# multiplex¶

`paddle.fluid.layers.``multiplex`(inputs, index)[源代码]

```# 输入为4个shape为[4,4]的Tensor
inputs = [[[0,0,3,4], [0,1,3,4], [0,2,4,4], [0,3,3,4]],
[[1,0,3,4], [1,1,7,8], [1,2,4,2], [1,3,3,4]],
[[2,0,3,4], [2,1,7,8], [2,2,4,2], [2,3,3,4]],
[[3,0,3,4], [3,1,7,8], [3,2,4,2], [3,3,3,4]]]

# index为shape为[4,1]的Tensor
index = [[3],[0],[1],[2]]

# 输出shape为[4,4]
out = [[3,0,3,4]    // out[0] = inputs[index[0]][0] = inputs[3][0] = [3,0,3,4]
[0,1,3,4]    // out[1] = inputs[index[1]][1] = inputs[0][1] = [0,1,3,4]
[1,2,4,2]    // out[2] = inputs[index[2]][2] = inputs[1][2] = [1,2,4,2]
[2,3,3,4]]   // out[3] = inputs[index[3]][3] = inputs[2][3] = [2,3,3,4]
```

## 参数¶

• inputs （list） - 为输入Tensor列表，列表元素为数据类型为float32，float64，int32，int64的多维Tensor。所有输入Tensor的shape应相同，秩必须至少为2。
• index （Variable）- 用来选择输入Tensor中的某些行构建输出Tensor的索引，为数据类型为int32或int64、shape为[M, 1]的2-D Tensor，其中M为输入Tensor个数。

## 返回类型¶

Variable(Tensor)。

## 代码示例¶

```import paddle.fluid as fluid
import numpy as np

x1 = fluid.layers.data(name='x1', shape=[4], dtype='float32')
x2 = fluid.layers.data(name='x2', shape=[4], dtype='float32')
index = fluid.layers.data(name='index', shape=[1], dtype='int32')
out = fluid.layers.multiplex(inputs=[x1, x2], index=index)

exe = fluid.Executor(fluid.CPUPlace())
exe.run(fluid.default_startup_program())

img1 = np.array([[1, 2], [3, 4]]).astype(np.float32)
img2 = np.array([[5, 6], [7, 8]]).astype(np.float32)
index = np.array([[1], [0]]).astype(np.int32)

res = exe.run(fluid.default_main_program(), feed={'x1':img1, 'x2':img2, 'index':index}, fetch_list=[out])
print(res) # [array([[5., 6.], [3., 4.]], dtype=float32)]
```