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: 18 days ago
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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 (almost 2 years ago)
• Default Branch: main
• Last Pushed: 2022-12-24T10:24:52.000Z (almost 2 years ago)
• Last Synced: 2024-10-27T18:57:18.383Z (about 2 months 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`.