ray_launcher.py (3 lines): - line 101: # TODO: use ConfigList from Coach launcher, and share customization code. - line 105: # TODO: move this to before customer-specified so they can override - line 111: self.hyperparameters = ConfigurationList() # TODO: move to shared reinforcement_learning/rl_resource_allocation_ray_customEnv/common/sagemaker_rl/ray_launcher.py (3 lines): - line 101: # TODO: use ConfigList from Coach launcher, and share customization code. - line 105: # TODO: move this to before customer-specified so they can override - line 111: self.hyperparameters = ConfigurationList() # TODO: move to shared reinforcement_learning/rl_mountain_car_coach_gymEnv/common/sagemaker_rl/ray_launcher.py (3 lines): - line 101: # TODO: use ConfigList from Coach launcher, and share customization code. - line 105: # TODO: move this to before customer-specified so they can override - line 111: self.hyperparameters = ConfigurationList() # TODO: move to shared reinforcement_learning/rl_stock_trading_coach_customEnv/common/sagemaker_rl/ray_launcher.py (3 lines): - line 101: # TODO: use ConfigList from Coach launcher, and share customization code. - line 105: # TODO: move this to before customer-specified so they can override - line 111: self.hyperparameters = ConfigurationList() # TODO: move to shared reinforcement_learning/rl_tic_tac_toe_coach_customEnv/common/sagemaker_rl/ray_launcher.py (3 lines): - line 96: # TODO: use ConfigList from Coach launcher, and share customization code. - line 100: # TODO: move this to before customer-specified so they can override - line 103: self.hyperparameters = ConfigurationList() # TODO: move to shared reinforcement_learning/rl_knapsack_coach_custom/common/sagemaker_rl/ray_launcher.py (3 lines): - line 101: # TODO: use ConfigList from Coach launcher, and share customization code. - line 105: # TODO: move this to before customer-specified so they can override - line 111: self.hyperparameters = ConfigurationList() # TODO: move to shared reinforcement_learning/rl_roboschool_stable_baselines/common/sagemaker_rl/ray_launcher.py (3 lines): - line 101: # TODO: use ConfigList from Coach launcher, and share customization code. - line 105: # TODO: move this to before customer-specified so they can override - line 111: self.hyperparameters = ConfigurationList() # TODO: move to shared reinforcement_learning/rl_predictive_autoscaling_coach_customEnv/common/sagemaker_rl/ray_launcher.py (3 lines): - line 101: # TODO: use ConfigList from Coach launcher, and share customization code. - line 105: # TODO: move this to before customer-specified so they can override - line 111: self.hyperparameters = ConfigurationList() # TODO: move to shared reinforcement_learning/rl_hvac_coach_energyplus/common/sagemaker_rl/ray_launcher.py (3 lines): - line 101: # TODO: use ConfigList from Coach launcher, and share customization code. - line 105: # TODO: move this to before customer-specified so they can override - line 111: self.hyperparameters = ConfigurationList() # TODO: move to shared reinforcement_learning/rl_portfolio_management_coach_customEnv/common/sagemaker_rl/coach_launcher.py (2 lines): - line 122: # TODO: remove this after converting all samples. - line 289: # TODO: Remove this whole class when nobody's using it any more. reinforcement_learning/rl_deepracer_robomaker_coach_gazebo/src/markov/metrics/s3_metrics.py (2 lines): - line 46: #! TODO this needs to be removed after muti part is fixed, note we don't have - line 453: # TODO: Service team can't handle "version" key in Evaluation Metrics due to reinforcement_learning/rl_deepracer_robomaker_coach_gazebo/src/markov/utils.py (2 lines): - line 181: # TODO: This code should be removed when the cloud service starts providing VIDEO_JOB_TYPE YAML parameter - line 249: # TODO: reinforcement_learning/rl_deepracer_robomaker_coach_gazebo/src/markov/evaluation_worker.py (2 lines): - line 65: MIN_RESET_COUNT = 10000 # TODO: change when console passes float("inf") - line 119: # TODO: Since we are not running Grand Prix in RoboMaker, reinforcement_learning/bandits_recsys_movielens_testbed/src/env.py (2 lines): - line 85: # TODO: Randomize user selection - line 121: # TODO: Implement PBM: Position based model reinforcement_learning/common/sagemaker_rl/coach_launcher.py (2 lines): - line 122: # TODO: remove this after converting all samples. - line 289: # TODO: Remove this whole class when nobody's using it any more. reinforcement_learning/rl_cartpole_coach/common/sagemaker_rl/coach_launcher.py (2 lines): - line 122: # TODO: remove this after converting all samples. - line 289: # TODO: Remove this whole class when nobody's using it any more. reinforcement_learning/rl_hvac_coach_energyplus/common/sagemaker_rl/coach_launcher.py (2 lines): - line 122: # TODO: remove this after converting all samples. - line 289: # TODO: Remove this whole class when nobody's using it any more. reinforcement_learning/rl_mountain_car_coach_gymEnv/common/sagemaker_rl/coach_launcher.py (2 lines): - line 122: # TODO: remove this after converting all samples. - line 289: # TODO: Remove this whole class when nobody's using it any more. reinforcement_learning/rl_stock_trading_coach_customEnv/common/sagemaker_rl/coach_launcher.py (2 lines): - line 122: # TODO: remove this after converting all samples. - line 289: # TODO: Remove this whole class when nobody's using it any more. reinforcement_learning/rl_traveling_salesman_vehicle_routing_coach/common/sagemaker_rl/coach_launcher.py (2 lines): - line 122: # TODO: remove this after converting all samples. - line 289: # TODO: Remove this whole class when nobody's using it any more. contrib/inference_pipeline_custom_containers/containers/postprocessor/docker/code/predictor.py (2 lines): - line 146: # TODO: use custom flag to indicate that this is in a pipeline rather than relying on the '*/*' - line 148: # TODO: this is wrong. fix it reinforcement_learning/rl_game_server_autopilot/sagemaker/common/sagemaker_rl/coach_launcher.py (2 lines): - line 122: # TODO: remove this after converting all samples. - line 289: # TODO: Remove this whole class when nobody's using it any more. reinforcement_learning/rl_predictive_autoscaling_coach_customEnv/common/sagemaker_rl/coach_launcher.py (2 lines): - line 122: # TODO: remove this after converting all samples. - line 289: # TODO: Remove this whole class when nobody's using it any more. reinforcement_learning/rl_network_compression_ray_custom/common/sagemaker_rl/coach_launcher.py (2 lines): - line 122: # TODO: remove this after converting all samples. - line 289: # TODO: Remove this whole class when nobody's using it any more. reinforcement_learning/rl_tic_tac_toe_coach_customEnv/common/sagemaker_rl/coach_launcher.py (2 lines): - line 122: # TODO: remove this after converting all samples. - line 287: # TODO: Remove this whole class when nobody's using it any more. reinforcement_learning/rl_deepracer_robomaker_coach_gazebo/src/markov/multi_agent_coach/multi_agent_graph_manager.py (2 lines): - line 76: self.num_checkpoints_to_keep = 4 # TODO: make this a parameter - line 626: # TODO: find better way to load checkpoints that were saved with a global network into the online network reinforcement_learning/rl_managed_spot_cartpole_coach/common/sagemaker_rl/coach_launcher.py (2 lines): - line 122: # TODO: remove this after converting all samples. - line 289: # TODO: Remove this whole class when nobody's using it any more. reinforcement_learning/rl_roboschool_ray/common/sagemaker_rl/coach_launcher.py (2 lines): - line 122: # TODO: remove this after converting all samples. - line 289: # TODO: Remove this whole class when nobody's using it any more. reinforcement_learning/rl_hvac_ray_energyplus/source/common/sagemaker_rl/coach_launcher.py (2 lines): - line 122: # TODO: remove this after converting all samples. - line 289: # TODO: Remove this whole class when nobody's using it any more. reinforcement_learning/bandits_statlog_vw_customEnv/common/sagemaker_rl/coach_launcher.py (2 lines): - line 122: # TODO: remove this after converting all samples. - line 289: # TODO: Remove this whole class when nobody's using it any more. reinforcement_learning/rl_roboschool_stable_baselines/common/sagemaker_rl/coach_launcher.py (2 lines): - line 122: # TODO: remove this after converting all samples. - line 289: # TODO: Remove this whole class when nobody's using it any more. reinforcement_learning/rl_resource_allocation_ray_customEnv/common/sagemaker_rl/coach_launcher.py (2 lines): - line 122: # TODO: remove this after converting all samples. - line 289: # TODO: Remove this whole class when nobody's using it any more. reinforcement_learning/rl_cartpole_batch_coach/common/sagemaker_rl/coach_launcher.py (2 lines): - line 122: # TODO: remove this after converting all samples. - line 289: # TODO: Remove this whole class when nobody's using it any more. reinforcement_learning/rl_deepracer_robomaker_coach_gazebo/common/sagemaker_rl/coach_launcher.py (2 lines): - line 122: # TODO: remove this after converting all samples. - line 289: # TODO: Remove this whole class when nobody's using it any more. reinforcement_learning/rl_unity_ray/common/sagemaker_rl/coach_launcher.py (2 lines): - line 122: # TODO: remove this after converting all samples. - line 289: # TODO: Remove this whole class when nobody's using it any more. reinforcement_learning/rl_deepracer_robomaker_coach_gazebo/src/markov/agent_ctrl/rollout_agent_ctrl.py (2 lines): - line 196: #! TODO evaluate if this is the best way to reset the car - line 759: # TODO: maybe clamping the value will provide a better customer experience. reinforcement_learning/rl_deepracer_robomaker_coach_gazebo/src/markov/cameras/frustum.py (2 lines): - line 26: # TODO: Hard coding the frustum values for now. These values need to be loaded from SDF directly - line 32: # TODO: Remove below camera_offsets and camera_pitch variables if we can get Camera pose directly reinforcement_learning/rl_knapsack_coach_custom/common/sagemaker_rl/coach_launcher.py (2 lines): - line 122: # TODO: remove this after converting all samples. - line 289: # TODO: Remove this whole class when nobody's using it any more. reinforcement_learning/rl_cartpole_ray/common/sagemaker_rl/coach_launcher.py (2 lines): - line 122: # TODO: remove this after converting all samples. - line 289: # TODO: Remove this whole class when nobody's using it any more. reinforcement_learning/rl_deepracer_robomaker_coach_gazebo/src/markov/multi_agent_coach/architectures/tensorflow_components/heads/sac_head.py (1 line): - line 62: # DH TODO: check shape of self.num_actions. It should be int reinforcement_learning/rl_cartpole_ray/common/sagemaker_rl/orchestrator/workflow/manager/experiment_manager.py (1 line): - line 1185: # TODO: add validation/instructions if multiple deployment reinforcement_learning/rl_game_server_autopilot/sagemaker/common/sagemaker_rl/orchestrator/workflow/manager/experiment_manager.py (1 line): - line 1185: # TODO: add validation/instructions if multiple deployment reinforcement_learning/bandits_statlog_vw_customEnv/common/sagemaker_rl/orchestrator/workflow/manager/experiment_manager.py (1 line): - line 1185: # TODO: add validation/instructions if multiple deployment reinforcement_learning/common/sagemaker_rl/orchestrator/workflow/manager/experiment_manager.py (1 line): - line 1185: # TODO: add validation/instructions if multiple deployment reinforcement_learning/rl_resource_allocation_ray_customEnv/common/sagemaker_rl/orchestrator/workflow/manager/experiment_manager.py (1 line): - line 1185: # TODO: add validation/instructions if multiple deployment reinforcement_learning/rl_stock_trading_coach_customEnv/common/sagemaker_rl/orchestrator/workflow/manager/experiment_manager.py (1 line): - line 1185: # TODO: add validation/instructions if multiple deployment reinforcement_learning/rl_deepracer_robomaker_coach_gazebo/common/sagemaker_rl/orchestrator/workflow/manager/experiment_manager.py (1 line): - line 1185: # TODO: add validation/instructions if multiple deployment reinforcement_learning/rl_traveling_salesman_vehicle_routing_coach/common/sagemaker_rl/orchestrator/workflow/manager/experiment_manager.py (1 line): - line 1185: # TODO: add validation/instructions if multiple deployment reinforcement_learning/rl_roboschool_stable_baselines/common/sagemaker_rl/orchestrator/workflow/manager/experiment_manager.py (1 line): - line 1185: # TODO: add validation/instructions if multiple deployment ground_truth_labeling_jobs/multi_modal_parallel_sagemaker_labeling_workflows_with_step_functions/src/lambda_src/api_batch_create/main.py (1 line): - line 98: # TODO: find more specific exception for resource not found reinforcement_learning/rl_cartpole_coach/common/sagemaker_rl/orchestrator/workflow/manager/experiment_manager.py (1 line): - line 1185: # TODO: add validation/instructions if multiple deployment reinforcement_learning/rl_predictive_autoscaling_coach_customEnv/common/sagemaker_rl/orchestrator/workflow/manager/experiment_manager.py (1 line): - line 1185: # TODO: add validation/instructions if multiple deployment end_to_end/music_recommendation/code/demo_helpers.py (1 line): - line 184: # TODO: flesh out docstrings end_to_end/fraud_detection/demo_helpers.py (1 line): - line 112: # TODO: flesh out docstrings reinforcement_learning/rl_hvac_coach_energyplus/common/sagemaker_rl/orchestrator/workflow/manager/experiment_manager.py (1 line): - line 1185: # TODO: add validation/instructions if multiple deployment reinforcement_learning/rl_deepracer_robomaker_coach_gazebo/src/markov/multi_agent_coach/multi_agent_environment.py (1 line): - line 79: ) # TODO: add a getter and setter training/distributed_training/pytorch/model_parallel/bert/bert_example/modeling.py (1 line): - line 1366: # TODO check with Google if it's normal there is no dropout on the token classifier of SQuAD in the TF version ground_truth_labeling_jobs/multi_modal_parallel_sagemaker_labeling_workflows_with_step_functions/src/lambda_src/api_workforce_show/main.py (1 line): - line 56: # TODO: Can add additional user attributes here. reinforcement_learning/rl_managed_spot_cartpole_coach/common/sagemaker_rl/orchestrator/workflow/manager/experiment_manager.py (1 line): - line 1185: # TODO: add validation/instructions if multiple deployment reinforcement_learning/rl_deepracer_robomaker_coach_gazebo/src/markov/virtual_event/constants.py (1 line): - line 108: # TODO: figure out what display name to use during wait contrib/inference_pipeline_custom_containers/containers/preprocessor/docker/code/predictor.py (1 line): - line 124: # TODO: use custom flag to indicate that this is in a pipeline rather than relying on the '*/*' reinforcement_learning/rl_deepracer_robomaker_coach_gazebo/src/markov/track_geom/constants.py (1 line): - line 63: # TODO: Fix the bot car dimension so that all collisions are detected reinforcement_learning/rl_mountain_car_coach_gymEnv/common/sagemaker_rl/orchestrator/workflow/manager/experiment_manager.py (1 line): - line 1185: # TODO: add validation/instructions if multiple deployment reinforcement_learning/rl_deepracer_robomaker_coach_gazebo/src/markov/track_geom/utils.py (1 line): - line 161: # TODO: Maybe implement some logic to make sure the park postion is always outside of the race track reinforcement_learning/rl_portfolio_management_coach_customEnv/common/sagemaker_rl/orchestrator/workflow/manager/experiment_manager.py (1 line): - line 1185: # TODO: add validation/instructions if multiple deployment reinforcement_learning/rl_network_compression_ray_custom/common/sagemaker_rl/orchestrator/workflow/manager/experiment_manager.py (1 line): - line 1185: # TODO: add validation/instructions if multiple deployment reinforcement_learning/rl_cartpole_batch_coach/common/sagemaker_rl/orchestrator/workflow/manager/experiment_manager.py (1 line): - line 1185: # TODO: add validation/instructions if multiple deployment reinforcement_learning/rl_roboschool_ray/common/sagemaker_rl/orchestrator/workflow/manager/experiment_manager.py (1 line): - line 1185: # TODO: add validation/instructions if multiple deployment reinforcement_learning/rl_deepracer_robomaker_coach_gazebo/src/markov/log_handler/deepracer_exceptions.py (1 line): - line 243: TODO: implemement logic here if we decide to log non fatal error metrics reinforcement_learning/rl_hvac_ray_energyplus/source/common/sagemaker_rl/orchestrator/workflow/manager/experiment_manager.py (1 line): - line 1185: # TODO: add validation/instructions if multiple deployment reinforcement_learning/rl_deepracer_robomaker_coach_gazebo/src/markov/s3_boto_data_store.py (1 line): - line 41: #! TODO remove ignore_lock after refactoring this class reinforcement_learning/rl_hvac_ray_energyplus/source/ray_experiment_builder.py (1 line): - line 61: # TODO import method from starter-kit ground_truth_labeling_jobs/multi_modal_parallel_sagemaker_labeling_workflows_with_step_functions/src/lambda_src/step_functions_send_second_level_sns_and_check_response/main.py (1 line): - line 16: # TODO: Selection should be based on frames in DDB table ground_truth_labeling_jobs/multi_modal_parallel_sagemaker_labeling_workflows_with_step_functions/src/lambda_src/shared/db.py (1 line): - line 563: # TODO: Replace with get_item reinforcement_learning/rl_unity_ray/common/sagemaker_rl/orchestrator/workflow/manager/experiment_manager.py (1 line): - line 1185: # TODO: add validation/instructions if multiple deployment reinforcement_learning/rl_knapsack_coach_custom/common/sagemaker_rl/orchestrator/workflow/manager/experiment_manager.py (1 line): - line 1185: # TODO: add validation/instructions if multiple deployment reinforcement_learning/bandits_statlog_vw_customEnv/src/vw_model.py (1 line): - line 156: # TODO: Error handling in parsing the given example reinforcement_learning/rl_deepracer_robomaker_coach_gazebo/src/markov/sagemaker_graph_manager.py (1 line): - line 194: # % TODO - refactor this module to be more modular based on the training algorithm and avoid if-else training/distributed_training/pytorch/data_parallel/maskrcnn/train_pytorch_smdataparallel_maskrcnn.py (1 line): - line 198: torch.cuda.empty_cache() # TODO check if it helps reinforcement_learning/rl_deepracer_robomaker_coach_gazebo/src/markov/virtual_event/virtual_event_manager.py (1 line): - line 543: # TODO: It might be theorically possible to have different kms keys for simtrace and mp4