getting a 403 response with Google AutoML vision Python API despite having assigned right Service Account












0















I have trained a model using google cloud AutoML Vision API, however when I specifically try to obtain the model performance metrics via the Python package I keep getting a 403 response: 



PermissionDenied: 403 Permission 'automl.modelEvaluations.list' denied on resource 'projects/MY_BUCKET_ID/locations/us-central1/models/MY_MODEL_ID' (or it may not exist).


I am using the python code as layed out in the documentation and also not having any unauthorised ops with the other operations (Create Dataset, Train Model), so really struggling to understand why is this the case. Here is the code:



# Get the full path of the model.

model_full_id = client.model_path(project_id, compute_region, model_id)

print(model_full_id)



# List all the model evaluations in the model by applying filter.

response = client.list_model_evaluations(model_full_id, filter_)


Thanks for your help






python google-cloud-automl







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    0















    I have trained a model using google cloud AutoML Vision API, however when I specifically try to obtain the model performance metrics via the Python package I keep getting a 403 response: 



    PermissionDenied: 403 Permission 'automl.modelEvaluations.list' denied on resource 'projects/MY_BUCKET_ID/locations/us-central1/models/MY_MODEL_ID' (or it may not exist).


    I am using the python code as layed out in the documentation and also not having any unauthorised ops with the other operations (Create Dataset, Train Model), so really struggling to understand why is this the case. Here is the code:



    # Get the full path of the model.
    
model_full_id = client.model_path(project_id, compute_region, model_id)
    
print(model_full_id)
    

    
# List all the model evaluations in the model by applying filter.
    
response = client.list_model_evaluations(model_full_id, filter_)


    Thanks for your help






    python google-cloud-automl







    share|improve this question

























      0












      0








      0








      I have trained a model using google cloud AutoML Vision API, however when I specifically try to obtain the model performance metrics via the Python package I keep getting a 403 response: 



      PermissionDenied: 403 Permission 'automl.modelEvaluations.list' denied on resource 'projects/MY_BUCKET_ID/locations/us-central1/models/MY_MODEL_ID' (or it may not exist).


      I am using the python code as layed out in the documentation and also not having any unauthorised ops with the other operations (Create Dataset, Train Model), so really struggling to understand why is this the case. Here is the code:



      # Get the full path of the model.
      
model_full_id = client.model_path(project_id, compute_region, model_id)
      
print(model_full_id)
      

      
# List all the model evaluations in the model by applying filter.
      
response = client.list_model_evaluations(model_full_id, filter_)


      Thanks for your help






      python google-cloud-automl







      share|improve this question














      I have trained a model using google cloud AutoML Vision API, however when I specifically try to obtain the model performance metrics via the Python package I keep getting a 403 response: 



      PermissionDenied: 403 Permission 'automl.modelEvaluations.list' denied on resource 'projects/MY_BUCKET_ID/locations/us-central1/models/MY_MODEL_ID' (or it may not exist).


      I am using the python code as layed out in the documentation and also not having any unauthorised ops with the other operations (Create Dataset, Train Model), so really struggling to understand why is this the case. Here is the code:



      # Get the full path of the model.
      
model_full_id = client.model_path(project_id, compute_region, model_id)
      
print(model_full_id)
      

      
# List all the model evaluations in the model by applying filter.
      
response = client.list_model_evaluations(model_full_id, filter_)


      Thanks for your help






      python google-cloud-automl




      python google-cloud-automl






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      asked Nov 15 '18 at 15:35









      Daniel VieiraDaniel Vieira

      1136




      1136
























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          After a few tests I found the problem. When calling out the model details you need to use model_id and not model_name, whereas in the previous API calls in the documentation the model_name was the identifier to use.



          model_full_id = client.model_path(project_id, compute_region, model_id)


          This fixed the issue.






          share|improve this answer























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            After a few tests I found the problem. When calling out the model details you need to use model_id and not model_name, whereas in the previous API calls in the documentation the model_name was the identifier to use.



            model_full_id = client.model_path(project_id, compute_region, model_id)


            This fixed the issue.






            share|improve this answer




























              1














              After a few tests I found the problem. When calling out the model details you need to use model_id and not model_name, whereas in the previous API calls in the documentation the model_name was the identifier to use.



              model_full_id = client.model_path(project_id, compute_region, model_id)


              This fixed the issue.






              share|improve this answer


























                1












                1








                1







                After a few tests I found the problem. When calling out the model details you need to use model_id and not model_name, whereas in the previous API calls in the documentation the model_name was the identifier to use.



                model_full_id = client.model_path(project_id, compute_region, model_id)


                This fixed the issue.






                share|improve this answer













                After a few tests I found the problem. When calling out the model details you need to use model_id and not model_name, whereas in the previous API calls in the documentation the model_name was the identifier to use.



                model_full_id = client.model_path(project_id, compute_region, model_id)


                This fixed the issue.







                share|improve this answer












                share|improve this answer



                share|improve this answer










                answered Nov 16 '18 at 17:54









                Daniel VieiraDaniel Vieira

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                1136






























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