sagemaker-python-sdk
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aws
A library for training and deploying machine learning models on Amazon SageMaker
*Issue #, if available:* *Description of changes:* Implemeted the fail_on_violation for the transform_with_monitoring step for sagemaker.transformer *Testing done:* ## Merge Checklist _Put an `x` in the boxes that apply. You...
**What did you find confusing? Please describe.** I try to understand which SageMaker SDK parameter would cause my SageMaker Pipeline step to re-run, this [documentation](https://sagemaker.readthedocs.io/en/stable/amazon_sagemaker_model_building_pipeline.html#caching-configuration) only gives an example of...
*Issue #, if available:* *Description of changes:* 1. Starting Triton version 23.12, sagemaker tritonserver is available in a different set of accounts, similar to other model servers such as djl-serving,...
Request for Enabling `include_local_workdir` Parameter Setting with `@step` Decorator in Local Mode
Describe the feature you'd like I would like to request the addition of a parameter for setting `include_local_workdir` when using the `@step` decorator in pipeline's local mode. Currently, there is...
Hi, I'm trying to implement a pipeline with @step decorator. So I was following descriptions on this side: https://docs.aws.amazon.com/sagemaker/latest/dg/pipelines-step-decorator-create-pipeline.html Paragraph: Define custom dependencies Code Line: get_step(step_train_result).add_depends_on(step_process_result) Problem: Function 'add_depends_on' needs...
**Describe the bug** Probably this is not a Bug, but when I try to deploy the Sagemaker Pytorch model, I am getting a `FileNotFoundError: [Errno 2] No such file or...
*Issue #, if available:* Fix for - https://github.com/aws/sagemaker-python-sdk/issues/4431 *Description of changes:* - Add `data_analysis_start_time` and `data_analysis_end_time` in ModelExplainabilityMonitor's _create_monitoring_schedule_from_job_definition - Add unit test code `test_model_explainability_monitor_with_one_time_schedule` and `_test_model_explainability_monitor_create_one_time_schedule` to test ModelExplainabilityMonitor's...
**Describe the bug** SageMaker Model Monitor provides one-time monitoring job schedule[[Link]](https://aws.amazon.com/about-aws/whats-new/2023/09/amazon-sagemaker-model-monitor-one-time-monitoring-jobs/). However, `ValueError` are raised when specifying `CronExpressionGenerator.now()`. **To reproduce** Using [SageMaker-Monitoring-Feature-Attribution-Drift-for-Endpoint.ipynb](https://github.com/aws/amazon-sagemaker-examples/blob/main/sagemaker_model_monitor/fairness_and_explainability_jsonlines/SageMaker-Monitoring-Feature-Attribution-Drift-for-Endpoint.ipynb): - Change `schedule_expression` to `CronExpressionGenerator.now()` - Specify `data_analysis_start_time`...
*Description of changes:* when running sagemaker in `local_gpu` mode it does not find the GPUs. The following config: ```yaml deploy: resources: reservations: devices: - capabilities: [gpu] ``` This will result...
**Describe the bug** Can't get list of training jobs using NameContains argument using `list_training_jobs` function. It returns training jobs without this argument properly. **To reproduce** ```python import boto3 import sagemaker...
