beginners-pytorch-deep-learning
Repository for scripts and notebooks from the book: Programming PyTorch for Deep Learning
File Explorer
Download Latest Version (.zip)- Chapter 2.ipynb
- download.py
- images.csv
- Chapter 3.ipynb
- Chapter 4.ipynb
- Chapter 5.ipynb
- Chapter 6.ipynb
- bad_random.py
- create_flame_graph_bad_random.sh
- create_flame_graph_good_random.sh
- good_random.py
- cam.ipynb
- casper.jpg
- casper2.jpg
- tensorboard-example.py
- catfish_model.py
- catfish_server.py
- get-prediction.sh
- run-flask-server.sh
- run-waitress-server.sh
- catfish_model.py
- catfish_server.py
- Dockerfile
- get-prediction.sh
- run-docker.sh
- run-model-service.sh
- catfish_model.py
- catfish_server.py
- Dockerfile
- get-prediction.sh
- run-docker.sh
- run-model-service.sh
- CMakeLists.txt
- hello.cpp
- CMakeLists.txt
- cnnnet.py
- load-cnn.cpp
- Chapter_8_5_Quantizing_Models.ipynb
- CMakeLists.txt
- Chapter9.5.ipynb
- Fast_bert_.ipynb
- fastai.ipynb
- Image_Self_Supervison.ipynb
- environment.yml
- LICENSE
- README.md
- requirements.txt
- requirements_cuda_available.txt
- train.py
# Installation Guide
git clone https://github.com/falloutdurham/beginners-pytorch-deep-learning
Downloads the entire project code from GitHub to your computer.
cd beginners-pytorch-deep-learning
Moves into the project folder you just downloaded.
2. Docker
Easy Recommended- Git Needed to download the project code from GitHub.
- Docker Desktop Needed to build and run containers. Install it and keep it running in the background.
docker build -f chapter8/catfish_docker_cloud/Dockerfile -t beginners-pytorch-deep-learning .
Builds a runnable image based on the Dockerfile.
docker run -p 8080:80 beginners-pytorch-deep-learning
Runs the built image as an actual container.
3. CMake
Mediumcd chapter8
This project's files live in a subfolder, so move into it first.
mkdir build && cd build
Creates a folder to hold the build output and moves into it.
cmake ..
Analyzes the source code and generates build configuration files (must be run inside the build folder).
make
Compiles the code based on the generated build configuration to produce an executable.
4. Python
Easypip install -r requirements.txt
Installs the Python libraries listed in requirements.txt (or similar).
jupyter notebook
Launches Jupyter in your browser so you can open and run the notebook (.ipynb) files.
