mindspore.ops.ScatterNdDiv

class mindspore.ops.ScatterNdDiv(use_locking=False)[source]

mindspore.ops.ScatterNdDiv is deprecated from version 2.10.0 and will be removed in a future version.

Applies sparse division to individual values or slices in a tensor.

Using given values to update tensor value through the division operation, along with the input indices. This operation outputs the input_x after the update is done, which makes it convenient to use the updated value.

Refer to mindspore.ops.scatter_nd_div() for more details.

Parameters:: use_locking (bool, optional) – Whether to protect the assignment by a lock. Default: False .

Inputs:

input_x (Union[Parameter, Tensor]) - The target tensor, with data type of Parameter or Tensor.
indices (Tensor) - The index to do div operation whose data type must be int32 or int64. The rank of indices must be at least 2 and indices.shape[-1] <= len(shape).
updates (Tensor) - The tensor to do the div operation with input_x. The data type is same as input_x, and the shape is indices.shape[:-1] + input_x.shape[indices.shape[-1]:].

Outputs:

Tensor, the updated input_x, has the same shape and type as input_x.

Supported Platforms:

Deprecated

Examples

>>> import mindspore
>>> import numpy as np
>>> from mindspore import Tensor, ops, Parameter
>>> input_x = Parameter(Tensor(np.array([1, 2, 3, 4, 5, 6, 7, 8]), mindspore.float32), name="x")
>>> indices = Tensor(np.array([[2], [4], [1], [7]]), mindspore.int32)
>>> updates = Tensor(np.array([6, 7, 8, 9]), mindspore.float32)
>>> use_locking = False
>>> scatter_nd_div = ops.ScatterNdDiv(use_locking)
>>> output = scatter_nd_div(input_x, indices, updates)
>>> print(output)
[1.         0.25       0.5        4.         0.71428573 6.
 7.         0.8888889 ]
>>> input_x = Parameter(Tensor(np.ones((4, 4, 4)), mindspore.float32))
>>> indices = Tensor(np.array([[0], [2]]), mindspore.int32)
>>> updates = Tensor(np.array([[[1, 1, 1, 1], [2, 2, 2, 2], [3, 3, 3, 3], [4, 4, 4, 4]],
...                            [[5, 5, 5, 5], [6, 6, 6, 6], [7, 7, 7, 7], [8, 8, 8, 8]]]), mindspore.float32)
>>> use_locking = False
>>> scatter_nd_div = ops.ScatterNdDiv(use_locking)
>>> output = scatter_nd_div(input_x, indices, updates)
>>> print(output)
[[[1.         1.         1.         1.        ]
  [0.5        0.5        0.5        0.5       ]
  [0.33333334 0.33333334 0.33333334 0.33333334]
  [0.25       0.25       0.25       0.25      ]]
 [[1.         1.         1.         1.        ]
  [1.         1.         1.         1.        ]
  [1.         1.         1.         1.        ]
  [1.         1.         1.         1.        ]]
 [[0.2        0.2        0.2        0.2       ]
  [0.16666667 0.16666667 0.16666667 0.16666667]
  [0.14285715 0.14285715 0.14285715 0.14285715]
  [0.125      0.125      0.125      0.125     ]]
 [[1.         1.         1.         1.        ]
  [1.         1.         1.         1.        ]
  [1.         1.         1.         1.        ]
  [1.         1.         1.         1.        ]]]