8f8fbb9f6543a4ccaad53923d33647e7138d95ea,encoding/parallel.py,ModelDataParallel,__init__,#ModelDataParallel#Any#Any#Any#,50

Before Change

    def __init__(self, module, device_ids=None, dim=0):
        super(ModelDataParallel, self).__init__()
        if device_ids is None:
            device_ids = list(range(torch.cuda.device_count()))
        self.dim = dim
        self.module = module
        self.device_ids = device_ids
        self.master_mean, self.master_var = {}, {}

After Change

        return obj

    if isinstance(obj, list) or isinstance(obj, tuple):
        results = map(get_a_var, obj)
        for result in results:
            if isinstance(result, Variable):
                return result
    if isinstance(obj, dict):
        results = map(get_a_var, obj.items())
        for result in results:
            if isinstance(result, Variable):
                return result
    return None


def my_parallel_apply(modules, inputs, kwargs_tup=None):
    assert len(modules) == len(inputs)
    if kwargs_tup:
        assert len(modules) == len(kwargs_tup)
    else:

Instances