assets/batch_score/components/driver/src/batch_score/common/configuration/command_line_argument_specification.py (5 lines):
	- line 10: # TODO: Name this ARGUMENT_SPECIFICATION
	- line 12: # TODO: headers with booleans fail during session.post.
	- line 169: # TODO: add validation to ensure that this parameter is not empty when save_mini_batch_results is enabled.
	- line 182: # TODO: add the choices 'append_row' and 'summary_only'.
	- line 223: # TODO: convert this to a boolean


assets/batch_score_oss/components/driver/src/batch_score_oss/common/configuration/command_line_argument_specification.py (5 lines):
	- line 9: # TODO: Name this ARGUMENT_SPECIFICATION
	- line 11: # TODO: headers with booleans fail during session.post.
	- line 157: # TODO: add validation to ensure that this parameter is not empty when save_mini_batch_results is enabled.
	- line 170: # TODO: add the choices 'append_row' and 'summary_only'.
	- line 198: # TODO: convert this to a boolean


assets/model_monitoring/components/src/model_data_collector_preprocessor/run.py (4 lines):
	- line 145: # TODO: Evaluate if we need to overwrite
	- line 208: # TODO: Move this to tracking stream if both data and dataref are NULL
	- line 216: data_rows = df.select(data_columns).rdd.take(SCHEMA_INFER_ROW_COUNT)  # TODO: make it an argument user can define
	- line 259: # TODO: if neither data and dataref move to tracking stream (or throw ModelMonitoringException?)


assets/training/model_evaluation/src/utils.py (4 lines):
	- line 253: # TODO: check if we need to look in different keys for precision, recall and f1
	- line 297: #     # TODO: Add checks for logging longer lists
	- line 893: # TODO support batched=True and handle processing multiple examples in lambda
	- line 992: # TODO: Fix this post PrP


assets/training/finetune_acft_hf_nlp/src/model_selector/model_selector.py (4 lines):
	- line 41: # TODO - Move REFINED_WEB to :dataclass HfModelTypes
	- line 46: # TODO Move this constants class to package
	- line 77: TODO Move this function to run utils
	- line 203: # TODO Revist whether `model_id` is still relevant


assets/model_monitoring/components/src/model_data_collector_preprocessor/mdc_preprocessor_helper.py (3 lines):
	- line 208: # TODO raise validation error if the SP has no permission to generate user delegation key
	- line 315: # TODO fallback to spark conf "spark.hadoop.fs.azure.sas.my_container.my_account.blob.core.windows.net"
	- line 335: # TODO support credential pass through for credential less data


assets/model_monitoring/components/src/shared_utilities/histogram_utils.py (3 lines):
	- line 16: # TODO: Unnecessary calculation, use count from summary and remove _get_smaller_df()
	- line 33: # TODO: profile agg if required
	- line 75: # TODO: profile rdd.histogram


assets/batch_score/components/driver/src/batch_score/common/parallel/worker.py (2 lines):
	- line 150: # TODO: consider adjusting back-off.
	- line 355: # TODO: Clean up this log line


assets/training/finetune_acft_hf_nlp/src/register_model/register_presets_model.py (2 lines):
	- line 102: # TODO: This relies on the v1 SDK. Handling will need to be adapted to shift to v2
	- line 320: # TODO auto construct relative path instead of hard-coding it


assets/training/finetune_acft_image/src/model_output_selector/model_output_selector.py (2 lines):
	- line 9: TODO: Replace with control flow https://msdata.visualstudio.com/Vienna/_workitems/edit/2306663.
	- line 123: # conditional_output. TODO: Task 2306663 (https://msdata.visualstudio.com/Vienna/_workitems/edit/2306663)


assets/model_monitoring/components/src/data_drift_compute_metrics/numerical_data_drift_metrics.py (2 lines):
	- line 96: # TODO: Update to leverage SynapeML library again once the logarithmic base issue in entropy is fixed.
	- line 153: # TODO: Update to leverage DistributionBalanceMeasure again after reference distribution is supported in SynapeML.


assets/batch_score_oss/components/driver/src/batch_score_oss/common/telemetry/events/batch_score_event.py (2 lines):
	- line 15: # TODO: Add comments to describe each field
	- line 69: # TODO: How to get values for 'execution_mode', 'process_id' and 'node_id'?


assets/model_monitoring/components/src/model_data_collector_preprocessor/genai_preprocessor_df_schemas.py (2 lines):
	- line 11: # TODO: The user_id and session_id may not be available in v1.
	- line 33: # TODO: The user_id and session_id may not be available in v0 of trace aggregator.


assets/batch_score/components/driver/src/batch_score/common/telemetry/events/batch_score_event.py (2 lines):
	- line 15: # TODO: Add comments to describe each field
	- line 68: # TODO: How to get values for 'execution_mode', 'process_id' and 'node_id'?


assets/model_monitoring/components/src/model_data_collector_preprocessor/mdc_utils.py (2 lines):
	- line 77: # TODO need full schema override
	- line 93: # TODO separate df into 2 parts, one with dataref, one without, then only handle the one with dataref, and


assets/training/model_management/environments/mlflow-model-inference/context/mlflow_score_script.py (2 lines):
	- line 348: # TODO check with OSS about pd.Series
	- line 362: # TODO keeping this around while _infer_schema doesn't work on dataframe string signatures


assets/inference/environments/mlflow-py312-inference/context/mlflow_score_script.py (2 lines):
	- line 348: # TODO check with OSS about pd.Series
	- line 362: # TODO keeping this around while _infer_schema doesn't work on dataframe string signatures


assets/model_monitoring/components/src/generation_safety_quality/annotation_compute_histogram/run.py (2 lines):
	- line 240: # TODO add validation for threshold args!!
	- line 309: # TODO support multiple returned annotations


assets/training/model_management/src/azureml/model/mgmt/processors/transformers/vision/predict.py (2 lines):
	- line 93: # TODO: use in-memory dataset throughout the code (eg instead of list of images).
	- line 95: # TODO: change image height and width based on kwargs.


assets/batch_score_oss/components/driver/src/batch_score_oss/common/parallel/worker.py (2 lines):
	- line 147: # TODO: consider adjusting back-off.
	- line 349: # TODO: Clean up this log line


assets/model_monitoring/components/src/shared_utilities/io_utils.py (2 lines):
	- line 117: # TODO: remove this check block after we are able to support submitting managed identity MoMo graphs.
	- line 178: # TODO add link to doc


scripts/azureml-assets/azureml/assets/publish_utils.py (2 lines):
	- line 259: # TODO: Use a more direct approach like this, when supported by Azure CLI:
	- line 269: # TODO: Add fetching env from other labels


assets/training/finetune_acft_hf_nlp/components_v2/pipeline_components/text_generation/spec.yaml (1 line):
	- line 38: # TODO remove text key if the format is made similar to openai


assets/batch_score_oss/components/driver/src/batch_score_oss/common/scoring/scoring_utils.py (1 line):
	- line 55: # TODO: Remove 403 from retriable statuses.


assets/training/finetune_acft_multimodal/src/model_import/model_import.py (1 line):
	- line 88: # TODO Revist whether `model_id` is still relevant


assets/training/model_management/src/azureml/model/mgmt/utils/logging_utils.py (1 line):
	- line 97: # TODO: Use V2 way of determining this.


assets/batch_score_oss/components/driver/src/batch_score_oss/common/telemetry/events/batch_score_init_completed_event.py (1 line):
	- line 10: # TODO: Add comments to describe each field


assets/training/model_management/environments/mlflow-model-inference/context/mlmonitoring/worker/sender.py (1 line):
	- line 94: # TODO: split payload if it is large?


assets/training/finetune_acft_hf_nlp/src/finetune/finetune.py (1 line):
	- line 61: # TODO - Move REFINED_WEB to :dataclass HfModelTypes


assets/aml-benchmark/components/src/aml_benchmark/batch_benchmark_score/batch_score/parallel/worker.py (1 line):
	- line 134: # TODO: consider adjusting back-off.


assets/batch_score/components/driver/src/batch_score/common/configuration/configuration_parser.py (1 line):
	- line 36: # TODO: Override all parameter values specified in the file


assets/inference/environments/mlflow-py312-inference/context/mlmonitoring/worker/sender.py (1 line):
	- line 94: # TODO: split payload if it is large?


assets/model_monitoring/components/src/model_data_collector_preprocessor/spark_run.py (1 line):
	- line 34: # TODO remove this step after we switch our interface from mltable to uri_folder


assets/responsibleai/tabular/components/src/rai_component_utilities.py (1 line):
	- line 25: # TODO: seems this method needs to be made public


assets/batch_score_oss/components/driver/src/batch_score_oss/common/telemetry/events/batch_score_request_completed_event.py (1 line):
	- line 12: # TODO: Add comments to describe each field


assets/training/model_management/src/azureml/model/mgmt/processors/transformers/config.py (1 line):
	- line 32: # TODO: check if this exists in evaluate-mlflow package


assets/common/src/utils/run_utils.py (1 line):
	- line 99: # TODO: Use V2 way of determining this.


scripts/azureml-assets/azureml/assets/validate_assets.py (1 line):
	- line 854: # TODO: skip hidden layer valdn till most models are scanned


assets/batch_score_oss/components/driver/src/batch_score_oss/common/telemetry/events/batch_score_input_row_completed_event.py (1 line):
	- line 12: # TODO: Add comments to describe each field


assets/training/model_management/src/azureml/model/mgmt/downloader/downloader.py (1 line):
	- line 77: # TODO: Handle error case correctly, since azcopy exits with 0 exit code, even in case of error.


assets/training/model_evaluation/components/distributed_model_prediction/spec.yaml (1 line):
	- line 64: type: uri_file  # TODO: Not implemented yet in this component


assets/aml-benchmark/components/src/aml_benchmark/utils/logging.py (1 line):
	- line 86: # TODO: Update the logic later. Right now, prevent logging error message


assets/model_monitoring/components/src/data_drift_compute_metrics/compute_data_drift.py (1 line):
	- line 75: # TODO: fix this if, else


assets/training/model_evaluation/src/task_factory/image/image_uploader.py (1 line):
	- line 5: # TODO: refactor to use the same image uploading code in the Dataset Downloader and the Compute Metrics components.


assets/model_monitoring/components/tools/spec_version_upgrader.py (1 line):
	- line 170: # TODO add --all to upgrade all components


assets/training/model_evaluation/src_distributed/download_extra_dependency.py (1 line):
	- line 34: # TODO: See if there are any packages that should be updated


assets/batch_score/components/driver/src/batch_score/utils/v2_output_formatter.py (1 line):
	- line 90: "id": "",  # TODO: populate this ID


assets/batch_score/components/driver/src/batch_score/common/telemetry/events/batch_score_input_row_completed_event.py (1 line):
	- line 12: # TODO: Add comments to describe each field


assets/batch_score/components/driver/src/batch_score/__init__.py (1 line):
	- line 13: # TODO: remove this hack after dedicated environment is published.


assets/batch_score_oss/components/driver/src/batch_score_oss/common/telemetry/events/event_utils.py (1 line):
	- line 20: # TODO: Investigate if this can be common_context_vars that is not restricted for use in events.


assets/training/finetune_acft_hf_nlp/src/model_selector/finetune_config.py (1 line):
	- line 21: # TODO - Move REFINED_WEB to :dataclass HfModelTypes


assets/training/model_evaluation/src_distributed/prepare_data.py (1 line):
	- line 138: # TODO support batched=True and handle processing multiple examples in lambda


assets/batch_score/components/driver/src/batch_score/common/telemetry/events/batch_score_minibatch_completed_event.py (1 line):
	- line 10: # TODO: Add comments to describe each field


assets/training/model_evaluation/src/task_factory/image/generation.py (1 line):
	- line 29: # TODO: use model parameter to get the output image field.


assets/batch_score_oss/components/driver/src/batch_score_oss/common/telemetry/events/batch_score_request_started_event.py (1 line):
	- line 10: # TODO: Add comments to describe each field


assets/model_monitoring/components/src/shared_utilities/store_url.py (1 line):
	- line 142: # TODO: remove after we figure out cache failure issues.


assets/model_monitoring/components/src/data_drift_compute_metrics/io_utils.py (1 line):
	- line 38: # TODO: log metrics to mlflow


assets/model_monitoring/components/src/model_data_collector_preprocessor/trace_aggregator.py (1 line):
	- line 108: # TODO: Prompt flow team doesn't guarantee that all spans will have request_id due to a backlog of work.


assets/model_monitoring/components/src/shared_utilities/constants.py (1 line):
	- line 197: # TODO: add link to documentation once available


assets/batch_score/components/driver/src/batch_score/common/telemetry/events/batch_score_request_started_event.py (1 line):
	- line 10: # TODO: Add comments to describe each field


assets/batch_score/components/driver/src/batch_score/common/telemetry/events/event_utils.py (1 line):
	- line 20: # TODO: Investigate if this can be common_context_vars that is not restricted for use in events.


assets/training/finetune_acft_image/src/framework_selector/framework_selector.py (1 line):
	- line 9: TODO: Framework selectors to use "switch" control flow once its supported by pipeline team.


assets/training/model_evaluation/src/evaluators/evaluators.py (1 line):
	- line 25: # TODO: Import ForecastColumns from azureml.evaluate.mlflow, when it will be


assets/batch_score_oss/components/driver/src/batch_score_oss/common/telemetry/events/batch_score_worker_increased_event.py (1 line):
	- line 10: # TODO: Add comments to describe each field


assets/large_language_models/rag/components/src/flow_creation.py (1 line):
	- line 518: # TODO: add actual implementation to create a PF flow from a json payload from previous step


assets/batch_score_oss/components/driver/src/batch_score_oss/common/parallel/congestion.py (1 line):
	- line 73: # TODO: https://dev.azure.com/msdata/Vienna/_workitems/edit/2832428


assets/training/model_evaluation/src_distributed/data_utils.py (1 line):
	- line 254: # TODO: Fix this post PrP


assets/model_monitoring/components/src/data_drift_compute_metrics/categorical_data_drift_metrics.py (1 line):
	- line 57: # TODO: Update to leverage SynapeML library again once the logarithmic base issue in entropy is fixed.


assets/model_monitoring/components/src/model_monitor_feature_selector/run.py (1 line):
	- line 63: # TODO: For now we raise InvalidInputError since it is categorized as UserError for momo SLA.


assets/training/model_evaluation/src/task_factory/tabular/forecast.py (1 line):
	- line 6: # TODO: Add Forecast predictor


assets/batch_score/components/driver/src/batch_score/common/telemetry/events/batch_score_minibatch_endpoint_health_event.py (1 line):
	- line 10: # TODO: Add comments to describe each field


assets/batch_score/components/driver/src/batch_score/common/telemetry/events/batch_score_worker_increased_event.py (1 line):
	- line 10: # TODO: Add comments to describe each field


assets/batch_score_oss/components/driver/src/batch_score_oss/common/configuration/configuration_parser.py (1 line):
	- line 36: # TODO: Override all parameter values specified in the file


assets/batch_score_oss/components/driver/src/batch_score_oss/common/telemetry/events/batch_score_minibatch_completed_event.py (1 line):
	- line 10: # TODO: Add comments to describe each field


assets/model_monitoring/components/src/model_data_collector_preprocessor/genai_run.py (1 line):
	- line 91: # TODO: as of right now UX does not want us to remove the promoted fields.


assets/model_monitoring/components/src/model_monitor_create_manifest/run.py (1 line):
	- line 30: # TODO: investigate why these aren't initialized by AzureML Filesystem itself


assets/batch_score/components/driver/src/batch_score/common/telemetry/events/batch_score_init_completed_event.py (1 line):
	- line 10: # TODO: Add comments to describe each field


assets/batch_score/components/driver/src/batch_score/batch_pool/quota/quota_client.py (1 line):
	- line 307: # TODO: Eventify this trace


assets/batch_score_oss/components/driver/src/batch_score_oss/utils/v2_output_formatter.py (1 line):
	- line 94: "id": "",  # TODO: populate this ID


assets/training/model_evaluation/src_distributed/model_prediction.py (1 line):
	- line 310: # TODO: Add logic for selecting MII Over VLLM using model size


assets/batch_score/components/driver/src/batch_score/common/parallel/congestion.py (1 line):
	- line 73: # TODO: https://dev.azure.com/msdata/Vienna/_workitems/edit/2832428


assets/batch_score_oss/components/driver/src/batch_score_oss/common/telemetry/events/batch_score_minibatch_endpoint_health_event.py (1 line):
	- line 10: # TODO: Add comments to describe each field


assets/batch_score_oss/components/driver/src/batch_score_oss/common/telemetry/events/batch_score_worker_decreased_event.py (1 line):
	- line 10: # TODO: Add comments to describe each field


assets/batch_score/components/driver/src/batch_score/common/telemetry/events/batch_score_request_completed_event.py (1 line):
	- line 12: # TODO: Add comments to describe each field


assets/batch_score/components/driver/src/batch_score/common/scoring/scoring_utils.py (1 line):
	- line 55: # TODO: Remove 403 from retriable statuses.


assets/batch_score/components/driver/src/batch_score/common/telemetry/events/batch_score_worker_decreased_event.py (1 line):
	- line 10: # TODO: Add comments to describe each field


assets/training/finetune_acft_image/src/finetune/finetune.py (1 line):
	- line 1112: # TODO: overwriting the save_as_mlflow_model flag to True. Otherwise, it will fail the pipeline service since it