tf.data.Dataset with constant size batches












1















I have a dataset with 19 elements and a batch size of 10. I set my dataset to continuously iterate over the same elements but I noticed that the last batch has only 4 elements instead of 5, and then it starts over with 5, 5, 5, 4, and so on.



How is is possible to force the iterator to fill up shorter batches with elements coming from the next iteration so that all the batches have the same size?



P.S. just to understand, isn't this the obvious behavior when training a model?






tensorflow tensorflow-datasets







share|improve this question




















  • 1





    If you look at the documentation of tf.data.Dataset.batch, there is an optional drop_remainder parameter to discard the last incomplete batch. I don't know if there is a way to complete the last batch with the beginning of the next iteration. If you're shuffling your data it shouldn't matter discarding the last batch, but anyway it would be interesting to have a way to do that.

    – jdehesa
    Nov 19 '18 at 21:35


















1















I have a dataset with 19 elements and a batch size of 10. I set my dataset to continuously iterate over the same elements but I noticed that the last batch has only 4 elements instead of 5, and then it starts over with 5, 5, 5, 4, and so on.



How is is possible to force the iterator to fill up shorter batches with elements coming from the next iteration so that all the batches have the same size?



P.S. just to understand, isn't this the obvious behavior when training a model?






tensorflow tensorflow-datasets







share|improve this question




















  • 1





    If you look at the documentation of tf.data.Dataset.batch, there is an optional drop_remainder parameter to discard the last incomplete batch. I don't know if there is a way to complete the last batch with the beginning of the next iteration. If you're shuffling your data it shouldn't matter discarding the last batch, but anyway it would be interesting to have a way to do that.

    – jdehesa
    Nov 19 '18 at 21:35
















1












1








1








I have a dataset with 19 elements and a batch size of 10. I set my dataset to continuously iterate over the same elements but I noticed that the last batch has only 4 elements instead of 5, and then it starts over with 5, 5, 5, 4, and so on.



How is is possible to force the iterator to fill up shorter batches with elements coming from the next iteration so that all the batches have the same size?



P.S. just to understand, isn't this the obvious behavior when training a model?






tensorflow tensorflow-datasets







share|improve this question
















I have a dataset with 19 elements and a batch size of 10. I set my dataset to continuously iterate over the same elements but I noticed that the last batch has only 4 elements instead of 5, and then it starts over with 5, 5, 5, 4, and so on.



How is is possible to force the iterator to fill up shorter batches with elements coming from the next iteration so that all the batches have the same size?



P.S. just to understand, isn't this the obvious behavior when training a model?






tensorflow tensorflow-datasets




tensorflow tensorflow-datasets






share|improve this question















share|improve this question













share|improve this question




share|improve this question








edited Nov 19 '18 at 21:26







petrux

















asked Nov 19 '18 at 21:17









petruxpetrux

688822




688822








  • 1





    If you look at the documentation of tf.data.Dataset.batch, there is an optional drop_remainder parameter to discard the last incomplete batch. I don't know if there is a way to complete the last batch with the beginning of the next iteration. If you're shuffling your data it shouldn't matter discarding the last batch, but anyway it would be interesting to have a way to do that.

    – jdehesa
    Nov 19 '18 at 21:35
















  • 1





    If you look at the documentation of tf.data.Dataset.batch, there is an optional drop_remainder parameter to discard the last incomplete batch. I don't know if there is a way to complete the last batch with the beginning of the next iteration. If you're shuffling your data it shouldn't matter discarding the last batch, but anyway it would be interesting to have a way to do that.

    – jdehesa
    Nov 19 '18 at 21:35










1




1





If you look at the documentation of tf.data.Dataset.batch, there is an optional drop_remainder parameter to discard the last incomplete batch. I don't know if there is a way to complete the last batch with the beginning of the next iteration. If you're shuffling your data it shouldn't matter discarding the last batch, but anyway it would be interesting to have a way to do that.

– jdehesa
Nov 19 '18 at 21:35







If you look at the documentation of tf.data.Dataset.batch, there is an optional drop_remainder parameter to discard the last incomplete batch. I don't know if there is a way to complete the last batch with the beginning of the next iteration. If you're shuffling your data it shouldn't matter discarding the last batch, but anyway it would be interesting to have a way to do that.

– jdehesa
Nov 19 '18 at 21:35














1 Answer
1






active

oldest

votes


















1














To have this behavior, the .repeat() method should be invoked before the batch() or padded_batch() one. So:



file_names = [...]

def my_map_func(record):

    ....

dataset = tf.data.TFRecordDataset(file_names)

    .map(map_func=my_map_func)

    .repeat()  # here!

    .batch(5)





share|improve this answer























    Your Answer






    StackExchange.ifUsing("editor", function () {
    StackExchange.using("externalEditor", function () {
    StackExchange.using("snippets", function () {
    StackExchange.snippets.init();
    });
    });
    }, "code-snippets");

    StackExchange.ready(function() {
    var channelOptions = {
    tags: "".split(" "),
    id: "1"
    };
    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: true,
    noModals: true,
    showLowRepImageUploadWarning: true,
    reputationToPostImages: 10,
    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%2fstackoverflow.com%2fquestions%2f53382769%2ftf-data-dataset-with-constant-size-batches%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









    1














    To have this behavior, the .repeat() method should be invoked before the batch() or padded_batch() one. So:



    file_names = [...]
    
def my_map_func(record):
    
    ....
    
dataset = tf.data.TFRecordDataset(file_names)
    
    .map(map_func=my_map_func)
    
    .repeat()  # here!
    
    .batch(5)





    share|improve this answer




























      1














      To have this behavior, the .repeat() method should be invoked before the batch() or padded_batch() one. So:



      file_names = [...]
      
def my_map_func(record):
      
    ....
      
dataset = tf.data.TFRecordDataset(file_names)
      
    .map(map_func=my_map_func)
      
    .repeat()  # here!
      
    .batch(5)





      share|improve this answer


























        1












        1








        1







        To have this behavior, the .repeat() method should be invoked before the batch() or padded_batch() one. So:



        file_names = [...]
        
def my_map_func(record):
        
    ....
        
dataset = tf.data.TFRecordDataset(file_names)
        
    .map(map_func=my_map_func)
        
    .repeat()  # here!
        
    .batch(5)





        share|improve this answer













        To have this behavior, the .repeat() method should be invoked before the batch() or padded_batch() one. So:



        file_names = [...]
        
def my_map_func(record):
        
    ....
        
dataset = tf.data.TFRecordDataset(file_names)
        
    .map(map_func=my_map_func)
        
    .repeat()  # here!
        
    .batch(5)






        share|improve this answer












        share|improve this answer



        share|improve this answer










        answered Nov 20 '18 at 8:36









        petruxpetrux

        688822




        688822
































            draft saved

            draft discarded




















































            Thanks for contributing an answer to Stack Overflow!


            • 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.


            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%2fstackoverflow.com%2fquestions%2f53382769%2ftf-data-dataset-with-constant-size-batches%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







            -

            這個網誌中的熱門文章

            Tangent Lines Diagram Along Smooth Curve

            圖片
            7 1 I am trying to replicate a diagram and have a minimal example. I don't know how to add additional tangents between the specified points and preserve smoothness. documentclass{article} usepackage{tikz} usetikzlibrary{calc,intersections} begin{document} begin{tikzpicture} % Axes draw [->, name path=x] (-1,0) -- (11,0) node [right] {$x$}; draw [->] (0,-1) -- (0,6) node [above] {$y$}; % Origin node at (0,0) [below left] {$0$}; % Points coordinate (start) at (1,-0.8); coordinate (c1) at (3,3); coordinate (c2) at (5.5,1.5); coordinate (c3) at (8,4); coordinate (end) at (10.5,-0.8); % show the points foreach n in {start,c1,c2,c3,end} fill [black] (n) circle (2pt) node [below] {}; % join the coordinates draw [thick,name path=curve] (start) to[out=70,in=180] (c1) to[out=0,in=180]
            閱讀完整內容

            Yusuf al-Mu'taman ibn Hud

            圖片
            Main article: Taifa of Zaragoza Al-Mu'taman Ruler of Zaragoza Reign 1081–1085 Predecessor Ahmad al-Muqtadir Successor Al-Mustain II Born Zaragoza Died 1085 Full name Yusuf ibn Ahmad al-Mu'taman ibn Hūd House Banu Hud Yusuf ibn Ahmad al-Mu'taman ibn Hūd (Arabic: المؤتمن بالله يوسف إبن أحمد إبن هود ‎, al-Mutaman bi l-Lah , died c. 1085) was the third king of the Banu Hud dynasty who ruled over the Taifa of Zaragoza from 1081 to 1085. Yusuf al-Mutaman reigned during the height of power of Muslim Zaragoza , following the thriving period of his father Ahmad al-Muqtadir. He continued his father's efforts and created around him a court of intellectuals, living in the beautiful palace of Aljafería, nicknamed as "the palace of joy". Al-Mu'taman was also a scholarly king and a patron of science, philosophy and arts. As an example of a wise king, he knew astrology, philosophy, and especially mathematics, a discipline in which
            閱讀完整內容

            Zucchini

            圖片
            This article is about the vegetable. For other uses, see Zucchini (disambiguation). Zucchini (courgette) A striped and a uniform color zucchini Genus Cucurbita Species Cucurbita pepo Origin 19th century northern Italy The zucchini ( / z uː ˈ k iː n i / , American English) or courgette ( / k ʊər ˈ ʒ ɛ t / , British English) is a summer squash which can reach nearly 1 metre (100 cm; 39 in) in length, but is usually harvested when still immature at about 15 to 25 cm (6 to 10 in). [1] A zucchini is a thin-skinned cultivar of what in Britain and Ireland is referred to as a marrow. [2] [3] In South Africa, a zucchini is known as a baby marrow. Along with certain other squashes and pumpkins, the zucchini belongs to the species Cucurbita pepo . It can be dark or light green. A related hybrid, the golden zucchini, is a deep yellow or orange color. [4] In a culinary context, the zucchini is treated as a vegetable; it is usually cooked and presented as a savory dish o
            閱讀完整內容