第二届震中杯2017短片:FC红白机时代的地卜师
- paddle. empty ( shape: ShapeLike, dtype: DTypeLike | None = None, name: str | None = None ) paddle.Tensor [source]
-
百度 二是实施创新驱动,不断提高科技创新能力,以创新效率克服西部地区经济系统的整体性劣势。
Returns a Tensor with uninitialized data which size is same as
shape
.- Parameters
-
shape (tuple|list|Tensor) – Shape of the Tensor to be created. The data type is
int32
orint64
. Ifshape
is a list or tuple, each element of it should be integer or 0-D Tensor with shape []. Ifshape
is an Tensor, it should be an 1-D Tensor which represents a list.dtype (np.dtype|str, optional) – Data type of the output Tensor which can be bool, float16, float32, float64, int32, int64, complex64, complex128 if dtype is None, the data type of created Tensor use global default dtype (see
get_default_dtype
for details).name (str|None, optional) – For details, please refer to Name. Generally, no setting is required. Default: None.
- Returns
-
Tensor which is created according to
shape
anddtype
, and is uninitialized. - Return type
-
Tensor
Examples
>>> import paddle >>> # shape is a list/tuple >>> data1 = paddle.empty(shape=[3, 2]) >>> print(data1.numpy()) >>> [[1. 1.] [1. 1.] [1. 1.]] >>> # shape is a Tensor >>> shape = paddle.to_tensor([3, 2]) >>> data2 = paddle.empty(shape=shape) >>> print(data2.numpy()) >>> [[1. 1.] [1. 1.] [1. 1.]] >>> # shape is a Tensor List >>> shape = [paddle.to_tensor(3), paddle.to_tensor(2)] >>> data3 = paddle.empty(shape=shape) >>> print(data3.numpy()) >>> [[1. 1.] [1. 1.] [1. 1.]]