text: import matplotlib.pyplot as plt
  import numpy as np
  
  
  
  def plot(ac):
    ac=np.array(ac)
    ac=ac.reshape((28,28))
    ac=[[int(ac2+0.48) for ac2 in ac1] for ac1 in ac]
  
  
    plt.imshow(ac)
  
  f=np.load("model.npz",allow_pickle=True)
  f2=np.load("model2.npz",allow_pickle=True)
  f3=np.load("model3.npz",allow_pickle=True)
  f4=np.load("model4.npz",allow_pickle=True)
  f5=np.load("model5.npz",allow_pickle=True)
  
  model=f["model"]
  print("exp model1")
  model2=f2["model"]
  print("exp model2")
  model3=f3["model"]
  print("exp model3")
  model4=f4["model"]
  print("exp model4")
  model5=f5["model"]
  print("exp model5")
  
  models=[model,model2,model3,model4,model5]
  t=f["t"]
  t0=np.mean(t[np.where(t<0.5)])
  t1=np.mean(t[np.where(t>0.5)])
  
  def runmodel(inp,model):
    x=inp
    for l in model:
      x=np.dot(x,l)
      x=np.maximum(x,0)
    x=np.mean(x,axis=-1)
    return x
  
  def lossbybool(inp):
    """input either 0 or 1"""
    dt=t1-t0
    inp/=dt
    inp+=t0
    ret=(runmodel(inp,models[0])-m7[0])**2
    for zw,mea in zip(models[1:],m7):
      ret+=(runmodel(inp,models[0])-mea)**2
    return ret/len(m7)
  
  m7=[np.mean(runmodel(t,m)) for m in models]
  
  
  print("done loading")
  
  