empty

paddle. empty ( shape, dtype=None, name=None ) [源代码]

该OP创建形状大小为shape并且数据类型为dtype的Tensor，其中元素值是未初始化的。

参数：

  • shape (list|tuple|Tensor) – 指定创建Tensor的形状(shape), 数据类型为int32 或者int64。

  • dtype （np.dtype|str， 可选）- 输出变量的数据类型，可以是bool, float16, float32, float64, int32, int64。若为None，则输出变量的数据类型为系统全局默认类型，默认值为None。

  • 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：返回一个根据 shape 和 dtype 创建并且尚未初始化的Tensor。

代码示例：

import paddle
import numpy as np

paddle.set_device("cpu")  # and use cpu device

# example 1: argument ``shape`` is a list which doesn't contain Tensor.
data1 = paddle.empty(shape=[2,3], dtype='float32')
#[[4.3612203e+27 1.8176809e+31 1.3555911e-19]     # uninitialized
# [1.1699684e-19 1.3563156e-19 3.6408321e-11]]    # uninitialized

# example 2: argument ``shape`` is a Tensor, the data type must be int64 or int32.
shape_data = np.array([2, 3]).astype('int32')
shape = paddle.to_tensor(shape_data)
data2 = paddle.empty(shape=shape, dtype='float32')
#[[1.7192326e-37 4.8125365e-38 1.9866003e-36]     # uninitialized
# [1.3284029e-40 7.1117408e-37 2.5353012e+30]]    # uninitialized

# example 3: argument ``shape`` is a list which contains Tensor.
dim2_data = np.array([3]).astype('int32')
dim2 = paddle.to_tensor(dim2_data)
data3 = paddle.empty(shape=[2, dim2], dtype='float32')
#[[1.1024214e+24 7.0379409e+22 6.5737699e-34]     # uninitialized
# [7.5563101e+31 7.7130405e+31 2.8020654e+20]]    # uninitialized