Amazon web services 的SSL验证失败https://runtime.sagemaker.us-east-2.amazonaws.com/endpoints/sagemaker-tensorflow 拉姆达?

Amazon web services 的SSL验证失败https://runtime.sagemaker.us-east-2.amazonaws.com/endpoints/sagemaker-tensorflow 拉姆达?,amazon-web-services,tensorflow,machine-learning,amazon-sagemaker,Amazon Web Services,Tensorflow,Machine Learning,Amazon Sagemaker,嗨,我一直在努力调用sagemaker模型的端点,我能够从jupyter调用predict方法。问题是当从lamda调用端点时,这是我的代码 import boto3 import math import dateutil import json import os import nltk from nltk.corpus import stopwords import string from nltk.stem import WordNetLemmatizer from sklearn.fea

嗨,我一直在努力调用sagemaker模型的端点,我能够从jupyter调用predict方法。问题是当从lamda调用端点时,这是我的代码

import boto3
import math
import dateutil
import json
import os
import nltk
from nltk.corpus import stopwords
import string
from nltk.stem import WordNetLemmatizer
from sklearn.feature_extraction.text import TfidfVectorizer
import numpy

nltk.data.path.append("/tmp")
nltk.download("stopwords", download_dir = "/tmp")
nltk.download("punkt", download_dir = "/tmp")
nltk.download("wordnet", download_dir = "/tmp")

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

def lambda_handler(event, context):
    try:    
        print("Received event: " + json.dumps(event, indent=2))    
        request = json.loads(json.dumps(event))
        transformed_data = json.dumps(event)
        stopword = stopwords.words('english')
        lemmatizer = WordNetLemmatizer()
        vectorizer = TfidfVectorizer()
        tokens = nltk.word_tokenize('this is sample text')
        no_stop = [word for word in tokens if word not in stopword]
        # no_punc = [word for word in no_stop if word not in string.punctuation]
        # print(no_punc +'no punc**')
        vertorized_data = vectorizer.fit_transform(no_stop)
        vertorized_data = vertorized_data.toarray()
        data = numpy.array(vertorized_data)
        payload = json.dumps(data.tolist())

        result = client.invoke_endpoint(EndpointName=ENDPOINT_NAME, 
                               Body=payload,
                               ContentType='application/json')
                               
    
        result = result['Body'].read().decode('utf-8')
        print(result)
        
        return {
            'statusCode': 200,
            'isBase64Encoded':False,
            'body': json.dumps(predictions)
        }

    except Exception as err:
        return {
            'statusCode': 400,
            'isBase64Encoded':False,
            'body': 'Call Failed {0}'.format(err)
        }
我得到的错误如下

“正文”:“调用失败,[Errno 2]没有此类文件或目录的SSL验证失败”

注意:我可以通过jupyter笔记本而不是lamda的端点调用predict