How to stack (None,1024) tensor into (None,7,7,1024) tensor in keras?





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I have a tensor A of shape (None,1024) and I want to repeat it 49 times to make a matrix tensor of shape (None,7,7,1024). Every (,1024) vector is a copy of the tensor A.



How do I do this?



I tried



A = K.stack([A,A,A,A,A,A,A])

A = K.stack([A,A,A,A,A,A,A])


But this gives me a tensor of shape (7, 7, None, 1024)






python tensorflow keras tensor







share|improve this question





























    2















    I have a tensor A of shape (None,1024) and I want to repeat it 49 times to make a matrix tensor of shape (None,7,7,1024). Every (,1024) vector is a copy of the tensor A.



    How do I do this?



    I tried



    A = K.stack([A,A,A,A,A,A,A])
    
A = K.stack([A,A,A,A,A,A,A])


    But this gives me a tensor of shape (7, 7, None, 1024)






    python tensorflow keras tensor







    share|improve this question

























      2












      2








      2








      I have a tensor A of shape (None,1024) and I want to repeat it 49 times to make a matrix tensor of shape (None,7,7,1024). Every (,1024) vector is a copy of the tensor A.



      How do I do this?



      I tried



      A = K.stack([A,A,A,A,A,A,A])
      
A = K.stack([A,A,A,A,A,A,A])


      But this gives me a tensor of shape (7, 7, None, 1024)






      python tensorflow keras tensor







      share|improve this question














      I have a tensor A of shape (None,1024) and I want to repeat it 49 times to make a matrix tensor of shape (None,7,7,1024). Every (,1024) vector is a copy of the tensor A.



      How do I do this?



      I tried



      A = K.stack([A,A,A,A,A,A,A])
      
A = K.stack([A,A,A,A,A,A,A])


      But this gives me a tensor of shape (7, 7, None, 1024)






      python tensorflow keras tensor




      python tensorflow keras tensor






      share|improve this question













      share|improve this question











      share|improve this question




      share|improve this question










      asked Nov 16 '18 at 12:24









      Nirvan AnjirbagNirvan Anjirbag

      3901418




      3901418
























          1 Answer
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          First use RepeatVector layer to repeat it for 49 times, then use Reshape layer to reshape it as desired:



          r_A = RepeatVector(49)(A)
          
rsh_A = Reshape((7, 7, -1))(r_A)


          Alternatively, you can define a function based on backend functions and wrap it inside a Lambda layer:



          from keras import backend as K
          

          
def rsh(x):
          
    y = K.repeat(x, 49)
          
    return K.reshape(y, (-1, 7, 7, K.int_shape(y)[-1]))
          

          
rsh_A = Lambda(rsh)(A)





          share|improve this answer


























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            1 Answer
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            1 Answer
            1






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            active

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            2














            First use RepeatVector layer to repeat it for 49 times, then use Reshape layer to reshape it as desired:



            r_A = RepeatVector(49)(A)
            
rsh_A = Reshape((7, 7, -1))(r_A)


            Alternatively, you can define a function based on backend functions and wrap it inside a Lambda layer:



            from keras import backend as K
            

            
def rsh(x):
            
    y = K.repeat(x, 49)
            
    return K.reshape(y, (-1, 7, 7, K.int_shape(y)[-1]))
            

            
rsh_A = Lambda(rsh)(A)





            share|improve this answer






























              2














              First use RepeatVector layer to repeat it for 49 times, then use Reshape layer to reshape it as desired:



              r_A = RepeatVector(49)(A)
              
rsh_A = Reshape((7, 7, -1))(r_A)


              Alternatively, you can define a function based on backend functions and wrap it inside a Lambda layer:



              from keras import backend as K
              

              
def rsh(x):
              
    y = K.repeat(x, 49)
              
    return K.reshape(y, (-1, 7, 7, K.int_shape(y)[-1]))
              

              
rsh_A = Lambda(rsh)(A)





              share|improve this answer




























                2












                2








                2







                First use RepeatVector layer to repeat it for 49 times, then use Reshape layer to reshape it as desired:



                r_A = RepeatVector(49)(A)
                
rsh_A = Reshape((7, 7, -1))(r_A)


                Alternatively, you can define a function based on backend functions and wrap it inside a Lambda layer:



                from keras import backend as K
                

                
def rsh(x):
                
    y = K.repeat(x, 49)
                
    return K.reshape(y, (-1, 7, 7, K.int_shape(y)[-1]))
                

                
rsh_A = Lambda(rsh)(A)





                share|improve this answer















                First use RepeatVector layer to repeat it for 49 times, then use Reshape layer to reshape it as desired:



                r_A = RepeatVector(49)(A)
                
rsh_A = Reshape((7, 7, -1))(r_A)


                Alternatively, you can define a function based on backend functions and wrap it inside a Lambda layer:



                from keras import backend as K
                

                
def rsh(x):
                
    y = K.repeat(x, 49)
                
    return K.reshape(y, (-1, 7, 7, K.int_shape(y)[-1]))
                

                
rsh_A = Lambda(rsh)(A)






                share|improve this answer














                share|improve this answer



                share|improve this answer








                edited Nov 16 '18 at 12:57

























                answered Nov 16 '18 at 12:39









                todaytoday

                11.7k22441




                11.7k22441
































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