masked_scatter¶

paddle. masked_scatter ( x, mask, value, name=None ) [source]

Copies elements from value into x tensor at positions where the mask is True.

Elements from source are copied into x starting at position 0 of value and continuing in order one-by-one for each occurrence of mask being True. The shape of mask must be broadcastable with the shape of the underlying tensor. The value should have at least as many elements as the number of ones in mask.

Parameters

x (Tensor) – An N-D Tensor. The data type is float16, float32, float64, int32, int64 or bfloat16.
mask (Tensor) – The boolean tensor indicate the position to be filled. The data type of mask must be bool.
value (Tensor) – The value used to fill the target tensor. Supported data types are same as x.
name (str, optional) – Name for the operation (optional, default is None). For more information, please refer to Name.

Returns

Tensor, A reshaped Tensor with the same data type as x.

Examples

           >>> import paddle
>>> paddle.seed(2048)
>>> x = paddle.randn([2, 2])
>>> print(x)
Tensor(shape=[2, 2], dtype=float32, place=Place(cpu), stop_gradient=True,
    [[-1.24725831,  0.03843464],
    [-0.31660911,  0.04793844]])

>>> mask = paddle.to_tensor([[True, True], [False, False]])
>>> value = paddle.to_tensor([1, 2, 3, 4, 5,], dtype="float32")

>>> out = paddle.masked_scatter(x, mask, value)
>>> print(out)
Tensor(shape=[2, 2], dtype=float32, place=Place(cpu), stop_gradient=True,
    [[1,  2],
    [-0.31660911,  0.04793844]])

          