如何使用Lambda和API网关部署AWS Sagemaker创建的乳腺癌预测端点?

print(type(result)) 你可以看到它是一本字典。现在您可以看到关键字名称是“score”,而不是您要给pred的“predicted\u label”。因此,将其替换为

pred = int(result['predictions'][0]['score'])

这是我的lambda函数:

import os
import io
import boto3
import json
import csv

# grab environment variables
ENDPOINT_NAME = os.environ['ENDPOINT_NAME']
runtime= boto3.client('runtime.sagemaker')

def lambda_handler(event, context):
   print("Received event: " + json.dumps(event, indent=2))

   data = json.loads(json.dumps(event))
   payload = data['data']
   print(payload)

   response = runtime.invoke_endpoint(EndpointName=ENDPOINT_NAME,
                                      ContentType='text/csv',
                                      Body=payload)
   #print(response)
   print(type(response))
   for key,value in response.items():
       print(key,value)
   result = json.loads(response['Body'].read().decode())
   print(type(result))
   print(result['predictions'])
   pred = int(result['predictions'][0]['score'])
   print(pred)
   predicted_label = 'M' if pred == 1 else 'B'

   return predicted_label