i'm using a hugging face model and a container to create a batch transform job in sagemaker. i have a custom inference code and in the output_fn function i'm returning json_dumps(prediction). I'm using print(prediction) to see, if i can see it in the cloudwatch logs to find out type and what prediction is. how can log these messages . Also, the inference output i get is in the form below., i'm not sure why is it not a json object in each line instead it has square brackets. I want to use the filter to match the input and output in the batch job. I'm not sure how the output should look like , because i'm trying to associate input with output by using dataprocessing config as below. but i get an error. the documenation has example of csv not json. what should the output look like so that i can associate the input with output when they both are in json format.
"DataProcessing": {
"JoinSource": "Input"
},
[ output text 1 ]
[output text 2 ]
# Serialize the prediction result into the desired response content type
def output_fn(prediction, accept=JSON_CONTENT_TYPE):
logger.info("Serializing the generated output.")
if accept == JSON_CONTENT_TYPE:
output = json.dumps(prediction)
return output, accept
raise Exception("Requested unsupported ContentType in Accept: {}".format(accept))
Have you taken a look at this StackOverflow question: https://stackoverflow.com/questions/60421123/aws-sagemaker-batch-transform-with-json-input-filter