Pytorch seminar

1. Data-driven, AI, Security, HCI Lab -DASH Lab
Hands on PyTorch

2. Data-driven, AI, Security, HCI Lab -DASH Lab
Contents
1. Prerequisite
2. About Pytorch
3. Hands on Pytorch
– Variable
– Autograd
– Functions
4. Autoencoder
5. Assignment

3. Data-driven, AI, Security, HCI Lab -DASH Lab
Prerequisite
1. OOP(Object-Oriented Programming)
2. Framework(vs Package)
3. Deep learning Modeling

4. Data-driven, AI, Security, HCI Lab -DASH Lab
1. How to read Programming Language?
생각, 느낌 따위를 나타내거나
전달하는 데에 쓰는 음성, 문자
따위의 수단. 또는 그 음성이나 문자
따위의 사회 관습적인 체계
What is language?

5. Data-driven, AI, Security, HCI Lab -DASH Lab
“컴퓨터 시스템을 구동시키는
소프트웨어를 작성하기 위한
형식언어”
언어의 특성을 확인할 수 있다면
앞으로의 코드를
체계적으로 읽을 수 있음
What is Programming Language?

6. Data-driven, AI, Security, HCI Lab -DASH Lab
What is Programming Language?
English basic structure
S
- [나]
S` of s
- [내 팔]
S+V
- [나는 걷는다]
S+V+O
- [나는 집으로 걷는다]

7. Data-driven, AI, Security, HCI Lab -DASH Lab
S+V
• Fs =100 (Fs is 100)
• f= 2 (f is 2)
S+V+O
• X is fs which is arranged
by numpy
• Y is sin divided by sme
values
• Plt figure should
size(10,5)
Programming Language basic structure

8. Data-driven, AI, Security, HCI Lab -DASH Lab
Programming Language basic structure
3.Object.Method(parameter)
2. Object.Method (X)
1. Method(Object)
Ex) Sorted(List) , abs(-3)
Ex)
Ex) plt.plot(graph)

9. Data-driven, AI, Security, HCI Lab -DASH Lab

10. Data-driven, AI, Security, HCI Lab -DASH Lab

11. Data-driven, AI, Security, HCI Lab -DASH Lab
프레임워크란?
• 규칙의 집합
• 앞서 개발한 사람들의 지혜와 사례를 활용
• 정형화된 형태의 규칙으로 만든 프로그램
중요한 점 : 제어반전
[ 내가 원하는 방식대로 코딩 ] X
[ 프로그램이 하라는 대로 코딩] O
Framework vs library

12. Data-driven, AI, Security, HCI Lab -DASH Lab

13. Data-driven, AI, Security, HCI Lab -DASH Lab
3. Pytorch

14. Data-driven, AI, Security, HCI Lab -DASH Lab
Popularity

15. Data-driven, AI, Security, HCI Lab -DASH Lab
Google and Facebook

16. Data-driven, AI, Security, HCI Lab -DASH Lab
Hands on Pytorch
1. Installation
2. Anaconda( GPU check)
3. Jupyter notebook

17. Data-driven, AI, Security, HCI Lab -DASH Lab
Python customization

18. Data-driven, AI, Security, HCI Lab -DASH Lab
Reproductivity model (in production)
For general
For GPU
For preprocessing( if you are using numpy backend

19. Data-driven, AI, Security, HCI Lab -DASH Lab
Common mistake on Pytorch
1. model.train() vs model.eval()
2. Call zero.grad() before backward()

20. Data-driven, AI, Security, HCI Lab -DASH Lab
Common mistake on Pytorch
1. model.train() vs model.eval()
2. Call zero.grad() before backward()
2. Call zero.grad() before backward()

21. Data-driven, AI, Security, HCI Lab -DASH Lab
Question
More questions at : yaup22cc@likelion.org