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