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If anyone from the dev team there, can you look into integrating the "make the research into production" part into allennlp. Facebook currently has fairseq, thi

If anyone from the dev team there, can you look into integrating the "make the research into production" part into allennlp. Facebook currently has fairseq, this and other nlp repos. Allennlp makes it easier to model most classes of NLP problems with a clean dependency injectable interface with most common tasks abstracted out cleanly.

smhx 8y ago
PyTorch dev here. We'll talk with the AllenNLP folks to see if we can make this can happen. We just released PyTorch 1.0 stable last Friday that adds stable production capabilities, so the stuff is just out of the oven. https://github.com/pytorch/pytorch/releases/tag/v1.0.0 https://github.com/pytorch/pytorch/releases/tag/v1.0.0
- joelgrus 8y ago
  AllenNLP dev here. We're going to do a "PyTorch 1.0" release of AllenNLP next week, and then after that we're planning to investigate how to incorporate the new "production" aspects.
  - smhx 8y ago
    win-win! collaboration via hacker news ;-)
  - Iamhisalt 8y ago
    Thanks for the book Joel!
  - sh33mp 8y ago
    Could you guys elaborate on the relationship between PyText, torchtext, and AllenNLP? I've briefly used the latter two, but with how quickly things are moving it'd be nice to have a quick answer from the devs themselves.
    - ahhegazy77 8y ago
      PyText dev here, Torchtext provides a set of data-abstractions that helps reading and processing raw text data into PyTorch tensors, at the moment we use Torchtext in PyText for training-time data reading and preprocessing. AllenNLP is a great NLP modeling library that is aimed at providing reference implementations and prebuilt state-of-the-art models, and make it easy to iterate on and research with models for different NLP tasks. We've built PyText to be a rich NLP modeling library (along the lines of AllenNLP) but with production capabilities baked in the design from day 1. Examples are: - We provide interfaces to make sure data preprocessing can be consistent between training and runtime - The model interfaces are compatible with ONNX and torch.jit - A core goal for us in the next few month is to be able to run models trained in PyText on mobile. Among other differences like supporting distributed training and multi-task learning. That being said, so far our library of models has been mostly influenced by our current production use-cases, we are actively working on enriching this library with more models and tasks while keeping production capabilities and inference speed in mind.
bethebunny 8y ago
AllenNLP is great, and influenced the design of PyText in several ways. There are some central design decisions of AllenNLP that make it incompatible with PyTorch's jit tracing and so make productionizing models require much more manual work. It also generally leaves preprocessing up to the user, so preprocessing consistently between training and inference is outside the scope of what AllenNLP does.

smhx 8y ago

PyTorch dev here. We'll talk with the AllenNLP folks to see if we can make this can happen. We just released PyTorch 1.0 stable last Friday that adds stable production capabilities, so the stuff is just out of the oven. https://github.com/pytorch/pytorch/releases/tag/v1.0.0 https://github.com/pytorch/pytorch/releases/tag/v1.0.0

joelgrus 8y ago
AllenNLP dev here. We're going to do a "PyTorch 1.0" release of AllenNLP next week, and then after that we're planning to investigate how to incorporate the new "production" aspects.
- smhx 8y ago
  win-win! collaboration via hacker news ;-)
- Iamhisalt 8y ago
  Thanks for the book Joel!
- sh33mp 8y ago
  Could you guys elaborate on the relationship between PyText, torchtext, and AllenNLP? I've briefly used the latter two, but with how quickly things are moving it'd be nice to have a quick answer from the devs themselves.
  - ahhegazy77 8y ago
    PyText dev here, Torchtext provides a set of data-abstractions that helps reading and processing raw text data into PyTorch tensors, at the moment we use Torchtext in PyText for training-time data reading and preprocessing. AllenNLP is a great NLP modeling library that is aimed at providing reference implementations and prebuilt state-of-the-art models, and make it easy to iterate on and research with models for different NLP tasks. We've built PyText to be a rich NLP modeling library (along the lines of AllenNLP) but with production capabilities baked in the design from day 1. Examples are: - We provide interfaces to make sure data preprocessing can be consistent between training and runtime - The model interfaces are compatible with ONNX and torch.jit - A core goal for us in the next few month is to be able to run models trained in PyText on mobile. Among other differences like supporting distributed training and multi-task learning. That being said, so far our library of models has been mostly influenced by our current production use-cases, we are actively working on enriching this library with more models and tasks while keeping production capabilities and inference speed in mind.

bethebunny 8y ago

AllenNLP is great, and influenced the design of PyText in several ways. There are some central design decisions of AllenNLP that make it incompatible with PyTorch's jit tracing and so make productionizing models require much more manual work. It also generally leaves preprocessing up to the user, so preprocessing consistently between training and inference is outside the scope of what AllenNLP does.