def _run_trainer(caffe_home, log_path, output_log_file, solver, input_weight_file, note):
    print("\tRunning trainer...")
    with open(output_log_file, "w") as f:
        process = subprocess.Popen([caffe_home + "/build/tools/caffe", "train",
            "--solver=" + solver, "--weights=" + input_weight_file],
            stdout=subprocess.PIPE, stderr=subprocess.STDOUT)

        if note != None:
            sys.stdout.write("Details for this training run: {}\n".format(note))

        for line in iter(process.stdout.readline, ''):
            sys.stdout.write(line)
            f.write(line)

        print("\t\tTraining output saved to %s" % output_log_file)
Runs Caffe to train the model.
dataset/ETHPy150Open BradNeuberg/cloudless/src/cloudless/train/train.py/_run_trainer