Train using predefined weights in Python

[LordSputnik]

Is there a particular reason why it isn't possible at the moment to use the Solver in Python to start from a pretrained network? As far as I can tell (and I don't have much experience with caffe, so I may be completely wrong), it would just be a case of creating a new constructor:

PySGDSolver::PySGDSolver(const string& param_file, const string& pretrained_param_file) {
    // as in PyNet, (as a convenience, not a guarantee), create a Python
    // exception if param_file can't be opened
    CheckFile(param_file);
    solver_.reset(new SGDSolver<float>(param_file));
    // we need to explicitly store the net wrapper, rather than constructing
    // it on the fly, so that it can hold references to Python objects
    net_.reset(new PyNet(solver_->net()));

    solver_->net()->CopyTrainedLayersFrom(pretrained_param_file);
}

[shelhamer]

You can fine-tune from Python:

solver = caffe.SGDSolver('solver.prototxt')
solver.net.copy_from('pretrained_param_file')
[...]

See #1703 for the next version of the Python interface, where you could suggest the convenience constructor for fine-tuning.