未验证 提交 0cd639b8 编写于 作者: F furnace 提交者: GitHub

add new empty op (PR #26659) doc (#2571)

Co-authored-by: Nroot <root@yq01-qianmo-com-255-129-13.yq01.baidu.com>
上级 cc2d8b36
.. _cn_api_tensor_empty:
empty
-------------------------------
.. py:function:: paddle.empty(shape, dtype=None, name=None)
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 :ref:`api_guide_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**:
.. code-block:: python
import paddle
import numpy as np
paddle.disable_static() # Now we are in imperative mode
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
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