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# Installation

This repository is tested on Python 3.6+, and Linux/Debian systems.
It is recommended to install in a [virtual environment](https://docs.python.org/3/library/venv.html) to keep your system in order.
Currently supported ML Frameworks are the following: `torch>=1.1.0,<=1.8.0`, `tensorflow>=1.8.0,<=2.0.0`, `tensorflow.keras >= 2.2.0`.

Install with pip using:

```bash
pip install sparseml
```

## Supported Framework Versions

The currently supported framework versions are:

- PyTorch-supported versions: `>= 1.1.0, < 1.8.0`
- Keras-supported versions: `2.3.0-tf` (through the TensorFlow `2.2` package; as of Feb 1st, 2021, `keras2onnx` has
not been tested for TensorFlow >= `2.3`). 
- TensorFlow V1-supported versions: >= `1.8.0` (TensorFlow >= `2.X` is not currently supported)

## Optional Dependencies

Additionally, optional dependencies can be installed based on the framework you are using.

PyTorch:

```bash
pip install sparseml[torch]
```

Keras:

```bash
pip install sparseml[tf_keras]
```

TensorFlow V1:

```bash
pip install sparseml[tf_v1]
```

TensorFlow V1 with GPU operations enabled:

```bash
pip install sparseml[tf_v1_gpu]
```

Depending on your device and CUDA version, you may need to install additional dependencies for using TensorFlow V1 with GPU operations.  
You can find these steps [here](https://www.tensorflow.org/install/gpu#older_versions_of_tensorflow).

Note, TensorFlow V1 is no longer being built for newer operating systems such as Ubuntu 20.04. 
Therefore, SparseML with TensorFlow V1 is unsupported on these operating systems as well.