atleast_2d

paddle. atleast_2d ( *inputs, name=None ) [源代码]

将输入转换为张量并返回至少为 2 维的视图。 2 维或更高维的输入会被保留。

参数

  • inputs (Tensor|list(Tensor)) - 一个或多个 Tensor,数据类型为: float16, float32, float64, int16, int32, int64, int8, uint8, complex64, complex128, bfloat16bool

  • name (str,可选) - 具体用法请参见 Name,一般无需设置,默认值为 None。

返回

Tensor 或者由 Tensor 组成的 list。当只有一个输入的时候返回一个 Tensor,当有多个输入的时候返回由 Tensor 组成的 list。

代码示例

>>> import paddle

>>> # one input
>>> x = paddle.to_tensor(123, dtype='int32')
>>> out = paddle.atleast_2d(x)
>>> print(out)
Tensor(shape=[1, 1], dtype=int32, place=Place(cpu), stop_gradient=True,
[[123]])

>>> # more than one inputs
>>> x = paddle.to_tensor(123, dtype='int32')
>>> y = paddle.to_tensor([1.23], dtype='float32')
>>> out = paddle.atleast_2d(x, y)
>>> print(out)
[Tensor(shape=[1, 1], dtype=int32, place=Place(cpu), stop_gradient=True,
[[123]]), Tensor(shape=[1, 1], dtype=float32, place=Place(cpu), stop_gradient=True,
[[1.23000002]])]

>>> # more than 2-D input
>>> x = paddle.to_tensor(123, dtype='int32')
>>> y = paddle.to_tensor([[[1.23]]], dtype='float32')
>>> out = paddle.atleast_2d(x, y)
>>> print(out)
[Tensor(shape=[1, 1], dtype=int32, place=Place(cpu), stop_gradient=True,
[[123]]), Tensor(shape=[1, 1, 1], dtype=float32, place=Place(cpu), stop_gradient=True,
[[[1.23000002]]])]

使用本API的教程文档