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slevental opened this issue Jan 17, 2018 · 1 comment
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How to create model without deploying endpoint? #49

slevental opened this issue Jan 17, 2018 · 1 comment

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@slevental
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Is it possible to create a model in SageMaker without doing tensorflow_estimator.deploy(...)?

@slevental
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Never mind, I've found solution:

import datetime
import sagemaker
from sagemaker import get_execution_role

sagemaker_session = sagemaker.Session()

role = get_execution_role()
model = tf_estimator.create_model()

container_def = model.prepare_container_def(
    instance_type='ml.m4.xlarge'
)

model_name = f"my-model-{datetime.datetime.now():%Y-%m-%d-%H-%M}"
sagemaker_session.create_model(model_name, role, container_def)

laurenyu added a commit to laurenyu/sagemaker-python-sdk that referenced this issue May 31, 2018
apacker pushed a commit to apacker/sagemaker-python-sdk that referenced this issue Nov 15, 2018
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