semvec/pypi-packages huggingface dataset:
extconv 0.1
Spatially varying convolutional layers for PyTorch.
License: MIT
Requires Python: >=3.10

<h1 align="center">xonv: Extended convolutional layers</h1>

This repository contains the code for extended convolutional layers.
These layers are akin to the convolutional layers in PyTorch, but with
the key difference that they have spatially varying kernels.

## Installation

For further development and to run the examples, clone the repository
and install the package in editable mode. **Make sure to adapt the
hardcoded CUDA version in `setup.cfg` to the one installed on your system.**

```bash
# Create a new conda environment.
conda create --name xonv python
conda activate xonv

# Clone the repository and install the package in editable mode.
git clone ttps://github.com/alisiahkoohi/xonv
cd xonv/
pip install -e .
```

Run the command below to install the package to be used in your Python environment.

```bash
pip install git+https://github.com/alisiahkoohi/xonv
```


## Usage

The extended convolutional layers can be used as a drop-in replacement
for the PyTorch convolutional layers. The following example demonstrates
how to use the extended convolutional layers:

```python
from xonv.layer import Xonv2D

input_size = (32, 32)  # Height, Width of input
in_channels = 3
out_channels = 16
kernel_size = 3
stride = 2

layer = Xonv2D(
    in_channels,
    out_channels,
    kernel_size,
    input_size,
    stride=stride,
)

input_tensor = torch.randn(1, in_channels, *input_size)
output = layer(input_tensor)

print(layer)
print(output.shape)  # Should be [1, 16, 16, 16]
```

## Examples

To visualize the toeplitz-like matrix associated with the convolutional layer, run the following command:

```bash
python scripts/create_toeplitz_like_matrix.py
```


## Questions

Please contact alisk@rice.edu for questions.

## Author

Ali Siahkoohi
pyfanotify 0.3.0
Python wrapper for Linux fanotify
License: MIT
Requires Python: >=3.5
Keywords: linux kernel fanotify

# pyfanotify
[![PyPI](https://img.shields.io/pypi/v/pyfanotify?logo=python&logoColor=white)][pypi_proj]
[![PyPI - Downloads](https://img.shields.io/pypi/dm/pyfanotify?logo=python&logoColor=white)][pypi_proj]
[![PyPI - License](https://img.shields.io/pypi/l/pyfanotify?logo=open-source-initiative&logoColor=white)](https://github.com/baskiton/pyfanotify/blob/main/LICENSE)

[![build](https://img.shields.io/github/actions/workflow/status/baskiton/pyfanotify/build.yml?logo=github)](https://github.com/baskiton/pyfanotify/actions/workflows/build.yml)
[![upload](https://img.shields.io/github/actions/workflow/status/baskiton/pyfanotify/pypi-upload.yml?label=upload&logo=github)](https://github.com/baskiton/pyfanotify/actions/workflows/pypi-upload.yml)
[![docs](https://img.shields.io/readthedocs/pyfanotify?logo=readthedocs&logoColor=white)][documentation]

Python wrapper for Linux fanotify. \
See [fanotify manpage][man_fanotify] for more details.

To detail see the [documentation][documentation]

### IMPORTANT!
`fanotify` requires execution from **ROOT**!

## Requirements
 * Python 3.6+

## Installing
### Using PIP
```sh
$ pip install pyfanotify
```
### From sources
```sh
$ git clone https://github.com/baskiton/pyfanotify.git
$ cd pyfanotify
$ python setup.py install
```

## Usage
See [examples][examples]


[pypi_proj]: https://pypi.org/project/pyfanotify/
[man_fanotify]: https://man7.org/linux/man-pages/man7/fanotify.7.html
[examples]: https://github.com/baskiton/pyfanotify/blob/main/examples
[documentation]: https://pyfanotify.readthedocs.io