mindspore.ops.scatter
- mindspore.ops.scatter(input, axis, index, src)[source]
Update the value in src to input according to the specified index. Refer to
mindspore.ops.tensor_scatter_elements()
for more details.- Parameters
input (Tensor) – The target tensor. The rank of input must be at least 1.
axis (int) – Which axis to scatter. Accepted range is [-r, r) where r = rank(input).
index (Tensor) – The index to do update operation whose data type must be mindspore.int32 or mindspore.int64. Same rank as input . And accepted range is [-s, s) where s is the size along axis.
src (Tensor) – The tensor doing the update operation with input , has the same type as input , and the shape of src should be equal to the shape of index .
- Returns
Tensor, has the same shape and type as input .
- Raises
TypeError – If index is neither int32 nor int64.
ValueError – If anyone of the rank among input , index and src less than 1.
ValueError – If the shape of src is not equal to the shape of index .
ValueError – If the rank of src is not equal to the rank of input .
RuntimeError – If the data type of input and src conversion of Parameter is required when data type conversion of Parameter is not supported.
- Supported Platforms:
Ascend
GPU
CPU
Examples
>>> input = Tensor(np.array([[1, 2, 3, 4, 5]]), dtype=ms.float32) >>> src = Tensor(np.array([[8, 8]]), dtype=ms.float32) >>> index = Tensor(np.array([[2, 4]]), dtype=ms.int64) >>> out = ops.scatter(input=input, axis=1, index=index, src=src) >>> print(out) [[1. 2. 8. 4. 8.]] >>> input = Tensor(np.zeros((5, 5)), dtype=ms.float32) >>> src = Tensor(np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]), dtype=ms.float32) >>> index = Tensor(np.array([[0, 0, 0], [2, 2, 2], [4, 4, 4]]), dtype=ms.int64) >>> out = ops.scatter(input=input, axis=0, index=index, src=src) >>> print(out) [[1. 2. 3. 0. 0.] [0. 0. 0. 0. 0.] [4. 5. 6. 0. 0.] [0. 0. 0. 0. 0.] [7. 8. 9. 0. 0.]] >>> input = Tensor(np.zeros((5, 5)), dtype=ms.float32) >>> src = Tensor(np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]), dtype=ms.float32) >>> index = Tensor(np.array([[0, 2, 4], [0, 2, 4], [0, 2, 4]]), dtype=ms.int64) >>> out = ops.scatter(input=input, axis=1, index=index, src=src) >>> print(out) [[1. 0. 2. 0. 3.] [4. 0. 5. 0. 6.] [7. 0. 8. 0. 9.] [0. 0. 0. 0. 0.] [0. 0. 0. 0. 0.]]