如何解决 AttributeError: 'NoneType' 对象没有属性 'CONTENT_TYPE'

如何解决如何解决 AttributeError: 'NoneType' 对象没有属性 'CONTENT_TYPE'

我正在按照教程在 Sagemaker 上使用 MXNET 来开发推荐引擎。

执行以下单元格后，我收到 AttributeError: 'nonetype' object has no attribute 'CONTENT_TYPE'

test_preds= []
for array in np.array_split(test_df[['customer_id','product_id']].values,40):
    test_preds += 
predictor.predict(json.dumps({'customer_id':array[:,0].tolist(),'product_id':array[:,1].tolist()}))
test_preds = np.array(test_preds)
print('MSE:',np.mean((test_df['star_rating'] -test_preds))**2)

显示的错误：

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-38-a830dbc6ac84> in <module>
      2 for array in np.array_split(test_df[['customer_id',40):
      3     test_preds += predictor.predict(json.dumps({'customer_id':array[:,----> 4                                    'product_id':array[:,1].tolist()}))
      5 test_preds = np.array(test_preds)
      6 print('MSE:',np.mean((test_df['star_rating'] -test_preds))**2)

~/anaconda3/envs/amazonei_mxnet_p36/lib/python3.6/site-packages/sagemaker/predictor.py in predict(self,data,initial_args,target_model,target_variant,inference_id)
    132 
    133         request_args = self._create_request_args(
--> 134             data,inference_id
    135         )
    136         response = self.sagemaker_session.sagemaker_runtime_client.invoke_endpoint(**request_args)

~/anaconda3/envs/amazonei_mxnet_p36/lib/python3.6/site-packages/sagemaker/predictor.py in _create_request_args(self,inference_id)
    158 
    159         if "ContentType" not in args:
--> 160             args["ContentType"] = self.content_type
    161 
    162         if "Accept" not in args:

~/anaconda3/envs/amazonei_mxnet_p36/lib/python3.6/site-packages/sagemaker/predictor.py in content_type(self)
    511     def content_type(self):
    512         """The MIME type of the data sent to the inference endpoint."""
--> 513         return self.serializer.CONTENT_TYPE
    514 
    515     @property

AttributeError: 'nonetype' object has no attribute 'CONTENT_TYPE'

  

**predictor 是训练模型的生产端点

test_df 在这里定义

df_titles = df[['customer_id','product_title','product_id','star_rating']]

df = df[['customer_id','star_rating']]

customers = df['customer_id'].value_counts()
products = df['product_id'].value_counts()

# Filter long-tail
customers = customers[customers >= 5]
products = products[products >= 10]
reduced_df_titles = df_titles.merge(pd.DataFrame({'customer_id': 
customers.index})).merge(pd.DataFrame({'product_id': 
products.index}))

reduced_df = df.merge(pd.DataFrame({'customer_id': 
customers.index})).merge(pd.DataFrame({'product_id': 
products.index}))
customers = reduced_df['customer_id'].value_counts()
products = reduced_df['product_id'].value_counts()

# Number users and items
#Next,we'll number each user and item,giving them their own 
sequential index. This will allow us to hold
#the information in a sparse format where the sequential indices 
indicate the row and column in our ratings matrix.
customer_index = pd.DataFrame({'customer_id': customers.index,'user': 
np.arange(customers.shape[0])})
product_index = pd.DataFrame({'product_id': products.index,'item': 
np.arange(products.shape[0])})

reduced_df = reduced_df.merge(customer_index).merge(product_index)
reduced_df_titles = 
reduced_df_titles.merge(customer_index).merge(product_index)

# Split train and test

train_df,test_df = train_test_split(reduced_df,test_size=0.2,random_state=0)