Metadata-Version: 2.1
Name: alchemy-catalyst
Version: 20.1.9
Summary: Alchemy. Experiments logging & visualization.
Home-page: https://github.com/catalyst-team/alchemy
Author: David Kuryakin
Author-email: dkuryakin@gmail.com
License: Apache License 2.0
Description: 
        <div align="center">
        
        ![Alchemy logo](https://raw.githubusercontent.com/catalyst-team/catalyst-pics/master/pics/alchemy_logo.png)
        
        **Experiments logging & visualization**
        
        [![Build Status](https://travis-ci.com/catalyst-team/alchemy.svg?branch=master)](https://travis-ci.com/catalyst-team/alchemy)
        [![Pipi version](https://img.shields.io/pypi/v/alchemy-catalyst.svg)](https://pypi.org/project/alchemy-catalyst/)
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        [![PyPI Status](https://pepy.tech/badge/alchemy-catalyst)](https://pepy.tech/project/alchemy-catalyst)
        [![Github contributors](https://img.shields.io/github/contributors/catalyst-team/alchemy.svg?logo=github&logoColor=white)](https://github.com/catalyst-team/alchemy/graphs/contributors)
        
        [![Twitter](https://img.shields.io/badge/news-on%20twitter-499feb)](https://t.me/catalyst_team)
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        </div>
        
        Part of [Catalyst Ecosystem](https://docs.google.com/presentation/d/1D-yhVOg6OXzjo9K_-IS5vSHLPIUxp1PEkFGnpRcNCNU/edit?usp=sharing). Project [manifest](https://github.com/catalyst-team/catalyst/blob/master/MANIFEST.md).
        
        ---
        
        ## Installation
        
        Common installation:
        ```bash
        pip install -U alchemy-catalyst
        ```
        
        ## Getting started
        
        1. Goto [Alchemy](https://alchemy.host/) and get your personal token.
        
        2. Run following **example.py**:
            ```python
            import random
        
            from alchemy import Logger
        
            token = "..."  # insert your personal token here
        
            for gid in range(1):
                for eid in range(2):
                    for mid in range(3):
                        metric = f"metric_{mid}"
                        group = f"group_{gid}"
                        experiment = f"experiment_{eid}"
        
                        logger = Logger(token, experiment, group)
        
                        n = 300
                        x = random.randint(-10, 10)
                        for i in range(n):
                            logger.log_scalar(metric, x)
                            x += random.randint(-1, 1)
                        logger.close()
            ```
        3. Now you should see your metrics on [Alchemy](https://alchemy.host/).
        
        ## Example
        
        For mode detailed tutorials, please follow [Catalyst examples](https://github.com/catalyst-team/catalyst/tree/master/examples#tutorials).
        
Keywords: Machine Learning,Deep Learning,PyTorch
Platform: UNKNOWN
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.5.0
Description-Content-Type: text/markdown
