Version control for software 2.0

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Documentation: stockroom.page

Slack: #stockroom

Twitter: @tensorwerk

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Introduction

Stockroom is a platform to version models, data, parameters, experiment artifacts etc. alongside git versioned source code.

• It is easy. The APIs are very similar to dictionaries in python
• It works alongside Git - in case you need to version source code as well. It's OK if you don't.
• High performance, thanks to the amazing hangar library
• Integration with PyTorch and its ecosystem, so that you don't need to write the complex pipeline code.

Why

One important motivation behind the initial design of stockroom is to avoid users learning another tool for versioning. We try to make the APIs as minimal and familiar as possible. Similar to other versioning tools, stockroom let "git" does checkout and rely on "git" to move between branches/commits. But unlike other tools, we channel your data access through the smart API so that we don't need to move the huge data files around when you traverse between commits.

Installation

$ pip install stockroom

Example

from stockroom import StockRoom

stock = StockRoom(enable_write=True)
model.load_state_dict(stock.model['resnet50'])
for e in range(epochs):
    for i in range(limit):
        optimizer.zero_grad()
        x, y = stock.data['dataset_name', i]
        out = model(x)
        loss = criterion(out, y)
        loss.backward()
        optimizer.step()
        if loss < previous_loss:
            stock.experiment['loss'] = loss.item()
            stock.model['resnet50'] = model.state_dict()
            stock.commit('adding a better model')

Contributing

We'd love to have you in the contributors list. Do check out the contribution guide before submitting a PR. Here is our latest #Hall-Of-Fame

License

This project is licensed under the terms of the Apache Software License 2.0