How to look at the parameters of a pytorch model?












0















I have a simple pytorch neural net that I copied from openai, and I modified it to some extent (mostly the input).



When I run my code, the output of the network remains the same on every episode, as if no training occurs.



I want to see if any training happens, or if some other reason causes the results to be the same.



How can I make sure any movement happens to the weights?



Thanks






machine-learning neural-network pytorch openai-gym







share|improve this question





























    0















    I have a simple pytorch neural net that I copied from openai, and I modified it to some extent (mostly the input).



    When I run my code, the output of the network remains the same on every episode, as if no training occurs.



    I want to see if any training happens, or if some other reason causes the results to be the same.



    How can I make sure any movement happens to the weights?



    Thanks






    machine-learning neural-network pytorch openai-gym







    share|improve this question



























      0












      0








      0








      I have a simple pytorch neural net that I copied from openai, and I modified it to some extent (mostly the input).



      When I run my code, the output of the network remains the same on every episode, as if no training occurs.



      I want to see if any training happens, or if some other reason causes the results to be the same.



      How can I make sure any movement happens to the weights?



      Thanks






      machine-learning neural-network pytorch openai-gym







      share|improve this question
















      I have a simple pytorch neural net that I copied from openai, and I modified it to some extent (mostly the input).



      When I run my code, the output of the network remains the same on every episode, as if no training occurs.



      I want to see if any training happens, or if some other reason causes the results to be the same.



      How can I make sure any movement happens to the weights?



      Thanks






      machine-learning neural-network pytorch openai-gym




      machine-learning neural-network pytorch openai-gym






      share|improve this question















      share|improve this question













      share|improve this question




      share|improve this question








      edited Jan 18 at 19:17







      Gulzar

















      asked Jan 18 at 18:57









      GulzarGulzar

      8371820




      8371820
























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          Depends on what you are doing, but the easiest would be to check weights of your model.



          You can check them really easily (and compare with the ones from previous iteration) using this code:



          for parameter in model.parameters():
          
    print(parameter.data)


          If the weights are changing, the neural network is being optimized (which doesn't necessarily mean it learns anything useful in particular).






          share|improve this answer























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            1 Answer
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            1 Answer
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            active

            oldest

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            active

            oldest

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            active

            oldest

            votes









            2














            Depends on what you are doing, but the easiest would be to check weights of your model.



            You can check them really easily (and compare with the ones from previous iteration) using this code:



            for parameter in model.parameters():
            
    print(parameter.data)


            If the weights are changing, the neural network is being optimized (which doesn't necessarily mean it learns anything useful in particular).






            share|improve this answer




























              2














              Depends on what you are doing, but the easiest would be to check weights of your model.



              You can check them really easily (and compare with the ones from previous iteration) using this code:



              for parameter in model.parameters():
              
    print(parameter.data)


              If the weights are changing, the neural network is being optimized (which doesn't necessarily mean it learns anything useful in particular).






              share|improve this answer


























                2












                2








                2







                Depends on what you are doing, but the easiest would be to check weights of your model.



                You can check them really easily (and compare with the ones from previous iteration) using this code:



                for parameter in model.parameters():
                
    print(parameter.data)


                If the weights are changing, the neural network is being optimized (which doesn't necessarily mean it learns anything useful in particular).






                share|improve this answer













                Depends on what you are doing, but the easiest would be to check weights of your model.



                You can check them really easily (and compare with the ones from previous iteration) using this code:



                for parameter in model.parameters():
                
    print(parameter.data)


                If the weights are changing, the neural network is being optimized (which doesn't necessarily mean it learns anything useful in particular).







                share|improve this answer












                share|improve this answer



                share|improve this answer










                answered Jan 18 at 20:29









                Szymon MaszkeSzymon Maszke

                4648




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