Metadata-Version: 2.1
Name: padl
Version: 0.2.0
Summary: Pipeline abstractions for deep learning
Home-page: https://github.com/lf1-io/padl
Author: LF1
Author-email: contact@lf1.io
License: Apache 2.0
Description: # PADL
        
        
        ![License](https://img.shields.io/badge/License-Apache_2.0-blue.svg) 
        
        # Pipeline Abstractions for Deep Learning
        
        
        Full documentation here: https://lf1-io.github.io/padl/
        
        **PADL**:
        
        - is a pipeline builder for **PyTorch**.
        - may be used with all of the great **PyTorch** functionality you're used to for writing layers.
        - allows users to build pre-processing, forward passes, loss functions **and** post-processing into the pipeline.
        - models may have arbitrary topologies and make use of arbitrary packages from the python ecosystem.
        - allows for converting standard functions to **PADL** components using a single keyword `transform`.
        
        **PADL** was developed at [LF1](https://lf1.io/), an AI innovation lab based in Berlin, Germany.
        
        
        ## Getting Started
        
        ### Installation
        
        ```
        pip install padl
        ```
        
        PADL currently supports python **3.7**, **3.8** and **3.9**.
        
        Python version >= **3.8** is preferred because creating and loading transforms (**not** execution) 
        can be slower in **3.7**.
        
        ### Your first PADL program
        
        ```python
        from padl import transform, batch, unbatch
        import torch
        from torch import nn
        nn = transform(nn)
        
        @transform
        def prepare(x):
            return torch.tensor(x)
        
        @transform
        def post(x):
            return x.topk(1)[1].item()
        
        my_pipeline = prepare >> batch >> nn.Linear(10, 20) >> unbatch >> post
        ```
        ### Try out PADL in Colab notebooks
        1. [MNIST](https://colab.research.google.com/github/lf1-io/padl/blob/main/notebooks/01_MNIST_using_padl.ipynb#scrollTo=bd560eb8)
        2. [Simple NLP example](https://colab.research.google.com/github/lf1-io/padl/blob/main/notebooks/02_nlp_example.ipynb)
        3. [Sentiment Analysis - NLP](https://colab.research.google.com/github/lf1-io/padl/blob/main/notebooks/03_Sentiment_Analysis_with_padl.ipynb)
        
        ### Resources
        
        - Read the documentation at <https://lf1-io.github.io/padl/>.
        - Find examples at <https://github.com/lf1-io/padl/tree/main/notebooks>.
        - Post issues at <https://github.com/lf1-io/padl/issues>.
        
        
        
        ## Contributing
        
        Code of conduct: https://github.com/lf1-io/padl/blob/main/CODE_OF_CONDUCT.md
        
        If your interested in contributing to PADL please look at the current issues: https://github.com/lf1-io/padl/issues
        
        
        
        ## Licensing
        
        PADL is licensed under the Apache License, Version 2.0. See LICENSE for the full license text.
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.7
Description-Content-Type: text/markdown
