atleast_2d¶
- paddle. atleast_2d ( *inputs, name=None ) [source]
-
Convert inputs to tensors and return the view with at least 2-dimension. Two 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
orbool
.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_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]]])]