关于Theano中扁平化功能的澄清

Question

在[ http://deeplearning.net/tutorial/lenet.html#lenet]中它说:

This will generate a matrix of shape (batch_size, nkerns[1] * 4 * 4),
# or (500, 50 * 4 * 4) = (500, 800) with the default values.
layer2_input = layer1.output.flatten(2)

当我在numpy 3d数组上使用flatten函数时,我得到一维数组.但在这里它说我得到一个矩阵.flatten(2)如何在theano中运作？

numpy上的类似示例生成一维数组:

     a= array([[[ 1,  2,  3],
    [ 4,  5,  6],
    [ 7,  8,  9]],

   [[10, 11, 12],
    [13, 14, 15],
    [16, 17, 18]],

   [[19, 20, 21],
    [22, 23, 24],
    [25, 26, 27]]])

   a.flatten(2)=array([ 1, 10, 19,  4, 13, 22,  7, 16, 25,  2, 11, 20,  5, 14, 23,  8, 17,
   26,  3, 12, 21,  6, 15, 24,  9, 18, 27])

Answer 1

numpy不支持只展平一些尺寸,但Theano确实如此.

所以如果a是一个numpy数组,a.flatten(2)没有任何意义.它运行没有错误,但只是因为2它作为order参数传递,似乎导致numpy坚持默认顺序C.

Theano flatten 确实支持轴规格.文档解释了它的工作原理.

Parameters:
    x (any TensorVariable (or compatible)) – variable to be flattened
    outdim (int) – the number of dimensions in the returned variable

Return type:
    variable with same dtype as x and outdim dimensions

Returns:
    variable with the same shape as x in the leading outdim-1 dimensions,
    but with all remaining dimensions of x collapsed into the last dimension.

例如,如果我们用展平(x,outdim = 2)展平形状(2,3,4,5)的张量,那么我们将具有相同的(2-1 = 1)前导尺寸(2,),其余尺寸已折叠.因此,此示例中的输出将具有形状(2,60).

一个简单的Theano演示:

import numpy
import theano
import theano.tensor as tt


def compile():
    x = tt.tensor3()
    return theano.function([x], x.flatten(2))


def main():
    a = numpy.arange(2 * 3 * 4).reshape((2, 3, 4))
    f = compile()
    print a.shape, f(a).shape


main()

版画

(2L, 3L, 4L) (2L, 12L)