mindspore.ops.GatherD
- class mindspore.ops.GatherD[source]
Gathers values along an axis specified by dim.
For a 3-D tensor, the output is:
output[i][j][k] = x[index[i][j][k]][j][k] # if dim == 0 output[i][j][k] = x[i][index[i][j][k]][k] # if dim == 1 output[i][j][k] = x[i][j][index[i][j][k]] # if dim == 2
If x is an n-D tensor with shape \((z_0, z_1, ..., z_i, ..., z_{n-1})\) and dim = i, the index must be an n-D tensor with shape \((z_0, z_1, ..., y, ..., z_{n-1})\) where y>=1 and the output will have the same shape as index.
- Inputs:
x (Tensor) - The source tensor. The shape is \((N,*)\) where \(*\) means,any number of additional dimensions.
dim (int) - The axis along which to index. It must be int32 or int64. Only constant value is allowed.
index (Tensor) - The indices of elements to gather. It can be one of the following data types: int32, int64. The value range of each index element is [-x_rank[dim], x_rank[dim]).
- Outputs:
Tensor, the shape of tensor is \((z_1, z_2, ..., z_N)\), has the same data type with x.
- Raises
TypeError – If dtype of dim or index is neither int32 nor int64.
ValueError – If length of shape of x is not equal to length of shape of index.
- Supported Platforms:
Ascend
GPU
CPU
Examples
>>> x = Tensor(np.array([[1, 2], [3, 4]]), mindspore.int32) >>> index = Tensor(np.array([[0, 0], [1, 0]]), mindspore.int32) >>> dim = 1 >>> output = ops.GatherD()(x, dim, index) >>> print(output) [[1 1] [4 3]]