Understanding backprop for softmax












1












$begingroup$


I'm looking on a given solution of the first assignment of cs231n course.



Down below a snippet from the loss function.
I don't really understand lines 140-143. Can you explain why dscores (the derivative of scores) is calculated like that?



enter image description here










share|improve this question









$endgroup$




bumped to the homepage by Community 4 hours ago


This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.















  • $begingroup$
    What is y? and N in conjunction to lim_scores?
    $endgroup$
    – Matthieu Brucher
    Dec 22 '18 at 21:04
















1












$begingroup$


I'm looking on a given solution of the first assignment of cs231n course.



Down below a snippet from the loss function.
I don't really understand lines 140-143. Can you explain why dscores (the derivative of scores) is calculated like that?



enter image description here










share|improve this question









$endgroup$




bumped to the homepage by Community 4 hours ago


This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.















  • $begingroup$
    What is y? and N in conjunction to lim_scores?
    $endgroup$
    – Matthieu Brucher
    Dec 22 '18 at 21:04














1












1








1





$begingroup$


I'm looking on a given solution of the first assignment of cs231n course.



Down below a snippet from the loss function.
I don't really understand lines 140-143. Can you explain why dscores (the derivative of scores) is calculated like that?



enter image description here










share|improve this question









$endgroup$




I'm looking on a given solution of the first assignment of cs231n course.



Down below a snippet from the loss function.
I don't really understand lines 140-143. Can you explain why dscores (the derivative of scores) is calculated like that?



enter image description here







neural-network deep-learning backpropagation cs231n






share|improve this question













share|improve this question











share|improve this question




share|improve this question










asked Dec 22 '18 at 17:18









yasecoyaseco

1061




1061





bumped to the homepage by Community 4 hours ago


This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.







bumped to the homepage by Community 4 hours ago


This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.














  • $begingroup$
    What is y? and N in conjunction to lim_scores?
    $endgroup$
    – Matthieu Brucher
    Dec 22 '18 at 21:04


















  • $begingroup$
    What is y? and N in conjunction to lim_scores?
    $endgroup$
    – Matthieu Brucher
    Dec 22 '18 at 21:04
















$begingroup$
What is y? and N in conjunction to lim_scores?
$endgroup$
– Matthieu Brucher
Dec 22 '18 at 21:04




$begingroup$
What is y? and N in conjunction to lim_scores?
$endgroup$
– Matthieu Brucher
Dec 22 '18 at 21:04










1 Answer
1






active

oldest

votes


















0












$begingroup$

Be aware that posting code in images very annoying to copy/paste and it's bad for web reference ment.



This is due to the derivative of the softmax, but to me it's seems fishy.



If $S$ is the softmax vector, then the Jacobian $DS$ consists of $S_j(delta_{ij}-S_i)$. This could explain the -=1 part, but not the /=N, and not the shape either.






share|improve this answer









$endgroup$













    Your Answer





    StackExchange.ifUsing("editor", function () {
    return StackExchange.using("mathjaxEditing", function () {
    StackExchange.MarkdownEditor.creationCallbacks.add(function (editor, postfix) {
    StackExchange.mathjaxEditing.prepareWmdForMathJax(editor, postfix, [["$", "$"], ["\\(","\\)"]]);
    });
    });
    }, "mathjax-editing");

    StackExchange.ready(function() {
    var channelOptions = {
    tags: "".split(" "),
    id: "557"
    };
    initTagRenderer("".split(" "), "".split(" "), channelOptions);

    StackExchange.using("externalEditor", function() {
    // Have to fire editor after snippets, if snippets enabled
    if (StackExchange.settings.snippets.snippetsEnabled) {
    StackExchange.using("snippets", function() {
    createEditor();
    });
    }
    else {
    createEditor();
    }
    });

    function createEditor() {
    StackExchange.prepareEditor({
    heartbeatType: 'answer',
    autoActivateHeartbeat: false,
    convertImagesToLinks: false,
    noModals: true,
    showLowRepImageUploadWarning: true,
    reputationToPostImages: null,
    bindNavPrevention: true,
    postfix: "",
    imageUploader: {
    brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
    contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
    allowUrls: true
    },
    onDemand: true,
    discardSelector: ".discard-answer"
    ,immediatelyShowMarkdownHelp:true
    });


    }
    });














    draft saved

    draft discarded


















    StackExchange.ready(
    function () {
    StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fdatascience.stackexchange.com%2fquestions%2f43033%2funderstanding-backprop-for-softmax%23new-answer', 'question_page');
    }
    );

    Post as a guest















    Required, but never shown

























    1 Answer
    1






    active

    oldest

    votes








    1 Answer
    1






    active

    oldest

    votes









    active

    oldest

    votes






    active

    oldest

    votes









    0












    $begingroup$

    Be aware that posting code in images very annoying to copy/paste and it's bad for web reference ment.



    This is due to the derivative of the softmax, but to me it's seems fishy.



    If $S$ is the softmax vector, then the Jacobian $DS$ consists of $S_j(delta_{ij}-S_i)$. This could explain the -=1 part, but not the /=N, and not the shape either.






    share|improve this answer









    $endgroup$


















      0












      $begingroup$

      Be aware that posting code in images very annoying to copy/paste and it's bad for web reference ment.



      This is due to the derivative of the softmax, but to me it's seems fishy.



      If $S$ is the softmax vector, then the Jacobian $DS$ consists of $S_j(delta_{ij}-S_i)$. This could explain the -=1 part, but not the /=N, and not the shape either.






      share|improve this answer









      $endgroup$
















        0












        0








        0





        $begingroup$

        Be aware that posting code in images very annoying to copy/paste and it's bad for web reference ment.



        This is due to the derivative of the softmax, but to me it's seems fishy.



        If $S$ is the softmax vector, then the Jacobian $DS$ consists of $S_j(delta_{ij}-S_i)$. This could explain the -=1 part, but not the /=N, and not the shape either.






        share|improve this answer









        $endgroup$



        Be aware that posting code in images very annoying to copy/paste and it's bad for web reference ment.



        This is due to the derivative of the softmax, but to me it's seems fishy.



        If $S$ is the softmax vector, then the Jacobian $DS$ consists of $S_j(delta_{ij}-S_i)$. This could explain the -=1 part, but not the /=N, and not the shape either.







        share|improve this answer












        share|improve this answer



        share|improve this answer










        answered Dec 22 '18 at 21:33









        Matthieu BrucherMatthieu Brucher

        61113




        61113






























            draft saved

            draft discarded




















































            Thanks for contributing an answer to Data Science Stack Exchange!


            • Please be sure to answer the question. Provide details and share your research!

            But avoid



            • Asking for help, clarification, or responding to other answers.

            • Making statements based on opinion; back them up with references or personal experience.


            Use MathJax to format equations. MathJax reference.


            To learn more, see our tips on writing great answers.




            draft saved


            draft discarded














            StackExchange.ready(
            function () {
            StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fdatascience.stackexchange.com%2fquestions%2f43033%2funderstanding-backprop-for-softmax%23new-answer', 'question_page');
            }
            );

            Post as a guest















            Required, but never shown





















































            Required, but never shown














            Required, but never shown












            Required, but never shown







            Required, but never shown

































            Required, but never shown














            Required, but never shown












            Required, but never shown







            Required, but never shown







            Popular posts from this blog

            How to label and detect the document text images

            Vallis Paradisi

            Tabula Rosettana