This change was mainly about moving from storing wavelets as
functions to functors. Now wavelets can have extra parameters.
This introduced a challenge of making the CUDA kernel accept
these functors so templates were used.
A helper utility was also introduced on operator side. RunForName function
translates wavelet names and runs the right DALI kernel.

Discrete wavelets have been discarded since we're currently focusing
on continuous wavelet transform.

Computation of wavelet input samples has been moved to a separate cuda
kernel which should give a speedup when computing wavelets for multiple
a and b parameters.

Input wavelet samples, their scaled values and b coefficient are stored in
shared memory instead of global memory which should speedup computation.