adding metadata to tensorflow tflearn CNN










0














I built a simple CNN network for (medical) image classification successfully, using tflearn. When I tried to add metadata to the CNN, I ran into this problem:ValueError: Cannot feed value of shape (96, 2) for Tensor 'TargetsData/Y:0', which has shape '(1390, 2)'. Any help is appreciated:



#extract pictures (0 thru 4095), next two bytes for the selection, and the rest for metadata
X, Y, Z = train_data[:,0:4096],train_data[:,4096:4098], train_data[:,4098:]
X = X.reshape([-1,64,64,1])


network = input_data(shape=[None, 64, 64, 1])
mdnetwork = input_data(shape=[None, 100])
network = conv_2d(network, 30, 3, activation='relu')
network = max_pool_2d(network, 2)
network = conv_2d(network, 30, 3, activation='relu')
network = conv_2d(network, 40, 3, activation='relu')
network = max_pool_2d(network, 2)
network = conv_2d(network, 40, 3, activation='relu')
network = conv_2d(network, 40, 3, activation='relu')
network = conv_2d(network, 30, 3, activation='relu')
network = max_pool_2d(network, 2)
network = fully_connected(network, 100, activation='relu')

Zt= fully_connected(Z, 100, activation='relu')
network = merge([network,Zt], 'concat')

network = dropout(network, 0.5)
network = fully_connected(network, 50, activation='relu')
network = fully_connected(network, 2, activation='softmax')

# Train using classifier
network = regression(network, optimizer='adam',
loss='categorical_crossentropy',
learning_rate=0.001)

model = tflearn.DNN(network, tensorboard_verbose=3)

model.fit([np.array(X).reshape(-1, 64, 64, 1), np.array(Z).reshape(-1, 100)], Y, n_epoch=5, shuffle=True, validation_set=0,
show_metric=True, batch_size=96, run_id='my_cnn')

model.save('my_cnn.tflearn')









share|improve this question


























    0














    I built a simple CNN network for (medical) image classification successfully, using tflearn. When I tried to add metadata to the CNN, I ran into this problem:ValueError: Cannot feed value of shape (96, 2) for Tensor 'TargetsData/Y:0', which has shape '(1390, 2)'. Any help is appreciated:



    #extract pictures (0 thru 4095), next two bytes for the selection, and the rest for metadata
    X, Y, Z = train_data[:,0:4096],train_data[:,4096:4098], train_data[:,4098:]
    X = X.reshape([-1,64,64,1])


    network = input_data(shape=[None, 64, 64, 1])
    mdnetwork = input_data(shape=[None, 100])
    network = conv_2d(network, 30, 3, activation='relu')
    network = max_pool_2d(network, 2)
    network = conv_2d(network, 30, 3, activation='relu')
    network = conv_2d(network, 40, 3, activation='relu')
    network = max_pool_2d(network, 2)
    network = conv_2d(network, 40, 3, activation='relu')
    network = conv_2d(network, 40, 3, activation='relu')
    network = conv_2d(network, 30, 3, activation='relu')
    network = max_pool_2d(network, 2)
    network = fully_connected(network, 100, activation='relu')

    Zt= fully_connected(Z, 100, activation='relu')
    network = merge([network,Zt], 'concat')

    network = dropout(network, 0.5)
    network = fully_connected(network, 50, activation='relu')
    network = fully_connected(network, 2, activation='softmax')

    # Train using classifier
    network = regression(network, optimizer='adam',
    loss='categorical_crossentropy',
    learning_rate=0.001)

    model = tflearn.DNN(network, tensorboard_verbose=3)

    model.fit([np.array(X).reshape(-1, 64, 64, 1), np.array(Z).reshape(-1, 100)], Y, n_epoch=5, shuffle=True, validation_set=0,
    show_metric=True, batch_size=96, run_id='my_cnn')

    model.save('my_cnn.tflearn')









    share|improve this question
























      0












      0








      0







      I built a simple CNN network for (medical) image classification successfully, using tflearn. When I tried to add metadata to the CNN, I ran into this problem:ValueError: Cannot feed value of shape (96, 2) for Tensor 'TargetsData/Y:0', which has shape '(1390, 2)'. Any help is appreciated:



      #extract pictures (0 thru 4095), next two bytes for the selection, and the rest for metadata
      X, Y, Z = train_data[:,0:4096],train_data[:,4096:4098], train_data[:,4098:]
      X = X.reshape([-1,64,64,1])


      network = input_data(shape=[None, 64, 64, 1])
      mdnetwork = input_data(shape=[None, 100])
      network = conv_2d(network, 30, 3, activation='relu')
      network = max_pool_2d(network, 2)
      network = conv_2d(network, 30, 3, activation='relu')
      network = conv_2d(network, 40, 3, activation='relu')
      network = max_pool_2d(network, 2)
      network = conv_2d(network, 40, 3, activation='relu')
      network = conv_2d(network, 40, 3, activation='relu')
      network = conv_2d(network, 30, 3, activation='relu')
      network = max_pool_2d(network, 2)
      network = fully_connected(network, 100, activation='relu')

      Zt= fully_connected(Z, 100, activation='relu')
      network = merge([network,Zt], 'concat')

      network = dropout(network, 0.5)
      network = fully_connected(network, 50, activation='relu')
      network = fully_connected(network, 2, activation='softmax')

      # Train using classifier
      network = regression(network, optimizer='adam',
      loss='categorical_crossentropy',
      learning_rate=0.001)

      model = tflearn.DNN(network, tensorboard_verbose=3)

      model.fit([np.array(X).reshape(-1, 64, 64, 1), np.array(Z).reshape(-1, 100)], Y, n_epoch=5, shuffle=True, validation_set=0,
      show_metric=True, batch_size=96, run_id='my_cnn')

      model.save('my_cnn.tflearn')









      share|improve this question













      I built a simple CNN network for (medical) image classification successfully, using tflearn. When I tried to add metadata to the CNN, I ran into this problem:ValueError: Cannot feed value of shape (96, 2) for Tensor 'TargetsData/Y:0', which has shape '(1390, 2)'. Any help is appreciated:



      #extract pictures (0 thru 4095), next two bytes for the selection, and the rest for metadata
      X, Y, Z = train_data[:,0:4096],train_data[:,4096:4098], train_data[:,4098:]
      X = X.reshape([-1,64,64,1])


      network = input_data(shape=[None, 64, 64, 1])
      mdnetwork = input_data(shape=[None, 100])
      network = conv_2d(network, 30, 3, activation='relu')
      network = max_pool_2d(network, 2)
      network = conv_2d(network, 30, 3, activation='relu')
      network = conv_2d(network, 40, 3, activation='relu')
      network = max_pool_2d(network, 2)
      network = conv_2d(network, 40, 3, activation='relu')
      network = conv_2d(network, 40, 3, activation='relu')
      network = conv_2d(network, 30, 3, activation='relu')
      network = max_pool_2d(network, 2)
      network = fully_connected(network, 100, activation='relu')

      Zt= fully_connected(Z, 100, activation='relu')
      network = merge([network,Zt], 'concat')

      network = dropout(network, 0.5)
      network = fully_connected(network, 50, activation='relu')
      network = fully_connected(network, 2, activation='softmax')

      # Train using classifier
      network = regression(network, optimizer='adam',
      loss='categorical_crossentropy',
      learning_rate=0.001)

      model = tflearn.DNN(network, tensorboard_verbose=3)

      model.fit([np.array(X).reshape(-1, 64, 64, 1), np.array(Z).reshape(-1, 100)], Y, n_epoch=5, shuffle=True, validation_set=0,
      show_metric=True, batch_size=96, run_id='my_cnn')

      model.save('my_cnn.tflearn')






      tensorflow metadata conv-neural-network






      share|improve this question













      share|improve this question











      share|improve this question




      share|improve this question










      asked Nov 12 '18 at 5:54









      nkumarnkumar

      11




      11






















          1 Answer
          1






          active

          oldest

          votes


















          0














          It is good I can answer my question here! Anyway, I found the issue in my code above. It was a simple error. The error message led me astray. Here is the solution: Replace this code snippet



          Zt= fully_connected(Z, 100, activation='relu')
          network = merge([network,Zt], 'concat')


          with



          network = merge([network, mdnetwork], 'concat')


          Thanks for those who read my request. Let me know if there are other options.






          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%2f53256551%2fadding-metadata-to-tensorflow-tflearn-cnn%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














            It is good I can answer my question here! Anyway, I found the issue in my code above. It was a simple error. The error message led me astray. Here is the solution: Replace this code snippet



            Zt= fully_connected(Z, 100, activation='relu')
            network = merge([network,Zt], 'concat')


            with



            network = merge([network, mdnetwork], 'concat')


            Thanks for those who read my request. Let me know if there are other options.






            share|improve this answer

























              0














              It is good I can answer my question here! Anyway, I found the issue in my code above. It was a simple error. The error message led me astray. Here is the solution: Replace this code snippet



              Zt= fully_connected(Z, 100, activation='relu')
              network = merge([network,Zt], 'concat')


              with



              network = merge([network, mdnetwork], 'concat')


              Thanks for those who read my request. Let me know if there are other options.






              share|improve this answer























                0












                0








                0






                It is good I can answer my question here! Anyway, I found the issue in my code above. It was a simple error. The error message led me astray. Here is the solution: Replace this code snippet



                Zt= fully_connected(Z, 100, activation='relu')
                network = merge([network,Zt], 'concat')


                with



                network = merge([network, mdnetwork], 'concat')


                Thanks for those who read my request. Let me know if there are other options.






                share|improve this answer












                It is good I can answer my question here! Anyway, I found the issue in my code above. It was a simple error. The error message led me astray. Here is the solution: Replace this code snippet



                Zt= fully_connected(Z, 100, activation='relu')
                network = merge([network,Zt], 'concat')


                with



                network = merge([network, mdnetwork], 'concat')


                Thanks for those who read my request. Let me know if there are other options.







                share|improve this answer












                share|improve this answer



                share|improve this answer










                answered Nov 17 '18 at 6:52









                nkumarnkumar

                11




                11



























                    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.





                    Some of your past answers have not been well-received, and you're in danger of being blocked from answering.


                    Please pay close attention to the following guidance:


                    • 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%2f53256551%2fadding-metadata-to-tensorflow-tflearn-cnn%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

                    Use pre created SQLite database for Android project in kotlin

                    Darth Vader #20

                    Ondo