src/sagemaker/serve/builder/model_builder.py (8 lines):
	- line 376: # TODO: use framework built-in method to save and load the model for all frameworks
	- line 407: # TODO: this won't work for larger image.
	- line 440: # TODO: move mode specific prepare steps under _model_builder_deploy_wrapper
	- line 534: # TODO: we should create model as per the framework
	- line 959: # TODO: add validation on MLmodel file
	- line 1447: # TODO: support native MLflow URIs
	- line 1673: # TODO: ideally these dictionaries need to be sagemaker_core shapes
	- line 1674: # TODO: for organization, abstract all validation behind this fn


src/sagemaker/workflow/steps.py (3 lines):
	- line 173: # TODO: move this method to CompiledStep
	- line 219: # TODO: we can remove the if-elif once move the validators to JsonGet constructor
	- line 236: # TODO: move it to JsonGet constructor


src/sagemaker/serve/save_retrive/version_1_0_0/save/utils.py (3 lines):
	- line 115: # TODO: We may need to use framework specific way to get the model size
	- line 122: # TODO: get input shape if pytorch
	- line 142: # TODO: performing integrity check is


src/sagemaker/remote_function/job.py (3 lines):
	- line 588: # TODO: update the feature store SDK to set the HMAC key there.
	- line 998: # TODO: remove the duplicates in the list
	- line 1418: # TODO Remove the following hack to avoid dir_exists error in the copy_tree call below.


src/sagemaker/serve/utils/predictors.py (3 lines):
	- line 25: # TODO: change mode_obj to union of IN_PROCESS and LOCAL_CONTAINER objs
	- line 261: # TODO: change mode_obj to union of IN_PROCESS and LOCAL_CONTAINER objs
	- line 380: # TODO: extend to LOCAL_CONTAINER mode


src/sagemaker/serve/model_format/mlflow/utils.py (2 lines):
	- line 76: # TODO: Dynamically getting fw version after beta
	- line 307: # TODO: Extend this for model server specific DLC as well, ie. DJL, Triton


src/sagemaker/workflow/pipeline.py (2 lines):
	- line 694: pipeline_name: str,  # TODO: remove it once its ExecutionVariable fixed in backend
	- line 908: # TODO: this waiter should be included in the botocore


src/sagemaker/serve/builder/transformers_builder.py (2 lines):
	- line 302: # TODO: Move to a helper function
	- line 367: # TODO: this won't work for larger image.


src/sagemaker/experiments/run.py (2 lines):
	- line 170: # TODO: we should revert the lower casting once backend fix reaches prod
	- line 685: # TODO: we should revert the lower casting once backend fix reaches prod


src/sagemaker/modules/train/model_trainer.py (2 lines):
	- line 397: # TODO: Move to use pydantic model validators
	- line 526: # TODO: Autodetect which image to use if source_code is provided


src/sagemaker/serve/model_server/torchserve/inference.py (2 lines):
	- line 39: # TODO: Add warning if it's pyfunc flavor since it will need to enforce schema
	- line 154: # TODO: move this to constants section


src/sagemaker/feature_store/feature_processor/feature_scheduler.py (2 lines):
	- line 959: # TODO: Remove this after GA
	- line 962: # TODO: This needs to be removed when new mode is introduced.


src/sagemaker/model.py (2 lines):
	- line 661: # TODO: we should replace _create_sagemaker_model() with create()
	- line 1679: live_logging=False,  # TODO: enable when IC supports this


src/sagemaker/serve/model_server/triton/server.py (2 lines):
	- line 22: # TODO: automatically update memory size
	- line 95: # TODO: set datatype from payload


src/sagemaker/spark/processing.py (2 lines):
	- line 621: # TODO (guoqioa@): method only checks urlparse scheme, need to perform deep s3 validation
	- line 1362: # TODO (guoqioa@): method only checks urlparse scheme, need to perform deep s3 validation


src/sagemaker/remote_function/core/serialization.py (1 line):
	- line 153: # TODO: use dask serializer in case dask distributed is installed in users' environment.


src/sagemaker/cli/compatibility/v2/modifiers/framework_version.py (1 line):
	- line 41: # TODO: check for sagemaker.tensorflow.serving.Model


src/sagemaker/workflow/conditions.py (1 line):
	- line 40: # TODO: consider base class for those with an expr method, rather than defining a type here


src/sagemaker/serve/model_server/triton/model.py (1 line):
	- line 37: # TODO: HMAC signing for integrity check


src/sagemaker/feature_store/dataset_builder.py (1 line):
	- line 468: # TODO: cleanup temp table, need more clarification, keep it for now


src/sagemaker/workflow/__init__.py (1 line):
	- line 31: # TODO: We should deprecate the Expression and replace it with PipelineVariable


src/sagemaker/huggingface/model.py (1 line):
	- line 198: # TODO: Remove the following function


src/sagemaker/feature_store/feature_processor/_input_loader.py (1 line):
	- line 199: # TODO: Accept `schema` parameter. (Inferring schema requires a pass through every row)


src/sagemaker/modules/configs.py (1 line):
	- line 29: # TODO: Can we add custom logic to some of these to set better defaults?


src/sagemaker/model_life_cycle.py (1 line):
	- line 32: # TODO: flesh out docstrings


src/sagemaker/metadata_properties.py (1 line):
	- line 33: # TODO: flesh out docstrings


src/sagemaker/workflow/function_step.py (1 line):
	- line 555: # TODO: Move _validate_submit_args function out of RemoteExecutor class


src/sagemaker/utilities/search_expression.py (1 line):
	- line 21: # TODO: we should update the lineage to use search expressions


src/sagemaker/local/entities.py (1 line):
	- line 294: # TODO - support SageMaker Models not just local models. This is not


src/sagemaker/serve/utils/optimize_utils.py (1 line):
	- line 57: # TODO: Use specific container type instead.


src/sagemaker/rl/estimator.py (1 line):
	- line 346: # TODO: can be applied to all other estimators


src/sagemaker/utils.py (1 line):
	- line 1589: # TODO: The function and it's usages can be deprecated once SageMaker Python SDK


doc/doc_utils/jumpstart_doc_utils.py (1 line):
	- line 240: proprietary_content_entries.append("     - {}\n".format(False))  # TODO: support training


src/sagemaker/serve/model_server/triton/triton_builder.py (1 line):
	- line 368: # TODO: migrate to image_uris.retrieve() once it starts to support Triton


src/sagemaker/feature_store/feature_processor/_validation.py (1 line):
	- line 74: # TODO: Validate target_stores values.


src/sagemaker/workflow/step_outputs.py (1 line):
	- line 49: # TODO: Implement this


src/sagemaker/experiments/_environment.py (1 line):
	- line 84: # TODO: need to update to get source_arn from config file once Transform side ready


src/sagemaker/serve/builder/jumpstart_builder.py (1 line):
	- line 576: # TODO: determine precedence of FINE_TUNING_MODEL_PATH and FINE_TUNING_JOB_NAME


src/sagemaker/workflow/_repack_model.py (1 line):
	- line 107: # TODO: The function and it's usages can be deprecated once SageMaker Python SDK


src/sagemaker/serve/detector/dependency_manager.py (1 line):
	- line 27: # TODO : Move PKL_FILE_NAME to common location


src/sagemaker/inference_recommender/inference_recommender_mixin.py (1 line):
	- line 611: # TODO: until we have bandwidth to integrate right_size + deploy with serverless


src/sagemaker/experiments/_metrics.py (1 line):
	- line 330: # TODO should probably use join


src/sagemaker/serve/model_server/torchserve/xgboost_inference.py (1 line):
	- line 167: # TODO: move this to constants section