살아 움직이는 머신러닝 파이프라인 설계: 텐서플로와 함께하는 머신러닝 프로젝트 자동화

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살아 움직이는 머신러닝 파이프라인 설계

examples=example_gen.outputs[“examples”])

context.run(statistics_gen)

for artifact in statistics_gen.outputs[“statistics”].get():

print(artifact.uri)

schema_gen = SchemaGen(

statistics=statistics_gen.outputs[“statistics”],

infer_feature_shape=False,

)

context.run(schema_gen)

transform = Transform(

examples=example_gen.outputs[“examples”],

schema=schema_gen.outputs[“schema”],

module_file=os.path.abspath(“transform.py”))

context.run(transform)

trainer = Trainer(

module_file=os.path.abspath(“trainer.py”),

examples=transform.outputs[“transformed_examples”],

transform_graph=transform.outputs[“transform_graph”],

schema=schema_gen.outputs[“schema”], ...