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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