multiplex

paddle. multiplex ( inputs: Sequence[Tensor], index: Tensor, name: str | None = None ) → Tensor [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[Tensor]|tuple[Tensor, ...]) – The input Tensor list. The list elements are N-D Tensors of data types float32, float64, int32, int64, complex64, complex128. All input Tensor shapes should be the same and rank must be at least 2.
index (Tensor) – 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.
name (str|None, optional) – Name for the operation (optional, default is None). For more information, please refer to api_guide_Name.

Returns

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

Return type

Tensor

Examples

           >>> import paddle

>>> img1 = paddle.to_tensor([[1, 2], [3, 4]], dtype=paddle.float32)
>>> img2 = paddle.to_tensor([[5, 6], [7, 8]], dtype=paddle.float32)
>>> inputs = [img1, img2]
>>> index = paddle.to_tensor([[1], [0]], dtype=paddle.int32)
>>> res = paddle.multiplex(inputs, index)
>>> print(res)
Tensor(shape=[2, 2], dtype=float32, place=Place(cpu), stop_gradient=True,
[[5., 6.],
 [3., 4.]])

          