Metadata-Version: 2.1
Name: alchemy-catalyst
Version: 20.3
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
Download-URL: https://github.com/catalyst-team/alchemy
Project-URL: Bug Tracker, https://github.com/catalyst-team/alchemy/issues
Project-URL: Documentation, https://catalyst-team.github.io/alchemy
Project-URL: Source Code, https://github.com/catalyst-team/alchemy
Keywords: Machine Learning,Deep Learning,PyTorch
Platform: UNKNOWN
Classifier: Environment :: Console
Classifier: Natural Language :: English
Classifier: Development Status :: 4 - Beta
Classifier: Operating System :: OS Independent
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: System :: Logging
Classifier: Topic :: System :: Monitoring
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: Implementation :: CPython
Requires-Python: >=3.5.0
Description-Content-Type: text/markdown
Requires-Dist: requests (==2.22.0)


<div align="center">

![Alchemy logo](https://raw.githubusercontent.com/catalyst-team/catalyst-pics/master/pics/alchemy_logo.png)

**Experiments logging & visualization**

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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

    # insert your personal token here
    token = "..."
    project = "default"

    for gid in range(1):
        group = f"group_{gid}"
        for eid in range(2):
            experiment = f"experiment_{eid}"
            logger = Logger(
                token=token,
                experiment=experiment,
                group=group,
                project=project,
            )
            for mid in range(4):
                metric = f"metric_{mid}"
                # let's sample some random data
                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/).


## Catalyst.Ecosystem

1. Goto [Alchemy](https://alchemy.host/) and get your personal token.

2. Log your Catalyst experiment with **AlchemyRunner**:
    ```python
    from catalyst.dl import SupervisedAlchemyRunner
    runner = SupervisedAlchemyRunner()

    runner.train(
        model=model,
        criterion=criterion,
        optimizer=optimizer,
        loaders=loaders,
        logdir=logdir,
        num_epochs=num_epochs,
        verbose=True,
        monitoring_params={
            "token": "...",  # insert your personal token here
            "project": "default",
            "experiment": "your_experiment_name",
            "group": "your_experiment_group_name",
        }
    )
    ```
3. Now you should see your metrics on [Alchemy](https://alchemy.host/).

## Examples

For mode detailed tutorials, please follow [Catalyst examples](https://github.com/catalyst-team/catalyst/tree/master/examples#tutorials).


