* Case 1:
    Given
        X = [[0, 1, 2, 0, 0]
             [0, 3, 4, 0, 0]
             [0, 0, 0, 0, 0]],
    and
        shape = [2, 2],
        offsets = [0, 1],
    output is:
        Out = [[1, 2],
               [3, 4]].
* Case 2:
    Given
        X = [[0, 1, 2, 5, 0]
             [0, 3, 4, 6, 0]
             [0, 0, 0, 0, 0]],
    and shape is tensor
        shape = [[0, 0, 0]
                 [0, 0, 0]]
    and
        offsets = [0, 1],

    output is:
        Out = [[1, 2, 5],
               [3, 4, 6]].

import paddle.fluid as fluid
# case 1
# 输入x的形状为[-1, 3, 5]，
# 参数shape = y是个Variable，形状是[-1, 2, 2]，输出Tensor将具有和y一样的形状
# y的具体数值不起作用，起作用的只有它的形状
# 经过下面的crop操作之后输出张量的形状是: [-1, 2, 2]
x = fluid.layers.data(name="x", shape=[3, 5], dtype="float32")
y = fluid.layers.data(name="y", shape=[2, 2], dtype="float32")
crop = fluid.layers.crop(x, shape=y)
## 或者 case 2
# 输入z的形状为: [-1, 3, 5], shape为整数列表[-1, 2, 3]
# 则经过下面的crop操作之后输出张量的形状为：[-1, 2, 3]
z = fluid.layers.data(name="z", shape=[3, 5], dtype="float32")
crop = fluid.layers.crop(z, shape=[-1, 2, 3])