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通过Python实现Google Cloud Machine Learning Engine的在线预测(Implement online predictions of Google Cloud Machine Learning Engine by Python)

 我想将App Engine的请求发送到ML Engine的模型。  
 我构建了用于在本地计算机上进行测试的示例代码。 但是，我收到错误'UNAUTHENTICATED'：  
WARNING:root:No ssl package found. urlfetch will not be able to validate SSL certificates.
91bnQuY34Oh8cJyF=....
{
  "error": {
    "code": 401,
    "message": "Request had invalid authentication credentials. Expected OAuth 2 access token, login cookie or other valid authentication credential. See https://developers.google.com/identity/sign-in/web/devconsole-project.",
    "status": "UNAUTHENTICATED"
  }
}
 
 我的示例代码：  
from google.appengine.api import urlfetch
import urllib
import time
import jwt

data_to_post = {"instances":[{"text":[185,15,14,124,370,832,112,120,...]}]}
encoded_data = urllib.urlencode(data_to_post)

model_url = 'https://ml.googleapis.com/v1/projects/myproject/models/analyizesentiment:predict'

from google.appengine.api import apiproxy_stub_map 
from google.appengine.api import urlfetch_stub
apiproxy_stub_map.apiproxy = apiproxy_stub_map.APIProxyStubMap() 
apiproxy_stub_map.apiproxy.RegisterStub('urlfetch', urlfetch_stub.URLFetchServiceStub())

PRIVATE_KEY_ID_FROM_JSON = '??????????????????'
PRIVATE_KEY_FROM_JSON = "-----BEGIN PRIVATE KEY-----\n??????????\n-----END PRIVATE KEY-----\n"
iat = time.time()
exp = iat + 3600
payload = {'iss': 'accountname@myprojectname.iam.gserviceaccount.com',
           'sub': 'accountname@myprojectname.iam.gserviceaccount.com',
           'aud': 'https://ml.googleapis.com/v1/',
           'iat': iat,
           'exp': exp}
additional_headers = {'kid': PRIVATE_KEY_ID_FROM_JSON,
                      'alg': "RS256",
                      "typ": "JWT",}
signed_jwt = jwt.encode(payload, PRIVATE_KEY_FROM_JSON, headers=additional_headers, algorithm='RS256')
print(signed_jwt)

result = urlfetch.fetch(model_url, encoded_data, method=urlfetch.POST, headers={'Content-type': 'application/json', 'Authorization': 'Bearer ' + signed_jwt})
print(result.content)

I want to send requests from App Engine to the model of ML Engine. 
I built the sample code for testing on my local machine. However, I received the error 'UNAUTHENTICATED':  
WARNING:root:No ssl package found. urlfetch will not be able to validate SSL certificates.
91bnQuY34Oh8cJyF=....
{
  "error": {
    "code": 401,
    "message": "Request had invalid authentication credentials. Expected OAuth 2 access token, login cookie or other valid authentication credential. See https://developers.google.com/identity/sign-in/web/devconsole-project.",
    "status": "UNAUTHENTICATED"
  }
}
 
My sample code: 
from google.appengine.api import urlfetch
import urllib
import time
import jwt

data_to_post = {"instances":[{"text":[185,15,14,124,370,832,112,120,...]}]}
encoded_data = urllib.urlencode(data_to_post)

model_url = 'https://ml.googleapis.com/v1/projects/myproject/models/analyizesentiment:predict'

from google.appengine.api import apiproxy_stub_map 
from google.appengine.api import urlfetch_stub
apiproxy_stub_map.apiproxy = apiproxy_stub_map.APIProxyStubMap() 
apiproxy_stub_map.apiproxy.RegisterStub('urlfetch', urlfetch_stub.URLFetchServiceStub())

PRIVATE_KEY_ID_FROM_JSON = '??????????????????'
PRIVATE_KEY_FROM_JSON = "-----BEGIN PRIVATE KEY-----\n??????????\n-----END PRIVATE KEY-----\n"
iat = time.time()
exp = iat + 3600
payload = {'iss': 'accountname@myprojectname.iam.gserviceaccount.com',
           'sub': 'accountname@myprojectname.iam.gserviceaccount.com',
           'aud': 'https://ml.googleapis.com/v1/',
           'iat': iat,
           'exp': exp}
additional_headers = {'kid': PRIVATE_KEY_ID_FROM_JSON,
                      'alg': "RS256",
                      "typ": "JWT",}
signed_jwt = jwt.encode(payload, PRIVATE_KEY_FROM_JSON, headers=additional_headers, algorithm='RS256')
print(signed_jwt)

result = urlfetch.fetch(model_url, encoded_data, method=urlfetch.POST, headers={'Content-type': 'application/json', 'Authorization': 'Bearer ' + signed_jwt})
print(result.content)

原文：https://stackoverflow.com/questions/49758982

更新时间：2022-11-11 13:11

最满意答案

 请验证LogErrorImport表上的主键。 确保它是一个设置为自动增量的标识列。 不要在代码中的任何位置设置此主键。 如果这些检查没有问题，则不应该出现重复的主键错误。  
 更新：您需要在try和catch块中使用using语句定义不同的'db'上下try ，以便它们不会相互冲突。 你可以这样做：  
try
{
   using (var _context = new DBContext())
   {
      //Normal save logic here
     _context.Save();
   }
}
catch(Exception ex)
{
   using (var _context = new DBContext())
   {
      //Log error here
     _context.Save();
   }
}

Please verify the Primary Key on your LogErrorImport table. Make sure it is an identity column which is set to auto increment. Do not set this primary key anywhere in your code. If these checks are alright, you shouldn't be getting duplicate Primary Key error. 
Update: You will need to define different sets of 'db' context in try and catch block with using statement so that they do not conflict with each other. You might do something like: 
try
{
   using (var _context = new DBContext())
   {
      //Normal save logic here
     _context.Save();
   }
}
catch(Exception ex)
{
   using (var _context = new DBContext())
   {
      //Log error here
     _context.Save();
   }
}

通过Python实现Google Cloud Machine Learning Engine的在线预测(Implement online predictions of Google Cloud Machine Learning Engine by Python)

最满意答案

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