Python Notebook Invoke Endpoint Sagemaker from Local

Question

I am trying to invoke an Amazon Sagemaker Endpoint from a local python notebook. This is the code I am using.

import boto3

aws_access_key_id = '...............'
aws_secret_access_key = '................'
tkn = '..........'
region_name = '............'

amz = boto3.client('sagemaker-runtime',
                   aws_access_key_id=aws_access_key_id,
                   aws_secret_access_key=aws_secret_access_key,
                   aws_session_token=tkn,
                   region_name=region_name)


response = amz.invoke_endpoint(
    EndpointName='mymodel',
    Body=b'bytes'
)

However, this doesn't work. Do I have to specify something else in Body ?

Fahri · Accepted Answer · 2018-06-28 15:34:07Z

2

You can use boto3 session . I assume you already prepared jsons and your aws credentials are already on ~/.aws/credentials.

import boto3, json, sagemaker

sagemaker_session = sagemaker.Session()
role              = "YOUR-SAGEMAKER-EXECUTION-ROLE"
region            = boto3.Session().region_name
endpointName=     'YOUR ENDPOINT NAME'
predictor = sagemaker.predictor.RealTimePredictor(
               endpointName, 
               sagemaker_session=sagemaker_session, 
               content_type="application/json")
d='YOUR JSON LINES- YOU CAN OPEN WITH PYTHON BUILT IN FUNCTIONS'
response=predictor.predict(json.dumps(d))

response has the answer body which formatted in json. You can parse it and use your results.

answered Jun 28, 2018 at 15:34

Fahri

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Gili Nachum · Accepted Answer · 2018-06-15 20:27:15Z

0

Each endpoint expects different binary data. By specifying Body=b'bytes' you're passing the bytes of the string literal bytes, while you should be passing some actual input data to infer off.

According to the doc, I recommended to include the relevant ContentType, of the input data you're sending.

You said:

However, this doesn't work.

What is the error you're getting back?

answered Jun 15, 2018 at 20:27

Gili Nachum

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