  We investigate the implications on the dark matter (DM) signal from the
AMS-02 cosmic antiproton flux. Global fits to the data are performed under
different propagation and hadronic interaction models. The uncertainties from
the injection spectrum, propagation effects and solar modulation of the cosmic
rays are taken into account comprehensively. Since we need to investigate
extended parameter regions with multiple free parameters in the fit, the
machine learning method is adopted to maintain a realistic time cost. We find
all the effects considered in the fitting process interplay with each other,
among which the hadronic interaction model is the most important factor
affecting the result. In most hadronic interaction and CR propagation models no
DM signal is found with significance larger than $2\sigma$ except that the
EPOS-LHC interaction model requires a more than $3\sigma$ DM signal with DM
mass around $1\,\mathrm{TeV}$. For the diffusive reacceleration propagation
model there is a highly significant DM signal with mass around
$100\,\mathrm{GeV}$. However, the signal becomes less than $1\sigma$ if we take
a charge dependent solar modulation potential in the analysis.
