implementing conv2d in fourier domain using np.einsum --> ValueError: einstein sum subscripts string contains too many subscripts for operand 0 The Next CEO of Stack Overflow2019 Community Moderator ElectionValueError: Input contains NaN, infinity or a value too large for dtype('float32')Approaches for implementing Domain specific Question answering SystemValueError: Input contains NaN, infinity or a value too large for dtype('float64')Text representation using TFIDF .toarray() freezes my computer. Too many features to handle?Converting video into frames using openCVHow can I solve it? : <ValueError: Input contains NaN, infinity or a value too large for dtype('float64').>Keras/TF: Making sure image training data shape is accurate for Time Distributed CNN+LSTMFeature selection using a filter for multiclass problem: What if many features are strongly predictive of few classes?

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implementing conv2d in fourier domain using np.einsum --> ValueError: einstein sum subscripts string contains too many subscripts for operand 0



The Next CEO of Stack Overflow
2019 Community Moderator ElectionValueError: Input contains NaN, infinity or a value too large for dtype('float32')Approaches for implementing Domain specific Question answering SystemValueError: Input contains NaN, infinity or a value too large for dtype('float64')Text representation using TFIDF .toarray() freezes my computer. Too many features to handle?Converting video into frames using openCVHow can I solve it? : <ValueError: Input contains NaN, infinity or a value too large for dtype('float64').>Keras/TF: Making sure image training data shape is accurate for Time Distributed CNN+LSTMFeature selection using a filter for multiclass problem: What if many features are strongly predictive of few classes?










0












$begingroup$


According to the convolution theorem, convolution operation changes to pointwise multiplication in fourier domain - here I have 'fft_x' of shape (batchsize, height, width, in_channels) which is the fft of input data and similarly 'fft_kernel' of shape (height, width, in_channels, out_channels) which is fft of the kernel after being padded to image size. To get pointwise multiplication of these in efficient way, I was using einsum in the following way -



...
print(fft_x)
print(fft_kernel)
output = 0
n=int(self.no_of_kernels/2)+1 # n = out_channels here
for i in range(n):
output += np.einsum('ijkl,jkl->ijk', fft_x, fft_kernel[i])
return output
...


It gives the following output and error-



Tensor("input_11:0", shape=(?, 28, 28, 1), dtype=complex64)
Tensor("fourier__conv2d_11/transpose:0", shape=(28, 28, 1, 17), dtype=complex64)
...
...
ValueError: einstein sum subscripts string contains too many subscripts for operand 0


Could anyone please explain why this error is arising? Thanks in advance for any help.










share|improve this question









$endgroup$
















    0












    $begingroup$


    According to the convolution theorem, convolution operation changes to pointwise multiplication in fourier domain - here I have 'fft_x' of shape (batchsize, height, width, in_channels) which is the fft of input data and similarly 'fft_kernel' of shape (height, width, in_channels, out_channels) which is fft of the kernel after being padded to image size. To get pointwise multiplication of these in efficient way, I was using einsum in the following way -



    ...
    print(fft_x)
    print(fft_kernel)
    output = 0
    n=int(self.no_of_kernels/2)+1 # n = out_channels here
    for i in range(n):
    output += np.einsum('ijkl,jkl->ijk', fft_x, fft_kernel[i])
    return output
    ...


    It gives the following output and error-



    Tensor("input_11:0", shape=(?, 28, 28, 1), dtype=complex64)
    Tensor("fourier__conv2d_11/transpose:0", shape=(28, 28, 1, 17), dtype=complex64)
    ...
    ...
    ValueError: einstein sum subscripts string contains too many subscripts for operand 0


    Could anyone please explain why this error is arising? Thanks in advance for any help.










    share|improve this question









    $endgroup$














      0












      0








      0





      $begingroup$


      According to the convolution theorem, convolution operation changes to pointwise multiplication in fourier domain - here I have 'fft_x' of shape (batchsize, height, width, in_channels) which is the fft of input data and similarly 'fft_kernel' of shape (height, width, in_channels, out_channels) which is fft of the kernel after being padded to image size. To get pointwise multiplication of these in efficient way, I was using einsum in the following way -



      ...
      print(fft_x)
      print(fft_kernel)
      output = 0
      n=int(self.no_of_kernels/2)+1 # n = out_channels here
      for i in range(n):
      output += np.einsum('ijkl,jkl->ijk', fft_x, fft_kernel[i])
      return output
      ...


      It gives the following output and error-



      Tensor("input_11:0", shape=(?, 28, 28, 1), dtype=complex64)
      Tensor("fourier__conv2d_11/transpose:0", shape=(28, 28, 1, 17), dtype=complex64)
      ...
      ...
      ValueError: einstein sum subscripts string contains too many subscripts for operand 0


      Could anyone please explain why this error is arising? Thanks in advance for any help.










      share|improve this question









      $endgroup$




      According to the convolution theorem, convolution operation changes to pointwise multiplication in fourier domain - here I have 'fft_x' of shape (batchsize, height, width, in_channels) which is the fft of input data and similarly 'fft_kernel' of shape (height, width, in_channels, out_channels) which is fft of the kernel after being padded to image size. To get pointwise multiplication of these in efficient way, I was using einsum in the following way -



      ...
      print(fft_x)
      print(fft_kernel)
      output = 0
      n=int(self.no_of_kernels/2)+1 # n = out_channels here
      for i in range(n):
      output += np.einsum('ijkl,jkl->ijk', fft_x, fft_kernel[i])
      return output
      ...


      It gives the following output and error-



      Tensor("input_11:0", shape=(?, 28, 28, 1), dtype=complex64)
      Tensor("fourier__conv2d_11/transpose:0", shape=(28, 28, 1, 17), dtype=complex64)
      ...
      ...
      ValueError: einstein sum subscripts string contains too many subscripts for operand 0


      Could anyone please explain why this error is arising? Thanks in advance for any help.







      python tensorflow numpy






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