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You can do this with the latest version of the sagemaker sdk 2.89.0
from sagemaker.workflow.pipeline_context import PipelineSession
session = PipelineSession()
inputs = [
ProcessingInput(
source="s3://my-bucket/sourcefile",
destination="/opt/ml/processing/inputs/",),
]
processor = FrameworkProcessor(...)
step_args = processor.run(inputs=inputs, source_dir="...")
step_sklearn = ProcessingStep(
name="MyProcessingStep",
step_args=step_args,
)
已回答 3 年前
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- 已提問 3 個月前

thank you!