feat: add pytorch.md (#138)

README.md

@@ -26,7 +26,8 @@ Quick Reference
 [FFmpeg](./docs/ffmpeg.md)<!--rehype:style=background: rgb(0 193 9/var(\-\-bg\-opacity));&class=contributing-->
 [LaTeX](./docs/latex.md)<!--rehype:style=background: rgb(0 128 128/var(\-\-bg\-opacity));&class=contributing-->
 [MATLAB](./docs/matlab.md)<!--rehype:style=background: rgb(0 118 168/var(\-\-bg\-opacity));&class=contributing-->
-[Vue 3](./docs/vue.md)<!--rehype:style=background: rgb(64 184 131/var(\-\-bg\-opacity));&class=contributing-->
+[Vue 3 ](./docs/vue.md)<!--rehype:style=background: rgb(64 184 131/var(\-\-bg\-opacity));&class=contributing-->
+[Pytorch](./docs/pytorch.md)<!--rehype:style=background: rgb(43 91 132/var(\-\-bg\-opacity));&class=contributing&data-info=👆看看还缺点儿什么？-->
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 ## 编程
@@ -60,6 +61,7 @@ Quick Reference
 [TOML](./docs/toml.md)<!--rehype:style=background: rgb(132 132 132/var(\-\-bg\-opacity));-->
 [YAML](./docs/yaml.md)<!--rehype:style=background: rgb(91 163 230/var(\-\-bg\-opacity));-->
 [Lua](./docs/lua.md)<!--rehype:style=background: rgb(64 196 255/var(\-\-bg\-opacity));-->
+[Pytorch](./docs/pytorch.md)<!--rehype:style=background: rgb(43 91 132/var(\-\-bg\-opacity));&class=contributing&data-info=👆看看还缺点儿什么？-->
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 ## 前端
@@ -173,15 +175,9 @@ Quick Reference
 <a href="https://github.com/Jack-Zhang-1314" title="fw_qaq">
   <img src="https://avatars.githubusercontent.com/u/82551626?v=4" width="42;" alt="fw_qaq"/>
 </a>
-<a href="https://github.com/Alex-Programer" title="Alex">
-  <img src="https://avatars.githubusercontent.com/u/115539090?v=4" width="42;" alt="Alex"/>
-</a>
 <a href="https://github.com/mofelee" title="mofelee">
   <img src="https://avatars.githubusercontent.com/u/5069410?v=4" width="42;" alt="mofelee"/>
 </a>
-<a href="https://github.com/expoli" title="expoli">
-  <img src="https://avatars.githubusercontent.com/u/31023767?v=4" width="42;" alt="expoli"/>
-</a>
 <a href="https://github.com/partoneplay" title="partoneplay">
   <img src="https://avatars.githubusercontent.com/u/5189132?v=4" width="42;" alt="partoneplay"/>
 </a>
@@ -191,18 +187,15 @@ Quick Reference
 <a href="https://github.com/13812700839" title="花殇">
   <img src="https://avatars.githubusercontent.com/u/58072506?v=4" width="42;" alt="花殇"/>
 </a>
+<a href="https://github.com/Alex-Programer" title="Alex">
+  <img src="https://avatars.githubusercontent.com/u/115539090?v=4" width="42;" alt="Alex"/>
+</a>
 <a href="https://github.com/Smartdousha" title="Anko">
   <img src="https://avatars.githubusercontent.com/u/52566311?v=4" width="42;" alt="Anko"/>
 </a>
-<a href="https://github.com/Brid9e" title="Brid9e">
-  <img src="https://avatars.githubusercontent.com/u/85558909?v=4" width="42;" alt="Brid9e"/>
-</a>
 <a href="https://github.com/CharlotteZeng" title="Chart">
   <img src="https://avatars.githubusercontent.com/u/19461184?v=4" width="42;" alt="Chart"/>
 </a>
-<a href="https://github.com/DaiNing810" title="DaiN">
-  <img src="https://avatars.githubusercontent.com/u/94962339?v=4" width="42;" alt="DaiN"/>
-</a>
 <a href="https://github.com/demigodliu" title="DemigodLiu">
   <img src="https://avatars.githubusercontent.com/u/30372735?v=4" width="42;" alt="DemigodLiu"/>
 </a>
@@ -212,9 +205,6 @@ Quick Reference
 <a href="https://github.com/JetSquirrel" title="JetSquirrel">
   <img src="https://avatars.githubusercontent.com/u/20291255?v=4" width="42;" alt="JetSquirrel"/>
 </a>
-<a href="https://github.com/Lihuagreek" title="Lihuagreek">
-  <img src="https://avatars.githubusercontent.com/u/51040740?v=4" width="42;" alt="Lihuagreek"/>
-</a>
 <a href="https://github.com/mariuszmichalowski" title="Mariusz Michalowski">
   <img src="https://avatars.githubusercontent.com/u/92091891?v=4" width="42;" alt="Mariusz Michalowski"/>
 </a>
@@ -242,9 +232,6 @@ Quick Reference
 <a href="https://github.com/hweining" title="hweining">
   <img src="https://avatars.githubusercontent.com/u/8973985?v=4" width="42;" alt="hweining"/>
 </a>
-<a href="https://github.com/k983551019" title="k983551019">
-  <img src="https://avatars.githubusercontent.com/u/48147837?v=4" width="42;" alt="k983551019"/>
-</a>
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@@ -254,9 +241,6 @@ Quick Reference
 <a href="https://github.com/liliangrong777" title="liliangrong777">
   <img src="https://avatars.githubusercontent.com/u/58727146?v=4" width="42;" alt="liliangrong777"/>
 </a>
-<a href="https://github.com/lykjjj" title="lykjjj">
-  <img src="https://avatars.githubusercontent.com/u/58510058?v=4" width="42;" alt="lykjjj"/>
-</a>
 <a href="https://github.com/onewesong" title="onewesong">
   <img src="https://avatars.githubusercontent.com/u/17920822?v=4" width="42;" alt="onewesong"/>
 </a>

docs/pytorch.md

@@ -0,0 +1,177 @@
+Pytorch  备忘清单
+===
+
+Pytorch 备忘单是 [Pytorch ](https://pytorch.org/) 官网
+
+入门
+-----
+
+### 介绍
+
+- [Pytorch基本语法]
+- [Pytorch初步应用]
+
+### 认识Pytorch
+
+```python
+from __future__ import print_function
+import torch
+x = torch.empty(5, 3)
+>>> print(x)
+tensor([[2.4835e+27, 2.5428e+30, 1.0877e-19],
+        [1.5163e+23, 2.2012e+12, 3.7899e+22],
+        [5.2480e+05, 1.0175e+31, 9.7056e+24],
+        [1.6283e+32, 3.7913e+22, 3.9653e+28],
+        [1.0876e-19, 6.2027e+26, 2.3685e+21]])
+```
+
+Tensors张量: 张量的概念类似于Numpy中的ndarray数据结构, 最大的区别在于Tensor可以利用GPU的加速功能.
+
+### 创建一个全零矩阵
+
+```python
+x = torch.zeros(5, 3, dtype=torch.long)
+>>> print(x)
+tensor([[0, 0, 0],
+        [0, 0, 0],
+        [0, 0, 0],
+        [0, 0, 0],
+        [0, 0, 0]])
+```
+
+创建一个全零矩阵并可指定数据元素的类型为long
+
+### 数据创建张量
+
+```python
+x = torch.tensor([2.5, 3.5])
+>>> print(x)
+tensor([2.5000, 3.3000])
+```
+
+Pytorch的基本语法
+---------------
+
+### 加法操作
+
+```python
+y = torch.rand(5, 3)
+>>> print(x + y)
+tensor([[ 1.6978, -1.6979,  0.3093],
+        [ 0.4953,  0.3954,  0.0595],
+        [-0.9540,  0.3353,  0.1251],
+        [ 0.6883,  0.9775,  1.1764],
+        [ 2.6784,  0.1209,  1.5542]])
+```
+
+第一种加法操作
+
+### 加法操作
+
+```python
+>>> print(torch.add(x, y))
+tensor([[ 1.6978, -1.6979,  0.3093],
+        [ 0.4953,  0.3954,  0.0595],
+        [-0.9540,  0.3353,  0.1251],
+        [ 0.6883,  0.9775,  1.1764],
+        [ 2.6784,  0.1209,  1.5542]])
+```
+
+第二种加法操作
+
+### 加法操作
+
+```python
+# 提前设定一个空的张量
+result = torch.empty(5, 3)
+# 将空的张量作为加法的结果存储张量
+ torch.add(x, y, out=result)
+>>> print(result)
+tensor([[ 1.6978, -1.6979,  0.3093],
+        [ 0.4953,  0.3954,  0.0595],
+        [-0.9540,  0.3353,  0.1251],
+        [ 0.6883,  0.9775,  1.1764],
+        [ 2.6784,  0.1209,  1.5542]])
+```
+
+第三种加法操作
+
+
+### 加法操作
+
+```python
+y.add_(x)
+>>> print(y)
+tensor([[ 1.6978, -1.6979,  0.3093],
+        [ 0.4953,  0.3954,  0.0595],
+        [-0.9540,  0.3353,  0.1251],
+        [ 0.6883,  0.9775,  1.1764],
+        [ 2.6784,  0.1209,  1.5542]])
+```
+
+第四种加法操作
+注意:所有in-place的操作函数都有一个下划线的后缀.
+比如x.copy_(y), x.add_(y), 都会直接改变x的值.
+
+### 张量操作
+
+```python
+
+>>> print(x[:, 1])
+tensor([-2.0902, -0.4489, -0.1441,  0.8035, -0.8341])
+```
+
+### 张量形状
+
+```python
+x = torch.randn(4, 4)
+# tensor.view()操作需要保证数据元素的总数量不变
+y = x.view(16)
+# -1代表自动匹配个数
+z = x.view(-1, 8)
+>>> print(x.size(), y.size(), z.size())
+torch.Size([4, 4]) torch.Size([16]) torch.Size([2, 8])
+```
+
+### 取张量元素
+
+```python
+x = torch.randn(1)
+>>> print(x)
+>>> print(x.item())
+tensor([-0.3531])
+-0.3530771732330322
+```
+
+
+### Torch Tensor和Numpy array互换
+
+```python
+a = torch.ones(5)
+>>> print(a)
+tensor([1., 1., 1., 1., 1.])
+```
+
+Torch Tensor和Numpy array共享底层的内存空间, 因此改变其中一个的值, 另一个也会随之被改变
+
+### Torch Tensor转换为Numpy array
+
+```python
+b = a.numpy()
+>>> print(b)
+[1. 1. 1. 1. 1.]
+```
+
+### Numpy array转换为Torch Tensor:
+
+```python
+import numpy as np
+a = np.ones(5)
+b = torch.from_numpy(a)
+np.add(a, 1, out=a)
+>>> print(a)
+>>> print(b)
+[2. 2. 2. 2. 2.]
+tensor([2., 2., 2., 2., 2.], dtype=torch.float64)
+```
+注意:所有在CPU上的Tensors, 除了CharTensor, 都可以转换为Numpy array并可以反向转换.