atleast_1d¶

paddle. atleast_1d ( *inputs, name=None ) [source]

Convert inputs to tensors and return the view with at least 1-dimension. Scalar inputs are converted, one or high-dimensional inputs are preserved.

Parameters

inputs (Tensor|list(Tensor)) – One or more tensors. The data type is float16, float32, float64, int16, int32, int64, int8, uint8, complex64, complex128, bfloat16 or bool.
name (str, optional) – Name for the operation (optional, default is None). For more information, please refer to Name.

Returns

One Tensor, if there is only one input. List of Tensors, if there are more than one inputs.

Examples

           >>> import paddle

>>> # one input
>>> x = paddle.to_tensor(123, dtype='int32')
>>> out = paddle.atleast_1d(x)
>>> print(out)
Tensor(shape=[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_1d(x, y)
>>> print(out)
[Tensor(shape=[1], dtype=int32, place=Place(cpu), stop_gradient=True,
[123]), Tensor(shape=[1], dtype=float32, place=Place(cpu), stop_gradient=True,
[1.23000002])]

>>> # more than 1-D input
>>> x = paddle.to_tensor(123, dtype='int32')
>>> y = paddle.to_tensor([[1.23]], dtype='float32')
>>> out = paddle.atleast_1d(x, y)
>>> print(out)
[Tensor(shape=[1], dtype=int32, place=Place(cpu), stop_gradient=True,
[123]), Tensor(shape=[1, 1], dtype=float32, place=Place(cpu), stop_gradient=True,
[[1.23000002]])]

          