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There should be a way to achieve this. The properties
attribute just mimics the response of Describe*
API call. In DescribeTrainingJob
API, we have OutputDataConfig
field as in https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_DescribeTrainingJob.html#API_DescribeTrainingJob_ResponseSyntax
So should be something like step.properties.OutputDataConfig.S3OutputPath
Having the same problem and tried setting an input to my evaluation job with source "step.properties.OutputDataConfig.S3OutputPath", but it doesn't evaluate to correct s3 path. Any other ideas?
Hi,
You will need to provide the output path in the EstimatorBase of the training step.
Examples
estimator_example = Estimator(
base_job_name="example",
role=role_arn,
instance_count=1,
output_path=f"s3://example-bucket/my-model",
environment={"region": region.name, "scope": scope_parameter},
output_kms_key=kms_key_arn
)
training_step = TrainingStep(
name="ExampleModelTraining",
estimator=estimator_example,
inputs={
"training_data": TrainingInput(
s3_data=transform_step.properties.ProcessingOutputConfig.Outputs[
transform_training_data_output_name
].S3Output.S3Uri
),
"training_target": TrainingInput(
s3_data=transform_step.properties.ProcessingOutputConfig.Outputs[
transform_training_target_output_name
].S3Output.S3Uri
),
},
)
Thanks,
Hi! As you can see in my question, Im already providing the output_path in my estimator. The question is: how can other pipeline steps access the custom outputs generated by the training step?
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- 已提問 10 個月前
- AWS 官方已更新 2 年前
- AWS 官方已更新 2 年前
Running into the same issue and found your question. Did you find solution for the above by any chance?