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If numba is installed, we should @jit(nopython=True, fastmath=True) compile the model when we lambdify them. This should of course be optional. If numba is not installed everything should work out of the box, and if it is installed everything should work faster. In addition, there should be a flag/option somewhere to never jit the models, just in case there's issues. Finally, the arguments to the jit function should be user-providable.
The text was updated successfully, but these errors were encountered:
I agree, this would be awesome. In principle the code we generate with sympy uses numpy, and thus should be compatible in most typical cases. I would propose to add a numba argument to either fit itself, or Fit.execute, which could be a boolean, or a dict of options which is passed to numba.njit.
If numba is installed, we should
@jit(nopython=True, fastmath=True)
compile the model when we lambdify them. This should of course be optional. If numba is not installed everything should work out of the box, and if it is installed everything should work faster. In addition, there should be a flag/option somewhere to never jit the models, just in case there's issues. Finally, the arguments to the jit function should be user-providable.The text was updated successfully, but these errors were encountered: