annotation coordinates do not respect log scaling

When adding annotations to a plot that uses log scaling, the annotation coordinates need to be rescaled to represent the log10 of the actual coordinates. While this is documented behavior, it is rather counterintuitive and should be fixed.
Seemingly no other axis-types (date, for instance) needs special treatment but works without modifying the underlying data.

Minimum example demonstrating the point, i.e. label_y is 4 but plotted at 10^4:

df = pd.DataFrame(data={'x':[1,2,3,4],
                        'y':[1,4,9,16],
                        })

fig = px.line(df,
              x='x',
              y='y',
              log_y=True,
              log_x=True,
              )

annotations = []
fig.for_each_trace(
    lambda trace: annotations.append(dict(x=np.log10(np.sqrt(trace.x[0]*trace.x[-1])),
                                          y=np.sqrt(trace.y[0]*trace.y[-1]),
                                          text=f'({np.sqrt(trace.x[0]*trace.x[-1])},{np.sqrt(trace.y[0]*trace.y[-1])})',))
)

fig.update_layout(annotations=annotations,
                  width=300,
                  height=300,
                  )
fig.show()

No source file or test is named. Start by reproducing the minimal example with log-scaled x and y axes, then trace how annotations and axis coordinates are handled; done means annotations accept actual data coordinates on log axes while date and other axis types continue to work without changing the underlying data.