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feature: Add SageMaker Experiment (#3536)
* feature: Add experiment plus Run class (#691) * feature: Add Experiment helper classes (#646) * feature: Add Experiment helper classes feature: Add helper class _RunEnvironment * change: Change sleep retry to backoff retry for get TC * minor fixes in backoff retry Co-authored-by: Dewen Qi <qidewen@amazon.com> * feature: Add helper classes and methods for Run class (#660) * feature: Add helper classes and methods for Run class * Add Parent class to address comment * fix docstyle check * Add arg docstrings in _helper Co-authored-by: Dewen Qi <qidewen@amazon.com> * feature: Add Experiment Run class (#651) Co-authored-by: Dewen Qi <qidewen@amazon.com> * change: Add integ tests for Run (#673) Co-authored-by: Dewen Qi <qidewen@amazon.com> * Update run log metric to use MetricsManager (#678) * Update run.log_metric to use _MetricsManager * fix several metrics issues * Add doc strings to metrics.py Co-authored-by: Dana Benson <danabens@amazon.com> Co-authored-by: Dana Benson <31262102+danabens@users.noreply.github.com> Co-authored-by: Dewen Qi <qidewen@amazon.com> Co-authored-by: Dewen Qi <qidewen@amazon.com> Co-authored-by: Dana Benson <danabens@amazon.com> Co-authored-by: Dana Benson <31262102+danabens@users.noreply.github.com> * change: Simplify exp plus integ test configuration (#694) Co-authored-by: Dewen Qi <qidewen@amazon.com> * feature: add RunName to expeirment_config (#696) * change: Update Run init and add Run load and _RunContext (#707) * change: Update Run init and add Run load Add exp name and run group name to load and address comments * Address nit comments Co-authored-by: Dewen Qi <qidewen@amazon.com> * fix: Fix run name uniqueness issue (#730) Co-authored-by: Dewen Qi <qidewen@amazon.com> * change: Update integ tests for Exp Plus M1 changes (#741) Co-authored-by: Dewen Qi <qidewen@amazon.com> * add metrics client to session object (#745) Co-authored-by: Dewen Qi <qidewen@amazon.com> Co-authored-by: Dana Benson <danabens@amazon.com> Co-authored-by: Dana Benson <31262102+danabens@users.noreply.github.com> Co-authored-by: qidewenwhen <32910701+qidewenwhen@users.noreply.github.com> * change: Add integ test for using Run in Transform Job (#749) Co-authored-by: Dewen Qi <qidewen@amazon.com> * Add async metrics sink (#739) Co-authored-by: Dewen Qi <qidewen@amazon.com> Co-authored-by: Dana Benson <danabens@amazon.com> Co-authored-by: Dana Benson <31262102+danabens@users.noreply.github.com> Co-authored-by: qidewenwhen <32910701+qidewenwhen@users.noreply.github.com> * use metrics client provided by session (#754) * fix flaky metrics test (#753) * change: Change Run.init and Run.load to constructor and module method respectively (#752) Co-authored-by: Dewen Qi <qidewen@amazon.com> * feature: Add latest metric service model (#757) Co-authored-by: Dewen Qi <qidewen@amazon.com> Co-authored-by: qidewenwhen <32910701+qidewenwhen@users.noreply.github.com> * fix: lowercase run name (#767) * Change: Minimize use of lower case tc name (#769) * change: Clean up test resources to remove model files (#756) * change: Clean up test resources to remove model files * fix: Change experiment enums to upper case * change: Upgrade boto3 and update test to validate mixed case name * fix: Update as per latest botocore release and backend change Co-authored-by: Dewen Qi <qidewen@amazon.com> * lowercase trial component name (#776) * change: Expose sagemaker experiment doc strings * fix: Fix exp name mixed case in issue Co-authored-by: Dewen Qi <qidewen@amazon.com> Co-authored-by: Dana Benson <danabens@amazon.com> Co-authored-by: Dana Benson <31262102+danabens@users.noreply.github.com> Co-authored-by: Yifei Zhu <66866419+yzhu0@users.noreply.github.com>
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‎.gitignore‎

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.vscode/
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**/tmp
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.python-version
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**/_repack_model.py
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**/_repack_script_launcher.sh
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**/_repack_script_launcher.sh
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tests/data/**/_repack_model.py
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tests/data/experiment/sagemaker-dev-1.0.tar.gz

‎doc/experiments/index.rst‎

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############################
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Amazon SageMaker Experiments
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############################
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The SageMaker Python SDK supports to track and organize your machine learning workflow across SageMaker with jobs, such as Processing, Training and Transform, or locally.
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.. toctree::
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:maxdepth: 2
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sagemaker.experiments

‎doc/experiments/sagemaker.experiments.rst‎

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Experiments
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============
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Run
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-------------
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.. autoclass:: sagemaker.experiments.Run
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:members:
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.. automethod:: sagemaker.experiments.load_run
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.. automethod:: sagemaker.experiments.list_runs
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.. autoclass:: sagemaker.experiments.SortByType
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:members:
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:undoc-members:
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.. autoclass:: sagemaker.experiments.SortOrderType
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:members:
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:undoc-members:

‎doc/index.rst‎

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workflows/index
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****************************
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Amazon SageMaker Experiments
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****************************
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You can use Amazon SageMaker Experiments to track machine learning experiments.
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.. toctree::
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:maxdepth: 2
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experiments/index
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*************************
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Amazon SageMaker Debugger
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*************************

‎requirements/extras/test_requirements.txt‎

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sagemaker-experiments==0.1.35
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Jinja2==3.0.3
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pandas>=1.3.5,<1.5
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scikit-learn==1.0.2

‎setup.py‎

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# Declare minimal set for installation
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required_packages = [
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"attrs>=20.3.0,<23",
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"boto3>=1.26.20,<2.0",
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"boto3>=1.26.28,<2.0",
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"google-pasta",
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"numpy>=1.9.0,<2.0",
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"protobuf>=3.1,<4.0",

‎src/sagemaker/amazon/amazon_estimator.py‎

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from sagemaker.deprecations import renamed_warning
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from sagemaker.estimator import EstimatorBase, _TrainingJob
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from sagemaker.inputs import FileSystemInput, TrainingInput
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from sagemaker.utils import sagemaker_timestamp
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from sagemaker.utils import sagemaker_timestamp, check_and_get_run_experiment_config
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from sagemaker.workflow.entities import PipelineVariable
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from sagemaker.workflow.pipeline_context import runnable_by_pipeline
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from sagemaker.workflow import is_pipeline_variable
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generates a default job name, based on the training image name
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and current timestamp.
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experiment_config (dict[str, str]): Experiment management configuration.
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Optionally, the dict can contain three keys:
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'ExperimentName', 'TrialName', and 'TrialComponentDisplayName'.
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Optionally, the dict can contain four keys:
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'ExperimentName', 'TrialName', 'TrialComponentDisplayName' and 'RunName'.
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The behavior of setting these keys is as follows:
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* If `ExperimentName` is supplied but `TrialName` is not a Trial will be
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automatically created and the job's Trial Component associated with the Trial.
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"""
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self._prepare_for_training(records, job_name=job_name, mini_batch_size=mini_batch_size)
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experiment_config = check_and_get_run_experiment_config(experiment_config)
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self.latest_training_job = _TrainingJob.start_new(
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self, records, experiment_config=experiment_config
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)

‎src/sagemaker/apiutils/_base_types.py‎

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search_items = search_method_response.get("Results", [])
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next_token = search_method_response.get(boto_next_token_name)
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for item in search_items:
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if cls.__name__ in item:
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yield search_item_factory(item[cls.__name__])
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# _TrialComponent class in experiments module is not public currently
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class_name = cls.__name__.lstrip("_")
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if class_name in item:
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yield search_item_factory(item[class_name])
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if not next_token:
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break
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except StopIteration:

‎src/sagemaker/apiutils/_boto_functions.py‎

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api_type, is_collection = member_name_to_type[member_name]
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if is_collection:
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if isinstance(boto_value, dict):
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member_value = api_type.from_boto(boto_value)
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member_value = {
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key: api_type.from_boto(value) for key, value in boto_value.items()
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}
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else:
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member_value = [api_type.from_boto(item) for item in boto_value]
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else:

‎src/sagemaker/dataset_definition/inputs.py‎

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"""DatasetDefinition input."""
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_custom_boto_types = {
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"redshift_dataset_definition": (RedshiftDatasetDefinition, True),
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"athena_dataset_definition": (AthenaDatasetDefinition, True),
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# RedshiftDatasetDefinition and AthenaDatasetDefinition are not collection
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# Instead they are singleton objects. Thus, set the is_collection flag to False.
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"redshift_dataset_definition": (RedshiftDatasetDefinition, False),
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"athena_dataset_definition": (AthenaDatasetDefinition, False),
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}
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def __init__(

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