conv1d.py 文件源码

def test_kmax_pool():
  nbatches, nkernels_in, nwords, ndim = 2, 1, 5, 3
  input_shape = (nbatches, nkernels_in, nwords, ndim)

  input = T.tensor4('input')

  k = 3
  f_kmax = theano.function([input], k_max_pooling(input, k))
  f_max = theano.function([input], max_pooling(input))

  image_data = np.arange(np.prod(input_shape), dtype=np.float64)
  np.random.shuffle(image_data)
  image_data = image_data.reshape(input_shape)
  print image_data
  print 'kmax'
  print f_kmax(image_data)
  print 'max'
  print f_max(image_data)