edd70b9132cbc32f866ee3aabbb023166c3dbe32,thinc/neural/_classes/affine.py,,_alloc_mem_if_able,#Any#,19

Before Change

def _alloc_mem_if_able(model, *args, **kwargs):
    weights = [desc for (name, desc) in model.descriptions.items()
               if isinstance(desc, describe.Weights)]
    shapes = {}
    for param in weights:
        shape = tuple([getattr(model, dim, None) for dim in param.shape])

After Change

def _alloc_mem_if_able(model, *args, **kwargs):
    if model.nO is None or model.nI is None:
        return None
    else:
        model.mem = Memory(model.nO * model.nI + model.nO)
        model.W = model.mem.add(name, (model.nO, model.nI))
        model.b = model.mem.add(name, (model.nO,))


def _init_weights_if_able(model, *args, **kwargs):
    if model.mem:
        for name, desc in model.description.items():
            if isinstance(desc, Weights):

Instances