segment_mean¶

paddle.incubate. segment_mean ( data, segment_ids, name=None ) [source]

Warning

API “paddle.incubate.tensor.math.segment_mean” is deprecated since 2.4.0, and will be removed in future versions. Please use “paddle.geometric.segment_mean” instead. Reason: paddle.incubate.segment_mean will be removed in future

Segment Mean Operator.

Ihis operator calculate the mean value of input data which with the same index in segment_ids. It computes a tensor such that

\[out_i = \mathop{mean}_{j \in \{segment\_ids_j == i \} } data_{j}\]

where sum is over j such that ‘segment_ids[j] == i’ and $n_i$ is the number of all index ‘segment_ids[j] == i’.

Parameters

data (tensor) – a tensor, available data type float32, float64, int32, int64.
segment_ids (tensor) – a 1-d tensor, which have the same size with the first dimension of input data. available data type is int32, int64.
name (str, optional) – Name for the operation (optional, default is None). For more information, please refer to Name.

Returns

Tensor, the Segment Mean result.

Examples

           >>> import paddle
>>> data = paddle.to_tensor([[1, 2, 3], [3, 2, 1], [4, 5, 6]], dtype='float32')
>>> segment_ids = paddle.to_tensor([0, 0, 1], dtype='int32')
>>> out = paddle.incubate.segment_mean(data, segment_ids)
>>> print(out)
Tensor(shape=[2, 3], dtype=float32, place=Place(cpu), stop_gradient=True,
[[2., 2., 2.],
 [4., 5., 6.]])

          