| """Resident linear cue-memory head; all fitting uses labeled support only.""" |
| import numpy as np |
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|
| def fresh_weights(dimension): |
| return np.zeros((int(dimension),2),dtype=np.float64) |
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| def predict(features,weights): |
| return np.argmax(np.asarray(features)@weights,axis=1) |
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| def fit_readout(features,labels,initial,method='gradient',steps=24,rate=.5,ridge=.1): |
| x=np.asarray(features,dtype=np.float64); y=np.eye(2)[np.asarray(labels,dtype=int)] |
| w=np.array(initial,dtype=np.float64,copy=True) |
| if x.ndim!=2 or len(x)!=len(y) or w.shape!=(x.shape[1],2): raise ValueError('readout shape mismatch') |
| if not np.isfinite(x).all(): raise ValueError('nonfinite features') |
| if method=='ridge': |
| |
| return x.T@np.linalg.solve(x@x.T+float(ridge)*np.eye(len(x)),y) |
| if method=='direct': |
| |
| return (x.T@(2*y-1))/max(1,len(x)) |
| if method!='gradient': raise ValueError('unknown operator') |
| for _ in range(int(steps)): |
| logits=x@w; logits-=logits.max(axis=1,keepdims=True) |
| p=np.exp(logits); p/=p.sum(axis=1,keepdims=True) |
| w-=float(rate)*x.T@(p-y)/len(x) |
| return w |
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|
| def adapt(features,labels,policy,control='intact',initial=None): |
| x=lesion(np.asarray(features,dtype=np.float64),control) |
| |
| order=np.arange(len(x)) |
| if policy.probe=='reverse': order=order[::-1] |
| elif policy.probe=='balanced': order=np.argsort(labels,kind='stable') |
| chosen=order[:max(2,int(len(x)*policy.support_fraction))] |
| xx=x[chosen]; yy=np.asarray(labels)[chosen] |
| xx=np.tile(xx,(policy.replay,1)); yy=np.tile(yy,policy.replay) |
| weights=fit_readout(xx,yy,fresh_weights(x.shape[1]) if initial is None else initial,policy.operator,policy.steps,policy.rate,policy.ridge) |
| return weights,{'support_examples':len(chosen),'replayed_examples':len(xx),'update_steps':policy.steps if policy.operator=='gradient' else 1,'changed_parameters':int(np.count_nonzero(weights))} |
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| def lesion(features,control): |
| x=np.array(features,copy=True) |
| slices={'graph_off':(0,32),'donor_off':(32,48),'memory_off':(48,56)} |
| if control in slices: |
| lo,hi=slices[control] |
| for offset in range(0,x.shape[1]-1,64): x[:,offset+lo:offset+hi]=0 |
| elif control!='intact': raise ValueError('unknown control') |
| return x |
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|
