mindspore.Tensor.gather_nd
- Tensor.gather_nd(indices)[source]
Gathers slices from a input tensor by indices. Using given indices to gather slices from a input tensor with a specified shape. input tensor’s shape is \((N,*)\) where \(*\) means any number of additional dimensions. For convenience define it as input_x, the variable input_x refers to input tensor. indices is an K-dimensional integer tensor. Suppose that it is a (K-1)-dimensional tensor and each element of it defines a slice of input tensor:
\[output[(i_0, ..., i_{K-2})] = input\_x[indices[(i_0, ..., i_{K-2})]]\]The last dimension of indices can not more than the rank of input tensor: \(indices.shape[-1] <= input\_x.rank\).
- Parameters
indices (Tensor) – The index tensor that gets the collected elements, with int32 or int64 data type.
- Returns
Tensor, has the same type as input tensor and the shape is \(indices\_shape[:-1] + input\_x\_shape[indices\_shape[-1]:]\).
- Raises
ValueError – If length of shape of input tensor is less than the last dimension of indices.
- Supported Platforms:
Ascend
GPU
CPU
Examples
>>> input_x = Tensor(np.array([[-0.1, 0.3, 3.6], [0.4, 0.5, -3.2]]), mindspore.float32) >>> indices = Tensor(np.array([[0, 0], [1, 1]]), mindspore.int32) >>> output = input_x.gather_nd(indices) >>> print(output) [-0.1 0.5]