Tensorflow matmul how to deal with channel=None











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I am trying to do matmul of two tensors, one is [None, 4, 256], and the other is its transpose (I use tf.transpose and got a tensor [256, 4, None]). The expected result is a [4, 4] tensor. When I use matmul, it returns an error. I am wondering, how can I get the expected result? Thank you!



#inputs: [None, 4, 256]
inputs_transpose = tf.transpose(inputs, perm = [0, 2, 1]) #[None, 256, 4]
temp_weights = tf.matmul(inputs, inputs_transpose) #[4, 4]expected









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    I am trying to do matmul of two tensors, one is [None, 4, 256], and the other is its transpose (I use tf.transpose and got a tensor [256, 4, None]). The expected result is a [4, 4] tensor. When I use matmul, it returns an error. I am wondering, how can I get the expected result? Thank you!



    #inputs: [None, 4, 256]
    inputs_transpose = tf.transpose(inputs, perm = [0, 2, 1]) #[None, 256, 4]
    temp_weights = tf.matmul(inputs, inputs_transpose) #[4, 4]expected









    share|improve this question


























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      down vote

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      up vote
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      down vote

      favorite











      I am trying to do matmul of two tensors, one is [None, 4, 256], and the other is its transpose (I use tf.transpose and got a tensor [256, 4, None]). The expected result is a [4, 4] tensor. When I use matmul, it returns an error. I am wondering, how can I get the expected result? Thank you!



      #inputs: [None, 4, 256]
      inputs_transpose = tf.transpose(inputs, perm = [0, 2, 1]) #[None, 256, 4]
      temp_weights = tf.matmul(inputs, inputs_transpose) #[4, 4]expected









      share|improve this question















      I am trying to do matmul of two tensors, one is [None, 4, 256], and the other is its transpose (I use tf.transpose and got a tensor [256, 4, None]). The expected result is a [4, 4] tensor. When I use matmul, it returns an error. I am wondering, how can I get the expected result? Thank you!



      #inputs: [None, 4, 256]
      inputs_transpose = tf.transpose(inputs, perm = [0, 2, 1]) #[None, 256, 4]
      temp_weights = tf.matmul(inputs, inputs_transpose) #[4, 4]expected






      python tensorflow matrix-multiplication tensor






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      edited Nov 10 at 9:45

























      asked Nov 10 at 9:25









      Cindy

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          From Tensowflow docs



          "Note: This function diverges from default Numpy behavior for float and string types when None is present in a Python list or scalar. Rather than silently converting None values, an error will be thrown."



          Tensowflow does not accept None values while creating tensors.
          I tried to recreate the setup you had on my system and got this error message:



          TypeError: Failed to convert object of type <class 'list'> to Tensor. Contents: [None, 4, 256]. Consider casting elements to a supported type.


          You would need to explicitly handle the None by replacing it with a 0 before attempting to use the python list.






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            up vote
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            From Tensowflow docs



            "Note: This function diverges from default Numpy behavior for float and string types when None is present in a Python list or scalar. Rather than silently converting None values, an error will be thrown."



            Tensowflow does not accept None values while creating tensors.
            I tried to recreate the setup you had on my system and got this error message:



            TypeError: Failed to convert object of type <class 'list'> to Tensor. Contents: [None, 4, 256]. Consider casting elements to a supported type.


            You would need to explicitly handle the None by replacing it with a 0 before attempting to use the python list.






            share|improve this answer

























              up vote
              0
              down vote













              From Tensowflow docs



              "Note: This function diverges from default Numpy behavior for float and string types when None is present in a Python list or scalar. Rather than silently converting None values, an error will be thrown."



              Tensowflow does not accept None values while creating tensors.
              I tried to recreate the setup you had on my system and got this error message:



              TypeError: Failed to convert object of type <class 'list'> to Tensor. Contents: [None, 4, 256]. Consider casting elements to a supported type.


              You would need to explicitly handle the None by replacing it with a 0 before attempting to use the python list.






              share|improve this answer























                up vote
                0
                down vote










                up vote
                0
                down vote









                From Tensowflow docs



                "Note: This function diverges from default Numpy behavior for float and string types when None is present in a Python list or scalar. Rather than silently converting None values, an error will be thrown."



                Tensowflow does not accept None values while creating tensors.
                I tried to recreate the setup you had on my system and got this error message:



                TypeError: Failed to convert object of type <class 'list'> to Tensor. Contents: [None, 4, 256]. Consider casting elements to a supported type.


                You would need to explicitly handle the None by replacing it with a 0 before attempting to use the python list.






                share|improve this answer












                From Tensowflow docs



                "Note: This function diverges from default Numpy behavior for float and string types when None is present in a Python list or scalar. Rather than silently converting None values, an error will be thrown."



                Tensowflow does not accept None values while creating tensors.
                I tried to recreate the setup you had on my system and got this error message:



                TypeError: Failed to convert object of type <class 'list'> to Tensor. Contents: [None, 4, 256]. Consider casting elements to a supported type.


                You would need to explicitly handle the None by replacing it with a 0 before attempting to use the python list.







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                answered Nov 10 at 10:42









                Paritosh Singh

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