일 | 월 | 화 | 수 | 목 | 금 | 토 |
---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | |||
5 | 6 | 7 | 8 | 9 | 10 | 11 |
12 | 13 | 14 | 15 | 16 | 17 | 18 |
19 | 20 | 21 | 22 | 23 | 24 | 25 |
26 | 27 | 28 | 29 | 30 | 31 |
- keras
- ppc64le
- raspberry pi
- colab
- 딥러닝
- dataset
- face_recognition
- linux
- windows
- pyTorch
- download
- python
- colaboratory
- Jupyter notebook
- Anaconda
- python3
- Windows 10
- dlib
- object detection
- error
- Deep Learning
- urllib
- ubuntu
- CUDA
- shakeratos
- YouTube 8M
- FIle
- TensorFlow
- gpu memory
- install
- Today
- Total
목록전체 글 (77)
Shakerato
[Example] from tqdm.notebook import tqdm pbar = tqdm(filenames, disable=False) for x in pbar: pbar.set_description('test') -> Error occured: AttributeError: 'tqdm_notebook' object has no attribute 'sp' [Solution] 1. dsable=True 2. pip install jupyter
1. Download Visual Studio Code (vscode) : https://code.visualstudio.com/ 2. Install Latex Workshop: https://marketplace.visualstudio.com/items?itemName=James-Yu.latex-workshop 3. Check the manual: vscode - Latex Workshop - Manual - Installation and basic settings 4. Install MiKTeX (Installer version): https://miktex.org/download 5. Install latexmk: https://mg.readthedocs.io/latexmk.html 5.1. Ins..
파이썬이 설치되어 있다면, 파이썬에서 기본으로 제공하는 기능을 활용 (Python 2.x) python -m SimpleHTTPServer 8000 (Python 3.x) python -m http.server 8000
mosh website: https://mosh.org/#getting about mosh(한국어): https://b.luavis.kr/server/mosh abount mosh(english): https://www.linode.com/docs/networking/ssh/install-mosh-server-as-ssh-alternative-on-linux/ How to install on Ubuntu server Install Server sudo apt-get install python-software-properties sudo add-apt-repository ppa:keithw/mosh sudo apt-get update sudo apt-get install mosh Install Client..
vi /etc/ssh/sshd_config Add 'UseDNS no' text on the last line restart ssh service using below three methods - service sshd restart - /etc/init.d/sshd restart - /etc/init.d/ssh restart
In Pytorch Error 'Missing key(s) in state_dict' when loading pre-trained model (state_dict()) Reason In training stage, Use DataParallel for multi gpu usage In testing stage, Don't use DataParallel Solution 1. In testing stage, Use DataParallel 2. In testing stage, model.load_state_dict(torch.load(path), strict=False)