questions about the neural network architecture

[sim-san]

In your paper you write that you first apply a 2d convolution to X^(k) and then two 1d convolution. Finally you write that you flatten the matrix to stack the vectors of each sensor.
When I look at your code on Github, I see that you don't flatten the matrix after the individual convolution and use a 3d convolution layer .

Question:
Is there an important reason why you didn't flatten the matrix and use a 3d convolution for the matrix X^(3)?