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https://github.com/radi-cho/create-tf-app
Set up and maintain a machine learning project in Tensorflow with a single script.
https://github.com/radi-cho/create-tf-app
cli machine-learning shell-script tensorflow
Last synced: 13 days ago
JSON representation
Set up and maintain a machine learning project in Tensorflow with a single script.
- Host: GitHub
- URL: https://github.com/radi-cho/create-tf-app
- Owner: radi-cho
- License: mit
- Created: 2022-12-19T20:51:27.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2022-12-24T10:24:52.000Z (about 2 years ago)
- Last Synced: 2024-12-22T15:42:07.061Z (23 days ago)
- Topics: cli, machine-learning, shell-script, tensorflow
- Language: Python
- Homepage:
- Size: 15.6 KB
- Stars: 4
- Watchers: 3
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-tensorflow-2 - create-tf-app - Project builder command line tool for Tensorflow covering environment management, linting, and logging. (Sample Codes / Projects <a name="sample" /> ⛏️📐📁 / General 🚧 <a name="GeneralCode" />)
- awesome-tensorflow - create-tf-app - Project builder command line tool for Tensorflow covering environment management, linting, and logging. (Tools/Utilities)
- fucking-awesome-tensorflow - create-tf-app - Project builder command line tool for Tensorflow covering environment management, linting, and logging. (Tools/Utilities)
README
# create-tf-app
Set up and maintain a machine learning project in Tensorflow with a single script.Inspired by [create-react-app](https://github.com/facebook/create-react-app) and [create-ml-app](https://github.com/shreyashankar/create-ml-app). Made by [radi-cho](https://github.com/radi-cho).
## Usage
Make sure [Conda](https://docs.conda.io/en/latest/) is available on your device. Alternatively, if you don't need environment management, you can just use `main.py` as a template or edit `tf_app.sh` per your needs.
```sh
git clone https://github.com/radi-cho/create-tf-app.git tf_app
cd tf_app
sh ./tf_app.sh {create_env|run|lint|run_tensorboard}
```- `create_env` - Create a Conda environment (named tf_app by default) and install necessary packages.
- `run` - Run `main.py` in the appropriate environment and pass any arguments to it.
- `lint` - Run [flake8](https://pypi.org/project/flake8/) linting for all `.py` files unless specific filenames are be provided.
- `run_tensorboard` - Run [Tensorboard](https://tensorboard.dev/) to visualize records in the ./logs directory.You can use an environment variable - `TF_APP_ENV_NAME` - to create multiple projects or set a specific name.
```sh
TF_APP_ENV_NAME=tf_app2 sh ./tf_app.sh {create_env|run|lint|run_tensorboard}
```If you need to edit your environment or execute specific commands in it, you can always enter it with `conda activate tf_app`.