sagemaker-python-sdk
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aws
A library for training and deploying machine learning models on Amazon SageMaker
**Describe the bug** Exception during rule evaluation: Customer Error: No debugging data was saved by the training job. Check that the debugger hook was configured correctly before starting the training...
Reference: 0420645671 Please fill out the form below. ### System Information - **Framework (e.g. TensorFlow) / Algorithm (e.g. KMeans)**: XGBoost - **Framework Version**: 0.90 - **Python Version**: 3 - **CPU...
**Describe the bug** RepackModel steps in pipeline execution fails when built and upsert from Windows Environment. **To reproduce** - Start from a sagemaker [tutorial training pipeline](https://sagemaker-examples.readthedocs.io/en/latest/sagemaker-pipelines/tabular/abalone_build_train_deploy/sagemaker-pipelines-preprocess-train-evaluate-batch-transform.html) - Modify the Model...
**Describe the bug** Error is ``` botocore.exceptions.ClientError: An error occurred (ValidationException) when calling the CreateTrainingJob operation: Invalid training image. Please provide a valid Amazon Elastic Container Registry path of the...
**Describe the bug** Trained model artifacts are not downloaded from S3 during deploy on Windows 10. **To reproduce** Demonstrated on example from https://github.com/awslabs/amazon-sagemaker-examples/blob/master/sagemaker-python-sdk/tensorflow_script_mode_training_and_serving/tensorflow_script_mode_training_and_serving.ipynb ``` import sagemaker from sagemaker import get_execution_role...
**Describe the bug** [`DeserializerWrapper`](https://github.com/aws/sagemaker-python-sdk/blob/master/src/sagemaker/serve/builder/schema_builder.py#L81) overwrites the `content_type` provided to `deserialize()` to be the value of `Accept`. This `DeserializerWrapper` is used for both Input and Output de-serialization when using [`SchemaBuilder`](https://github.com/aws/sagemaker-python-sdk/blob/master/src/sagemaker/serve/builder/schema_builder.py#L134). The...
**Describe the bug** Hello, I think I encountered a bug in sagemaker.local. I'm trying to test a batch transform with images as input, but I get the following error even...
I am making an endpoint with this images on AWS sagemaker 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference:2.5.1-gpu-py311-cu124-ubuntu22.04-sagemaker I am trying to use SAM2 model by Meta the numpy version seems to be correct : Requirement...
*Issue #, if available:* *Description of changes:* By submitting this pull request, I confirm that you can use, modify, copy, and redistribute this contribution, under the terms of your choice.
*Issue #, if available:* *Description of changes:* This PR adds a new version of xgboost 3.0-5 By submitting this pull request, I confirm that you can use, modify, copy, and...