semvec/pypi-packages huggingface dataset:
tract-python 0.2.12
bindings of sonos/tract rust NN inference enging for python
Requires Python: >=3.7
Keywords: tract,neural network engine,deep learning

# tract-python

Project Archived: tract now maintains it's own Python package [here](https://github.com/sonos/tract/tree/main/api/py).

 [![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](https://opensource.org/licenses/MIT)
 [![PyPI version](https://badge.fury.io/py/tract_python.svg)](https://badge.fury.io/py/tract_python)
 [![CI](https://github.com/DreamerMind/tract-python/actions/workflows/CI.yml/badge.svg?branch=main)](https://github.com/DreamerMind/tract-python/actions/workflows/CI.yml)



[tract inference engine](https://github.com/sonos/tract) bindings in Python via FFI.
It support Neural Network inference from NNEF or ONNX.

## Why

No need to compile tract or have cargo installed, fast install.

`tract-cli` is very feature-full but reloading a model each time you wish
to do an inference is computationaly costy and slow.

Think `onnxruntime` except it support NNEF, and it is based on tract.

## Install

Install using pip:
```
pip install tract_python
```


## Usage

```python
import tract_python

print(tract_python.TRACT_VERSION)
# "X.X.X"

tract_model = tract_python.TractModel.load_from_path(
  # This parameter can be an ONNX or NNEF filepath (in case of NNEF it can be a dir or a tgz)
  './tests/assets/test_simple_nnef/' # simple graph that mul input by 2
)
# .run take as argument names the name of input nodes in your neural network
results = tract_model.run(input_0=np.arange(6).reshape(1, 2, 3).astype(np.float32))
print(results)
#{'output_0': array([[[ 0.,  2.,  4.],
#       [ 6.,  8., 10.]]], dtype=float32)}

```

## Status

This project is maintained with latest tract version.

## Scope

Our personnal usecase is to be able to run +10M inferences with 'tract' engine.
So loading/running NNEF or ONNX is sufficient.

We would be happy to support some others `tract-cli` features:
- [ ] computing: number of FMA operations
- [ ] computing: profiling infos

(Thought it would be better to extract from `tract-cli` a `tract-profile` crate first in original repo to avoid code duplicate)
We do not have the bandwith to do more and welcome any contributor that would wish to add more features.
pycuga 0.0.14
Python Cuda Genetic Algorithm Package

## 📦pycuga

Pycuga (PYthon CUda Genetic Algorithm) provides a package for performing island-based genetic algorithm on Python and CUDA.
- Methods for migartion, selection and mutation are implemented already. Users only need to pick the method during initialisation.
- User needs to define evaluation using Cuda code.

### Motivation
- When I worked on my previous project on [Solving Maximum Satisfiability Problem using CUDA](https://github.com/issacto/cuda-maxsat), I realised a lot of code could be reused, which save a lot of development time for solving other optimisation problems using genetic algorithm and CUDA. 


### Parameters

| Methods currently supported |  | 
| ------------- |:-------------:|
| Selection     | Elitism, Roulette Wheel | 
| Crossover     | One (point), Two (points), Uniform|
| Mutation      | Number     |


```
pip install pycuga
```

```python
p1 = PyCUGA(constArr, chromosomeSize, stringPlaceholder, mutationNumber, selectionMode, crossoverMode)
p1. launchKernel(islandSize, blockSize , chromosomeNo, isTime, timeAllowed, migrationRounds, rounds)
```

- constArr (numpy array): defines the details of the problem
- chromosomeSize (int): number of variables in a chromosome 
- stringPlaceholder (string): defines the evalutaion method and other constants
- mutationNumber (int): /
- selectionMode (string): "elitism" or "roulettewheel"
- crossoverMode (string): "one" or "two" or "uniform"

- islandSize (int): size of an island
- blockSize (int): Cuda block size
- chromosomeNo (int): number of chromosomes
- migrationRounds (int): number of rounds per migration
- isTime (bool): stopped by time or number of rounds
- timeAllowed (int): seconds allowed
- rounds (int): total number of rounds

Examples [here](https://github.com/issacto/PyCuGa/tree/main/samples).

Colab MaxSat example  [here](https://github.com/issacto/PyCuGa/tree/main/samples).

### Limitations
* Use multiples of 32 (for chromosome parameters) to avoid bugs and increase efficiency.
* Island migration is limited to 1 item currently
* Lack unit testing


### ❗Disclaimer
This is a mini project which I've put quite a lot of time and effort into, but I can't take responsibility for any bugs nor errors.
speakWin 0.0.2
Text to Speech Windows Based.

# `speakWin` Function

The `speakWin` function is a Python script that utilizes the `pyttsx3` library to convert text messages into speech. It is designed to work on Windows operating systems and uses the 'sapi5' speech engine. This function is useful for creating text-to-speech applications or for providing voice feedback in various projects.

## Installation

Before using the `speakWin` function, you need to install the `pyttsx3` library, which is not included in Python's standard library. You can install it using pip:

## version
0.0.1
## Authors

- [@RANJIT_MAITY](https://www.linkedin.com/in/ranjit-maity-75204a131/)


## Reales Date 
 23-09-2023
 
 


## Badges

[![MIT License](https://img.shields.io/apm/l/atomic-design-ui.svg?)](https://github.com/tterb/atomic-design-ui/blob/master/LICENSEs)
[![GPLv3 License](https://img.shields.io/badge/License-GPL%20v3-yellow.svg)](https://opensource.org/licenses/)
[![AGPL License](https://img.shields.io/badge/license-AGPL-blue.svg)](http://www.gnu.org/licenses/agpl-3.0)


##  About Author
I Am Ranjit From INDIA, a Certified Data scientist , Data Engineer by professional  with hands-on experience of more than 1year and 2months ,on ML> NLP> Data mining > Neural Networks > ModeL Deployment>ETL.
 Give me raw data and I'll return you insights, problems to be rectified and enhancements to achieve the target. I am always on the lookout for new projects to work And 
Am Always Happy â˜» To Play With Data


##  Links

[![linkedin](https://img.shields.io/badge/linkedin-0A66C2?style=for-the-badge&logo=linkedin&logoColor=white)](https://www.linkedin.com/in/ranjit-maity-75204a131/)
[![twitter](https://img.shields.io/badge/twitter-1DA1F2?style=for-the-badge&logo=twitter&logoColor=white)](https://twitter.com/ranjitmaity95)