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Sagemaker Inference for Tensorflow Base64 Input Error through API Gateway

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When I am trying to call my Sagemaker TF endpoint using API Gateway -> Lambda Func by passing a Base 64 String (an image) I am getting an unsupported string error. I also tried with application/Json but I am still getting the error. Need Suggestion.

In Notebook Instance this is how my input looks: <CODE> input = { 'instances': [{"b64": "iV"}] }

In Lambda function I am doing this: <CODE>

instance = [{"b64": "b64string"}] pleasework=json.dumps({"instances": instance}) response = runtime.invoke_endpoint(EndpointName=ENDPOINT_NAME_BASE64,ContentType='string',Accept='string' ,Body=pleasework)

ERROR: Inference Error: An error occurred (ModelError) when calling the InvokeEndpoint operation: Received client error (415) from primary with message "{"error": "Unsupported Media Type: string"}".

Incase if I pass application/json I get this error:

Received client error (400) from primary with message "{ "error": "Failed to process element: 0 of 'instances' list. Error: INVALID_ARGUMENT: JSON Value: {\n "b64": "iV"\n} Type: Object is not of expected type: uint8"}"

1 Answers
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I would suggest testing invoking your model locally first and confirming what the input your model is expecting using the saved_model CLI. Kindly see this link: https://www.tensorflow.org/guide/saved_model#the_savedmodel_format_on_disk

Then when invoking the model confirm that instance is in the correct input format shape your model expects.

answered 5 days ago

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