Why does the perceptive field formula differ from the calculation?

Describe the bug
The readme provides the following perception field calculation formula:
https://user-images.githubusercontent.com/12395799/106308730-6d4c5180-6261-11eb-82e9-a12a1958058d.png

where one sees (k[n]-1) under the sum.
However, the current code (v.3.3.1) uses k[n] in the expression (

keras-tcn/tcn/tcn.py

Line 248 in 455a035

return 1 + self.nb_stacks * sum([d * self.kernel_size for d in self.dilations])

).
I was wondering if it's a bug or I am missing something?

After all, the difference is a factor of k/(k-1), which does matter for applications. For kernel_size = 3 (default), this is 1.5 times.

Btw, there seems to be a square bracket out of place in the formula.

Paste a snippet
Irrelevant.

Dependencies
Irrelevant.

@Alexander-Serov yeah there's something wrong here. I'll try to investigate that more.

Here is the formula that works with the code. I'm going to update the code and the README.

Thanks for raising this problem! It has been merged to master: bb92425.

A new version 3.4.0 was released.

I found this formula empirically by trying a lot of combinations of different parameters. I'm pretty sure it is correct when using the TCN. But theoretically, the 2 is not justified. It seems however the 2 present in the formula might be just a problem of notation and parameterization (For example it's possible that if we want to specify dilations 1-2-4-8, we should only give to 1-2-4 to TensorFlow). One's should inspect the Conv1D code to see.

I added a note in the README. For later work.

Ref: https://stackoverflow.com/questions/63073760/using-dilated-convolution-in-keras