alt_i2v_V2.py 文件源码

def train():
  for i in range(500):
    print('now iter {} load pickled dataset...'.format(i))
    Xs = []
    ys = []
    names = [name for idx, name in enumerate( glob.glob('../dataset/*.pkl') )]
    random.shuffle( names )
    for idx, name in enumerate(names):
      try:
        X,y = pickle.loads(open(name,'rb').read() ) 
      except EOFError as e:
        continue
      if idx%100 == 0:
        print('now scan iter', idx)
      if idx >= 15000:
        break
      Xs.append( X )
      ys.append( y )

    Xs = np.array( Xs )
    ys = np.array( ys )
    model.fit(Xs, ys, epochs=1 )
    print('now iter {} '.format(i))
    model.save_weights('models/{:09d}.h5'.format(i))