Comments (6)
+1. Specifically, i'm having this issue with SageMaker SDK 2.5.5 and StepFunctions 1.1.1:
AttributeError Traceback (most recent call last)
<ipython-input-32-8cdc141c8efb> in <module>
12 client=sfn,
13 deploy_instance_count=deploy_instance_count,
---> 14 deploy_instance_type=deploy_instance_type,
15 )
<ipython-input-31-298b58046d07> in __init__(self, processor, raw_input_data_s3_uri, train_split_percentage, validation_split_percentage, test_split_percentage, max_seq_length, balance_dataset, estimator, role, bucket, client, deploy_instance_count, deploy_instance_type, **kwargs)
85 self.pipeline_name = 'training-pipeline-{date}'.format(date=self._generate_timestamp())
86
---> 87 self.definition = self.build_workflow_definition()
88 self.input_template = self._extract_input_template(self.definition)
89
<ipython-input-31-298b58046d07> in build_workflow_definition(self)
177 instance_type=deploy_instance_type,
178 model=model,
--> 179 model_name=self.pipeline_name
180 )
181
~/anaconda3/envs/python3/lib/python3.7/site-packages/stepfunctions/steps/sagemaker.py in __init__(self, state_id, model, model_name, instance_type, tags, **kwargs)
203 """
204 if isinstance(model, FrameworkModel):
--> 205 parameters = model_config(model=model, instance_type=instance_type, role=model.role, image=model.image)
206 if model_name:
207 parameters['ModelName'] = model_name
AttributeError: 'TensorFlowModel' object has no attribute 'image'
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@shunjd any update on timing for SageMaker SDK 2.x support?
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@cfregly I have a PR ready for merging #76
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Is this incorporated into the new release? This is also causing Pipenv not being able to lock. Specifically, when sagemaker>2.0.0 is already installed in the virtual env:
ERROR: Could not find a version that matches sagemaker<2.0.0,==2.15.0,>=1.71.0 (from -r /var/folders/91/xv32p1qd2g573gzb6h85ngsc0000gn/T/pipenvj8m7d8dhrequirements/pipenv-yvcfit9i-constraints.txt (line 8))
Pipenv won't have issues creating a new virtual env with unspecified versions of sagemaker and stepfunctions, because it'll select sagemaker==1.72.1. But this would of course break code, as mentioned in the PR above.
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Hey all,
We released a pre-release version (2.0.0rc1
) of stepfunctions to PyPI that uses SageMaker 2.0 and drops Python 2 support. Since this introduces breaking changes, this is a major version bump to v2.0.
https://pypi.org/project/stepfunctions/2.0.0rc1/
We're working on a stable release after we sort out the sunsetting plan for v1 of the Step Functions Data Science SDK.
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v2.0.0 was released in March - which includes SageMaker SDK 2.0.
https://github.com/aws/aws-step-functions-data-science-sdk-python/releases/tag/v2.0.0
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Related Issues (20)
- Is it Possible to use schema from ExecutionInput into container_arguments of ProcessingStep? HOT 6
- Feature Request: Add Workflow.create_or_update() to update workflow if it exists or create it if it doesn't HOT 1
- feature: adding support for AsyncInferenceConfig in endpoint config HOT 1
- Unable set ModelClientConfig in TransformerStep HOT 3
- object of type TrainingInput is not JSON serializable HOT 1
- Make sagemaker an optional dependency HOT 5
- [aws-stepfunctions] Support for ResultSelector HOT 1
- Allow drop-in states language HOT 1
- Support "Cycles" with Choice states HOT 1
- pip install stepfunctions fails in SageMaker Studio Notebook
- render_graph() has hidden dependencies
- Workflow Tags are not updated HOT 1
- Retry policies with error codes HOT 1
- stepfunctions package side effect of changing application's root logger logging level to ERROR
- Instructions in CONTRIBUTING no longer work with tox>=4
- Project Maintenance HOT 5
- Execution inputs as container arguments for processing jobs HOT 4
- Stepfunctions-Textract-StartDocumentTextDetection does not accept SNSTopicArn in NotificationChannel HOT 1
- Please add Distributed Map
- adding tags to a Sagemaker estimator in the training step does not seem to be supported
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