baselines/common/mpi_util.py
def mpi_weighted_mean(comm, local_name2valcount):
    """
    Perform a weighted average over dicts that are each on a different node
    Input: local_name2valcount: dict mapping key -> (value, count)
    Returns: key -> mean
    """
    all_name2valcount = comm.gather(local_name2valcount)
    if comm.rank == 0:
        name2sum = defaultdict(float)
        name2count = defaultdict(float)
        for n2vc in all_name2valcount:
            for (name, (val, count)) in n2vc.items():
                try:
                    val = float(val)
                except ValueError:
                    if comm.rank == 0:
                        warnings.warn('WARNING: tried to compute mean on non-float {}={}'.format(name, val))
                else:
                    name2sum[name] += val * count
                    name2count[name] += count
        return {name : name2sum[name] / name2count[name] for name in name2sum}
    else:
        return {}
def mpi_weighted_mean(comm, local_name2valcount):
    """
    Perform a weighted average over dicts that are each on a different node
    Input: local_name2valcount: dict mapping key -> (value, count)
    Returns: key -> mean
    """
    all_name2valcount = comm.gather(local_name2valcount)
    if comm.rank == 0:
        name2sum = defaultdict(float)
        name2count = defaultdict(float)
        for n2vc in all_name2valcount:
            for (name, (val, count)) in n2vc.items():
                try:
                    val = float(val)
                except ValueError:
                    if comm.rank == 0:
                        warnings.warn('WARNING: tried to compute mean on non-float {}={}'.format(name, val))
                else:
                    name2sum[name] += val * count
                    name2count[name] += count
        return {name : name2sum[name] / name2count[name] for name in name2sum}
    else:
        return {}
def mpi_weighted_mean ( comm , local_name2valcount ) : all_name2valcount = comm . gather ( local_name2valcount ) if comm . rank == 0 : name2sum = defaultdict ( float ) name2count = defaultdict ( float ) for n2vc in all_name2valcount : for ( name , ( val , count ) ) in n2vc . items ( ) : try : val = float ( val ) except ValueError : if comm . rank == 0 : warnings . warn ( 'WARNING: tried to compute mean on non-float {}={}' . format ( name , val ) ) else : name2sum [ name ] += val * count name2count [ name ] += count return { name : name2sum [ name ] / name2count [ name ] for name in name2sum } else : return { }
Perform a weighted average over dicts that are each on a different node
    Input: local_name2valcount: dict mapping key -> (value, count)
    Returns: key -> mean
Perform a weighted average over dicts that are each on a different node Input : local_name2valcount : dict mapping key - > ( value count ) Returns : key - > mean