masked_fill_() - masked_fill() - v1.5.0

一时失言乱红尘 2023-02-20 08:23 11阅读 0赞

#  masked\_fill\_() - masked\_fill() - v1.5.0 #

**torch.Tensor**  
[https://pytorch.org/docs/stable/tensors.html][https_pytorch.org_docs_stable_tensors.html]

*  `torch.Tensor.masked_fill` (Python method, in `torch.Tensor`)
 *  `torch.Tensor.masked_fill_` (Python method, in `torch.Tensor`)

**`masked_fill_(mask, value)` \- 函数名后面加下划线。in-place version 在 PyTorch 中是指当改变一个 tensor 的值的时候，不经过复制操作，而是直接在原来的内存上改变它的值，可以称为原地操作符。**  
**`masked_fill(mask, value)` \-> Tensor - 函数名后面没有下划线。out-of-place version 在 PyTorch 中是指当改变一个 tensor 的值的时候，经过复制操作，不是直接在原来的内存上改变它的值，而是修改复制的 tensor。**

## 1. `masked_fill_(mask, value)` ##

Fills elements of `self` tensor with `value` where `mask` is True. The shape of `mask` must be broadcastable with the shape of the underlying tensor.  
当对应位置的 `mask` 是 1，用 `value` 填充 `self` tensor 中的元素。

### 1.1 Parameters ###

`mask (BoolTensor)` – the boolean mask (元素是布尔值)  
`value (float)` – the value to fill in with (用于填充的值)

## 2. `masked_fill(mask, value)` \-> Tensor ##

Out-of-place version of `torch.Tensor.masked_fill_()`

## 3. example ##

### 3.1 `masked_fill(mask, value)` \-> Tensor ###

(pt-1.4_py-3.6) yongqiang@yongqiang:~$ python
    Python 3.6.10 |Anaconda, Inc.| (default, May  8 2020, 02:54:21)
    [GCC 7.3.0] on linux
    Type "help", "copyright", "credits" or "license" for more information.
    >>> import torch
    >>> data = torch.randn(2, 3)
    >>> data
    tensor([[ 1.1389,  0.7854, -1.1975],
            [ 0.1931,  1.4460, -0.0749]])
    >>>
    >>> mask = torch.tensor([[True, False, True], [False, True, False]])
    >>> mask
    tensor([[ True, False,  True],
            [False,  True, False]])
    >>>
    >>> masked1 = data.masked_fill(mask, 999)
    >>> masked1
    tensor([[ 9.9900e+02,  7.8542e-01,  9.9900e+02],
            [ 1.9310e-01,  9.9900e+02, -7.4897e-02]])
    >>>
    >>> data
    tensor([[ 1.1389,  0.7854, -1.1975],
            [ 0.1931,  1.4460, -0.0749]])
    >>>
    >>> exit()
    (pt-1.4_py-3.6) yongqiang@yongqiang:~$

### 3.2 `masked_fill_(mask, value)` ###

(pt-1.4_py-3.6) yongqiang@yongqiang:~$ python
    Python 3.6.10 |Anaconda, Inc.| (default, May  8 2020, 02:54:21)
    [GCC 7.3.0] on linux
    Type "help", "copyright", "credits" or "license" for more information.
    >>> import torch
    >>> data = torch.randn(2, 3)
    >>> data
    tensor([[ 0.0718, -0.4983, -0.7344],
            [-2.0372, -1.6503,  1.6308]])
    >>>
    >>> mask = torch.tensor([[True, False, True], [False, True, False]])
    >>> mask
    tensor([[ True, False,  True],
            [False,  True, False]])
    >>>
    >>> masked1 = data.masked_fill_(mask, 999)
    >>> masked1
    tensor([[ 9.9900e+02, -4.9832e-01,  9.9900e+02],
            [-2.0372e+00,  9.9900e+02,  1.6308e+00]])
    >>>
    >>> data
    tensor([[ 9.9900e+02, -4.9832e-01,  9.9900e+02],
            [-2.0372e+00,  9.9900e+02,  1.6308e+00]])
    >>>
    >>> exit()
    (pt-1.4_py-3.6) yongqiang@yongqiang:~$

### 3.3 `-np.inf` ###

(pt-1.4_py-3.6) yongqiang@yongqiang:~$ python
    Python 3.6.10 |Anaconda, Inc.| (default, May  8 2020, 02:54:21)
    [GCC 7.3.0] on linux
    Type "help", "copyright", "credits" or "license" for more information.
    >>> import torch
    >>> data = torch.randn(2, 3)
    >>> data
    tensor([[ 0.3838, -0.8961,  0.4759],
            [ 0.4764, -0.2403,  0.4010]])
    >>>
    >>> mask = torch.tensor([[True, False, True], [False, True, False]])
    >>> mask
    tensor([[ True, False,  True],
            [False,  True, False]])
    >>>
    >>> masked1 = data.masked_fill(mask, 0)
    >>> masked1
    tensor([[ 0.0000, -0.8961,  0.0000],
            [ 0.4764,  0.0000,  0.4010]])
    >>>
    >>> data
    tensor([[ 0.3838, -0.8961,  0.4759],
            [ 0.4764, -0.2403,  0.4010]])
    >>>
    >>> exit()
    (pt-1.4_py-3.6) yongqiang@yongqiang:~$

(pt-1.4_py-3.6) yongqiang@yongqiang:~$ python
    Python 3.6.10 |Anaconda, Inc.| (default, May  8 2020, 02:54:21)
    [GCC 7.3.0] on linux
    Type "help", "copyright", "credits" or "license" for more information.
    >>> import torch
    >>> import numpy as np
    >>>
    >>> data = torch.randn(2, 3)
    >>> data
    tensor([[5.2904e-02, 9.4895e-01, 2.6957e-01],
            [1.2166e-03, 1.2486e+00, 3.0534e+00]])
    >>>
    >>> mask = torch.tensor([[True, False, True], [False, True, False]])
    >>> mask
    tensor([[ True, False,  True],
            [False,  True, False]])
    >>>
    >>> masked1 = data.masked_fill(mask, -np.inf)
    >>> masked1
    tensor([[      -inf, 9.4895e-01,       -inf],
            [1.2166e-03,       -inf, 3.0534e+00]])
    >>>
    >>> data
    tensor([[5.2904e-02, 9.4895e-01, 2.6957e-01],
            [1.2166e-03, 1.2486e+00, 3.0534e+00]])
    >>>
    >>> exit()
    (pt-1.4_py-3.6) yongqiang@yongqiang:~$

[https_pytorch.org_docs_stable_tensors.html]: https://pytorch.org/docs/stable/tensors.html