semvec/pypi-packages huggingface dataset:
deep500 0.2.0
The deep learning metaframework

Deep500: A Deep Learning Meta-Framework and HPC Benchmarking Library
====================================================================

<p align="center">
	<img src="https://raw.githubusercontent.com/deep500/deep500/master/d500.png" /><br />
    (or: 500 ways to train deep neural networks)
</p>


Deep500 is a library that can be used to customize and measure anything with deep neural networks, using a clean, high-performant, and simple interface. Deep500 includes four levels of abstraction: (L0) Operators (layers); (L1) Network Evaluation; (L2) Training; and (L3) Distributed Training.

Using Deep500, you automatically gain:
* Operator validation, including gradient checking for backpropagation
* Statistically-accurate performance benchmarks and plots
* High-performance integration with popular deep learning frameworks (see Supported Frameworks below)
* Running your operator/framework/optimizer/communicator/... with real workloads, alongside existing environments
* and much more...

## Installation

Using pip: `pip install deep500`

## Usage

See the [tutorials](https://github.com/deep500/deep500/tree/master/tutorials).

## Requirements
 * Python 3.5 or later
 * Protobuf (`sudo apt-get install protobuf-compiler libprotoc-dev`)
 * For plotted metrics: matplotlib
 * For distributed optimization:
     * Any MPI implementation (OpenMPI, MPICH, MVAPICH etc.)
     * mpi4py Python package

## Supported Frameworks
 * Tensorflow
 * Pytorch
 * Caffe2

## Contributing

Deep500 is an open-source, community driven project. We are happy to accept Pull Requests with your contributions!

## License

Deep500 is published under the New BSD license, see [LICENSE](https://github.com/deep500/deep500/blob/master/LICENSE).
wosPyFile 2.0.0
Simple package for file reading

# PyFile

PyFile is a simple library which provides you some funcionalities for file reading and writing.

# Install

    from wosPyFile import pyFile

# Files

PyFile is effective on simple text files, let's see some examples:

## Reading

###  Read all
This will return all lines

    pyFile.read("file.txt")


###  Read with conditions
 This will return only lines that begins with the list elements

    pyFile.read("file.txt", ["AAA", "BBB", "CCC"])

## Extracting data from lines
Let's assume that we have a variable called **line** with the value bellow


> **ABC1234567**

To extract data from this line, you can use pyFile.getLineData(), the second parameter is responsible to split the line in list elements

	   pyFile.getLineData(line, [3,10])

Output:

> ["ABC", "1234567]


## Matrix

If you have a defined range you can use pyFile.generateMatrix()

    data = []
    collumns = 240
    size = 2
    matrix = pyFile.generateMatriz(collumns, len(lines), size)
    for index, line in  enumerate(lines):
	    pyFile.getLineData(line, matrix[index])


>A list element will be generated according with the interval defined in **size**
multiview-gpu 0.1.1
GPU-accelerated multiview clustering and dimensionality reduction
Keywords: multiview,clustering,dimensionality reduction

# Multiview-GPU

GPU-accelerated multiview clustering and dimensionality reduction thanks to Tensorflow.

Based on [multiview](https://pypi.org/project/multiview/).

# Dependedencies
For building:
- tensorflow-gpu
- numpy
- sklearn
- scipy
- setuptools

For testing and benchmarking:
- pytest
- pytest-benchmark
- multiview

```sh
pip install tensorflow-gpu numpy sklearn scipy setuptools pytest pytest-benchmark multiview
```

To run the tests:
```sh
pytest
# or
python setup.py test
```

Note: the benchmarks take some time to run, to skip them:
```sh
pytest --benchmark-disable
```

Conversely, to only run the tests
```sh
pytest --benchmark-only
```
openstack-summit-counter 0.4.0
OSC Plugin to help compute the number of summits someone has attended.

========================
OpenStack Summit Counter
========================

The ``summit count`` plugin for python-openstackclient helps the user
determine the number of summits they have attended since the beginning
of their interaction with OpenStack.

Installing
==========

::

  $ pip install openstack-summit-counter

Using
=====

::

  $ openstack summit count $first [$current]

For example, if your first summit was for the "Folsom" series and the
next summit is for "Rocky"::

  $ openstack summit count folsom rocky

  +---------+-------+
  | Field   | Value |
  +---------+-------+
  | Summits | 13    |
  +---------+-------+

Can also be used for counting PTGs. For example::

  $ openstack ptg count pike rocky

  +-------+-------+
  | Field | Value |
  +-------+-------+
  | PTGs  | 3     |
  +-------+-------+