A lightweight module for Multi-Task Learning in pytorch
Project description
A lightweight module for Multi-Task Learning in pytorch.
torchmtl tries to help you composing modular multi-task architectures with minimal effort. All you need is a list of dictionaries in which you define your layers and how they build on each other. From this, torchmtl constructs a meta-computation graph which is executed in each forward pass of the created MTLModel. To combine outputs from multiple layers, simple wrapper functions are provided.
Installation
torchmtl can be installed via pip:
pip install torchmtl
Quickstart
Assume you want to use two different embeddings of your input, combine them and then solve different prediction tasks.
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