luckmatter/recon_multilayer.py [256:282]:
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def accumulate(all_y, y):
    if all_y is None:
        all_y = dict()
        for k, v in y.items():
            if isinstance(v, list):
                all_y[k] = [ [vv] for vv in v ]
            else:
                all_y[k] = [v]
    else:
        for k, v in all_y.items():
            if isinstance(y[k], list):
                for vv, yy in zip(v, y[k]):
                    vv.append(yy)
            else:
                v.append(y[k])

    return all_y

def combine(all_y):
    output = dict()
    for k, v in all_y.items():
        if isinstance(v[0], list):
            output[k] = [ torch.cat(vv) for vv in v ]
        else:
            output[k] = torch.cat(v)

    return output
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student_specialization/utils.py [68:94]:
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def accumulate(all_y, y):
    if all_y is None:
        all_y = dict()
        for k, v in y.items():
            if isinstance(v, list):
                all_y[k] = [ [vv] for vv in v ]
            else:
                all_y[k] = [v]
    else:
        for k, v in all_y.items():
            if isinstance(y[k], list):
                for vv, yy in zip(v, y[k]):
                    vv.append(yy)
            else:
                v.append(y[k])

    return all_y

def combine(all_y):
    output = dict()
    for k, v in all_y.items():
        if isinstance(v[0], list):
            output[k] = [ torch.cat(vv) for vv in v ]
        else:
            output[k] = torch.cat(v)

    return output
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