Closed loretoparisi closed 2 years ago
@loretoparisi @saikumarchalla I am willing to contribute in this project and I have huge amount of labelled data as well to test this model and improve this model further if needed by collabing with other collaborators of tensorflow NLP models.Please assigned this issue to me. Regards!
@loretoparisi @yugaljain1999 Thanks for your interest on this model. Can you clarify a bit more on your feature request? My understanding is you are requesting to open source pQRNN model.
Welcome to create your own model based what we open sourced here, and use it anywhere (don't forget to tell us the result and impact if it's sharable)
We are working on TF2 + keras version of PRADO and pQRNN, which may cause significant code structure change on current codebase.
If you'd like to make your model merged to this code base to make your contribution more widely visible, be sure to talk with before creating the PR
@thunderfyc Yes, my specific request is about to open source the pQRNN
model as you just did for PRADO
(thanks for that!).
@thunderfyc I agree with @loretoparisi , my request is also about to open source pQRNN as it is next level version of PRADO and nicely worked on various datasets..
@loretoparisi How did u run PRADO model on your system as I am running on google colab and getting error related to bazel which I tried to install using build in commands in colab but even then it didn't run as it should. Can u please help me to resolve bazel error? Thanks!
@yugaljain1999 let me check it out.
@loretoparisi Have u find any way to run PRADO model? I am facing an issue in importing one module because it actually doesn't exist in original files but in runner.py it's written.
@loretoparisi @thunderfyc I got "no module found named tf_ops "error while running prado_model.py.
Error is in the line number 25 from tf_ops import sequence_string_projection_op as ssp
I couldn't get any info regarding tf_ops ,from where it came out as tf_ops.py is not any file which exist in directory named "prado".
Do you how to import tf_ops to solve this error? It would be great help.
Thanks.
Hi @thunderfyc I just wanted to check if there was any progress on the plans to open source the pQRNN (TF2 + keras) model? Was just curious about the rough timeline, if you had one. Thanks!
We are open sourcing PRADO (TF2 + keras) in the next couple of weeks. pQRNN is likely six months away.
@prabhukaliamoorthi Thanks on the general timeline! I Would love to try the model when its in TF2 + keras, if possible with custom dataset (non english).
@yugaljain1999 I succeeded in running it in google colab with bazel instructions. You can check out the first part of notebook I used to recreate the runtime environment: https://colab.research.google.com/drive/1XXwlZyYPnmVFtmwqWDrqZg9TFfgT02Ya?usp=sharing
@Gorluxor Thankyou so much for your notebook, it would really help me a lot. Can I run this notebook on GPU as well ? Thanks!
@yugaljain1999 When I ran it in a gpu environment, it said it isn't utilized, so I believe it's not useful at all. On the other hand when you run the training, it has references to TPU (so either TPU or just cpu). Overall I find the general process quite strange compared to normal training tf/keras models (at least for me).
@Gorluxor you are right I also find it strange when I ran this on GPU and it was throwing an error when running on GPU during training. Can I save weights after training this model on TPU as I didn't run any model on TPU till now and load those weights when using for deployment or production? Thanks!
@yugaljain1999 Wouldn't know to help you with that, as I don't know much about bazel or how is this running in the background. I wanted to try it myself yesterday, so that is why I figured out the environment. Still would not know how to change it to use my dataset for NER problem.
@Gorluxor no problem, I will myself too to load weights of this model trained on TPU and try to fit my data. Thanks a lot.
@yugaljain1999 On which dataset are you trying to train it on (saw that you said you have a huge amount of labeled data)? And what are you trying to predict? Plus did you manage to easily change the dataset to fit the model?
The keras+TF2 version is out.
@prabhukaliamoorthi That's great - could you please post the link to the model/code here if possible? Thanks!
@prrao87 I assume, this is the revised code https://github.com/tensorflow/models/tree/master/research/seq_flow_lite, just that it changed name under models
Is there any update on the pQRNN model release timeline? Thanks!
Yes, it's released but unofficially. If you want I can share repo. Thanks
On Thu, Mar 4, 2021, 4:15 AM jasonw247 notifications@github.com wrote:
Is there any update on the pQRNN model release timeline? Thanks!
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@yugaljain1999 that would be great, thanks!
Here is the repo - https://github.com/ChenghaoMou/pytorch-pQRNN
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@yugaljain1999 https://github.com/yugaljain1999 that would be great, thanks!
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Hi everyone! Has the official model (trained model and code) for PQRNN been released yet? Or are there any plans for doing so?
There are unofficial implementations, but are there any plans for releasing the official one?
Thank you!
Hi everyone! Has the official model (trained model and code) for PQRNN been released yet? Or is there any plans for doing so? There are unofficial implementations, but is there any plans for releasing the official one? Thank you!
We're working towards releasing them in Q4.
Can we close this issue? An opensourced version of PQRNN has been merged (#10475 )
definitely!
Prerequisites
Please answer the following question for yourself before submitting an issue.
1. The entire URL of the file you are using
https://github.com/tensorflow/models/tree/master/research/sequence_projection
2. Describe the feature you request
Release the PRADO generation model for pQRNN.
3. Additional context
Inference on large or medium size documents currently needs high end machines to handle in memory vectors for BERT like models. Only recent advancements in tokenization (SentencePiece, etc.) made it possible to speed up inference time, but not the model inference time itself.
4. Are you willing to contribute it? (Yes or No)
Yes