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https://github.com/akileshjayakumar/gpu-detection-scripts


https://github.com/akileshjayakumar/gpu-detection-scripts

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# GPU Detection Scripts

This repository contains Python scripts to check GPU availability and status using PyTorch and TensorFlow.

## Files

- **gpu_test.py**: Checks GPU availability using PyTorch and TensorFlow.
- **gpu_test_pytorch.py**: Checks GPU availability using PyTorch only.
- **gpu_test_tf.py**: Checks GPU availability using TensorFlow only.

## Usage

To check for GPU availability, run the appropriate script:

- **For both PyTorch and TensorFlow:**
```bash
python gpu_test.py
```
- **For PyTorch only:**
```bash
python gpu_test_pytorch.py
```
- **For TensorFlow only:**
```bash
python gpu_test_tf.py
```

## Output

Each script will display the following information:

- **PyTorch**:
- If CUDA is available.
- Number of CUDA devices.
- Name of the first CUDA device (if available).

- **TensorFlow**:
- Number of GPUs available (prefixed with `Num GPUs Available:`).

## Requirements

Ensure you have the necessary libraries installed. The scripts will notify you
if either library is missing. Install them individually with:

```bash
pip install torch tensorflow pytest
```

## Requirements

Ensure you have the necessary libraries installed. The scripts will notify you
if either library is missing. Install them individually with:

```bash
pip install torch tensorflow pytest
```

Alternatively, install everything from the provided requirements file:

```bash
pip install -r requirements.txt
```

## Testing

This project uses [pytest](https://pytest.org/) for its test suite. After
installing the required packages, run:

```bash
pytest
```

This command executes the tests under the `tests` directory and verifies that
each GPU detection script runs without errors.

## Acknowledgments

Thanks to the open-source community for the tools and libraries used.