My deep learning architecture accept input vector with size 512 and output vector with size 512 too.

The problem is I have X_data version that pairing with same y_data.

I have this tensors:

(4, 8, 512) -> (batch_size, number of X_data version, input size to model architecture) (list of X_data)

(4, 512) -> (batch_size, output size to model architecture) (y_data)

This means:

X_data[0,0,:] is pairing with y_data[0,:]
X_data[0,1,:] is pairing with y_data[0,:]
...
X_data[0,7,:] is pairing with y_data[0,:]
X_data[1,0,:] is pairing with y_data[1,:]
X_data[1,1,:] is pairing with y_data[1,:]
...
X_data[1,7,:] is pairing with y_data[1,:]

What is the final tensors shape of X_data and y_data so that I can train the model?