I want to input 3d array(custom data) to sklearn-PCA function

Question

I'm trying to input custom data(MIDI vector) into the PCA function of sklearn library.

Below is the current shape of my data.

data
[[[ 4.  56. ]    # [rhythm1 melody1] 
  [ 2.  56. ]    # [rhythm2 melody2]
  [ 2.  55. ]    # [rhythm3 melody3]
  [ 2.5 55. ]    #        ...
  [ 1.5 -1. ]    #        ...
  [ 4.  -1. ]    #        ...
  [ 4.  -1. ]    #        ...
  [ 4.  -1. ]    #        ...
  [ 4.  -1. ]    #        ...
  [ 4.  -1. ]]   # [rhythm n melody n]  
  
# next is another MIDI file's Rhythm & Melody
 [[ 4.  56. ]
  [ 2.  56. ]
  [ 2.  55. ]
  [ 2.5 55. ]
  [ 1.5 -1. ]
  [ 4.  -1. ]
  [ 4.  -1. ]
  [ 4.  -1. ]
  [ 4.  -1. ]
  [ 4.  -1. ]]]

I know that the shape of the sklearn input data is 2D array. However, I want to reduce the dimension in consideration of rhythm and melody.

Finally, I want to make my data like below.

data
[[x1    # dimension reduction about (rhythm1 & melody1)
  x2    # dimension reduction about (rhythm2 & melody2)
  x3    # dimension reduction about (rhythm3 & melody3)
  x4    #        ...
  x5    #        ...
  x6    #        ...
  x7    #        ...
  x8    #        ...
  x9    #        ...
  x10]  # dimension reduction about (rhythm10 & melody10)
  
# next is another MIDI file's Rhythm & Melody
 [y1
  y2
  y3
  y4
  y5
  y6
  y7
  y8
  y9
  y10]]

here is my code.

    def PCA_preprocessing(data, n_components=2):
        pca = PCA(n_components=n_components)  

        pca.fit(data)
        PCA_data = pca.transform(data)

        return PCA_data

    num_seq = data.shape[1]    # num_seq = 10
    PCA_data = PCA_preprocessing(data, n_components=num_seq)

Error code ValueError: Found array with dim 3. Estimator expected <= 2.

How can I solve this problem? Thank you for reading.