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Jan 5, 2018
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Add FAQ entry to README explaining how to predict against existing endpoints #37

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Add FAQ entry showing how to make predictions against existing endpoint
winstonaws Jan 3, 2018
f31b3c6
Fix code block formatting
winstonaws Jan 4, 2018
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21 changes: 21 additions & 0 deletions README.rst
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Expand Up @@ -1506,3 +1506,24 @@ Once you have the aws cli installed, you can upload a directory of files to S3 w
aws s3 cp /tmp/foo/ s3://bucket/path

You can read more about using the aws cli for manipulating S3 resources in the `AWS cli command reference <http://docs.aws.amazon.com/cli/latest/reference/s3/index.html>`__.


How do I make predictions against an existing endpoint?
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Create a Predictor object and provide it your endpoint name. Then, simply call its predict() method with your input.

You can either use the generic RealTimePredictor class, which by default does not perform any serialization/deserialization transformations on your input, but can be configured to do so through constructor arguments:
http://sagemaker.readthedocs.io/en/latest/predictors.html

Or you can use the TensorFlow / MXNet specific predictor classes, which have default serialization/deserialization logic:
http://sagemaker.readthedocs.io/en/latest/sagemaker.tensorflow.html#tensorflow-predictor
http://sagemaker.readthedocs.io/en/latest/sagemaker.mxnet.html#mxnet-predictor

Example code using the TensorFlow predictor:

::

from sagemaker.tensorflow import TensorFlowPredictor

predictor = TensorFlowPredictor('myexistingendpoint')
result = predictor.predict(['my request body'])