multiplex¶

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

Based on the given index parameter, the OP selects a specific row from each input Tensor to construct the output Tensor.

If the input of this OP contains \(m\) Tensors, where \(I_{i}\) means the i-th input Tensor, \(i\) between \([0,m)\) .

And \(O\) means the output, where \(O[i]\) means the i-th row of the output, then the output satisfies that \(O[i] = I_{index[i]}[i]\) .

For Example:

```Given:

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 = [[3],[0],[1],[2]]

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]
```
Parameters
• inputs (list) – The input Tensor list. The list elements are N-D Tensors of data types float32, float64, int32, int64. All input Tensor shapes should be the same and rank must be at least 2.

• index (Variable) – Used to select some rows in the input Tensor to construct an index of the output Tensor. It is a 2-D Tensor with data type int32 or int64 and shape [M, 1], where M is the number of input Tensors.

Returns

Output of multiplex OP, with data type being float32, float64, int32, int64.

Return type

Variable(Tensor)

Examples

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

x1 = fluid.data(name='x1', shape=[None, 2], dtype='float32')
x2 = fluid.data(name='x2', shape=[None, 2], dtype='float32')
index = fluid.data(name='index', shape=[None, 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)]
```