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Description
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System Information
- Tensorflow:
- Fails for all versions:
- *Fails for py3 and py2:
- Fails for CPU and GPU:
- No custom image:
Describe the problem
If I try to deploy a pre-built model like so:
sagemaker_model = TensorFlowModel(model_data = 's3://' + sagemaker_session.default_bucket() + '/model/model0100.tar.gz',
role = role,
framework_version='1.13', py_version='py3',
entry_point = 'train.py')
Will fail upon deploying:
predictor = sagemaker_model.deploy(initial_instance_count=1,
instance_type='ml.p2.xlarge')
I receive:
ValueError: Error hosting endpoint sagemaker-tensorflow-2019-07-07-11-50-45-473: Failed Reason: The image '520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-tensorflow:1.13-gpu-py3' does not exist.
I can get past this error by specifying the image (which is not well-documented - took a lot of digging to find a link that worked):
sagemaker_model = TensorFlowModel(model_data = 's3://' + sagemaker_session.default_bucket() + '/model/model0100.tar.gz',
role = role,
framework_version='1.13', py_version='py3',
entry_point = 'train.py', image = '763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference:1.13-gpu' )
Any idea how to solve this?
prameshbajra, nathanielrindlaub, ratulray, nilesh-patil and Laurens-T