CNNs would require the input data in another shape (e.g. nn.Conv2d would expect an input in the shape [batch_size, channels, height, width]). I’m unsure what kind of data set you are using, but you could provide the input in the expected shape and use a CNN as an alternative to the proposed model.
Note that CNNs apply their filters to the input and convolve (or cross-correlate) them. This is often beneficial, if your input data has a spatial pattern (such as images), but you could of course try this approach on any kind of data and report your findings.