def _score_for_model(meta):
mean_acc = list()<EOL>pipes = meta["<STR_LIT>"]<EOL>acc = meta["<STR_LIT>"]<EOL>if "<STR_LIT>" in pipes:<EOL><INDENT>mean_acc.append(acc["<STR_LIT>"])<EOL><DEDENT>if "<STR_LIT>" in pipes:<EOL><INDENT>mean_acc.append((acc["<STR_LIT>"] + acc["<STR_LIT>"]) / <NUM_LIT:2>)<EOL><DEDENT>if "<STR_LIT>" in pipes:<EOL><INDENT>mean_acc.append((acc["<STR_LIT>"] + acc["<STR_LIT>"] + acc["<STR_LIT>"]) / <NUM_LIT:3>)<EOL><DEDENT>return sum(mean_acc) / len(mean_acc)<EOL>
Returns mean score between tasks in pipeline that can be used for early stopping.