mindspore.ops.TensorScatterAdd

class mindspore.ops.TensorScatterAdd(*args, **kwargs)[source]

Creates a new tensor by adding the values from the positions in input_x indicicated by indices, with values from update. When multiple values are given for the same index, the updated result will be the sum of all values. This operation is almost equivalent to using ScatterNdAdd, except that the updates are applied on Tensor instead of Parameter.

The last axis of indices is the depth of each index vectors. For each index vector, there must be a corresponding value in update. The shape of update should be equal to the shape of input_x[indices].

Note

If some values of the indices are out of bound, instead of raising an index error, the corresponding update will not be updated to input_x.

Inputs:

  • input_x (Tensor) - The target tensor. The dimension of input_x must be no less than indices.shape[-1].

  • indices (Tensor) - The index of input tensor whose data type is int32 or int64. The rank must be at least 2.

  • update (Tensor) - The tensor to update the input tensor, has the same type as input, and update.shape should be equal to indices.shape[:-1] + input_x.shape[indices.shape[-1]:].

Outputs:

Tensor, has the same shape and type as input_x.

Raises

  • TypeError – If dtype of indices is neither int32 nor int64.

  • ValueError – If length of shape of input_x is less than the last dimension of shape of indices.

Supported Platforms:

GPU

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], [0, 0]]), mindspore.int32)
>>> update = Tensor(np.array([1.0, 2.2]), mindspore.float32)
>>> op = ops.TensorScatterAdd()
>>> output = op(input_x, indices, update)
>>> print(output)
[[ 3.1  0.3  3.6]
 [ 0.4  0.5 -3.2]]