set_

paddle.Tensor. set_ ( x: paddle.Tensor, source: paddle.Tensor | None = None, shape: Sequence[int] | None = None, stride: Sequence[int] | None = None, offset: int = 0, name: str | None = None ) → paddle.Tensor

set x with specified source Tensor’s underlying storage, shape, stride and offset.

Note that the x will share the same data with source Tensor.

Parameters

  • x (Tensor) – An arbitrary Tensor. The data type supports bfloat16, float16, float32, float64, bool, int8, int16, int32, int64, uint8, complex64 or complex128.

  • source (Tensor|None, optional) – Define the target Tensor to use. The data type supports bfloat16, float16, float32, float64, bool, int8, int16, int32, int64, uint8, complex64 or complex128. Default: None, which means to set x with an empty source tensor.

  • shape (list|tuple|None, optional) – Define the target shape. Each element of it should be integer. Default: None, which means it will use the specified source’s shape as default value.

  • stride (list|tuple|None, optional) – Define the target stride. Each element of it should be integer. Default: None, and when shape is also None, it will use the specified source’s stride as default value; when shape is specified, it will use the default stride corresponding to the specified shape.

  • offset (int, optional) – Define the target offset from x’s holder. Default: 0.

  • name (str|None, optional) – Name for the operation (optional, default is None). For more information, please refer to Name.

Returns

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

Examples

>>> import paddle

>>> src = paddle.to_tensor([[11., 22., 33.]])
>>> src2 = paddle.to_tensor([11., 22., 33., 44., 55., 66.])

>>> x = paddle.to_tensor([1., 2., 3., 4., 5.])
>>> x.set_()
>>> print(x)
Tensor(shape=[0], dtype=float32, place=Place(cpu), stop_gradient=True,
[])

>>> x = paddle.to_tensor([1., 2., 3., 4., 5.])
>>> x.set_(src)
>>> print(x)
Tensor(shape=[1, 3], dtype=float32, place=Place(cpu), stop_gradient=True,
[[11., 22., 33.]])

>>> print(x._is_shared_buffer_with(src))
True

>>> x = paddle.to_tensor([1., 2., 3., 4., 5.])
>>> x.set_(src, shape=[2, 1])
>>> print(x)
Tensor(shape=[2, 1], dtype=float32, place=Place(cpu), stop_gradient=True,
[[11.],
 [22.]])

>>> x = paddle.to_tensor([1., 2., 3., 4., 5.])
>>> x.set_(src2, shape=[3], stride=[2])
>>> print(x)
Tensor(shape=[3], dtype=float32, place=Place(cpu), stop_gradient=True,
[11., 33., 55.])

>>> x = paddle.to_tensor([1., 2., 3., 4., 5.])
>>> x.set_(src2, shape=[5], offset=4)
>>> print(x)
Tensor(shape=[5], dtype=float32, place=Place(cpu), stop_gradient=True,
[22., 33., 44., 55., 66.])