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    Bharath Ramsundar
    @rbharath
    @paulsonak There's some interest! We're working towards establishing a modelhub and adopting some common framework like ONNX/PMML for weight storage would be useful. We don't have any infrastructure for this yet though. See the discussion https://forum.deepchem.io/t/a-sketch-of-a-modelhub/445
    1 reply
    Karthik Viswanathan
    @nickinack
    Hey, I am trying to reproduce a paper that requires the following version of deepchem: https://github.com/deepchem/deepchem/tree/july2017. Unfortunately, this link is inactive. How do I download and use this version?
    Bharath Ramsundar
    @rbharath
    That was released in July 2017
    Karthik Viswanathan
    @nickinack
    @rbharath Thank you very much :) I also wanted to ask how the ConvMolFeaturizer() works. Do you have any documentation which explains how the featurisation takes place?
    alat-rights
    @alat-rights
    Yup! That should be in our documentation pages. Have you looked under featurizers? deepchem.readthedocs.io/ @nickinack
    Karthik Viswanathan
    @nickinack
    Yess :) I looked into it and it was very insightful. Thank you for the support :)
    9H-Fluorene (Kasitinard M.)
    @ninehfluorene:matrix.org
    [m]
    i have a question in the future is deepchem gonna have progress bar (for example tensorflow has verbose progress bar when it train)
    Omid Tarkhaneh
    @OmidTarkhaneh
    I want to design new efficient model based on DeepChem and (keras or pycharm) is there any resources help me for this aim??
    Atreya Majumdar
    @atreyamaj

    @OmidTarkhaneh There are layers defined within Deepchem from Keras etc, they can be found here: https://deepchem.readthedocs.io/en/latest/api_reference/layers.html

    These can be used like how you would use Keras

    Omid Tarkhaneh
    @OmidTarkhaneh
    @atreyamaj Thanks a lot for your help. Is there any resources which help how to preprcoess datasets related to the chemistery. My datasets are kind of DUDE datasets (structural datasets) and I should change in a way suitable for DeepChem
    Bharath Ramsundar
    @rbharath
    @ninehfluorene:matrix.org Good question. We don't have plans for this at present but it would be a useful feature to add
    @OmidTarkhaneh Check out our tutorial series (click tutorials on deepchem.io). Some of the the tutorials may be relevant for your work
    Abhik Seal
    @abhik1368
    Where did the from deepchem.models.tensorgraph.layers import Label, Weights go ? Can anyone help, i used it a year ago and now latest version things have changed
    Bharath Ramsundar
    @rbharath
    @abhik1368 TensorGraph was our old framework for building models (basically a custom version of keras). We've ported all our models to just use Keras directly. You can get the available layers from deepchem.models.layers now
    Abhik Seal
    @abhik1368
    I want to run a standard regression like solubility can you point me to an example ?
    Abhik Seal
    @abhik1368
    Can you show how to load a dataset and use the latest code to train and test , any links ? I want to use atom_features, degree_slice, membership as features
    2 replies
    9H-Fluorene (Kasitinard M.)
    @ninehfluorene:matrix.org
    [m]
    or you want to custom dataset?
    example
    qm9 have 20 rebel but you want just 15 rebel
    make seperate for train,test,valid (50:30:20)
    normalization , make you own model with tensorflow
    9H-Fluorene (Kasitinard M.)
    @ninehfluorene:matrix.org
    [m]
    This is interesting i just found paper that working on QM9 prediction and just find out that order to improve on loss (mae) i should do data clean up (decrease Noise on data) and add more features (for example group up some of molecules that similar etc.)
    https://pubs.acs.org/doi/10.1021/acs.jpca.0c05969
    9H-Fluorene (Kasitinard M.)
    @ninehfluorene:matrix.org
    [m]
    And it bag a question in the future of deepchem molnet is there are gonna be improved version of any database (for example qm9_v2 or something like that) what do you think if this concept ?
    AshW360
    @AshW360
    Hi, how do we separate compounds from .csv file with water solubility?
    Omid Tarkhaneh
    @OmidTarkhaneh
    I am looking for some papers with their code using deepchem for potential energy prediction, if any I wonder someone send me. Thanks in advance.
    Omid Tarkhaneh
    @OmidTarkhaneh
    In the past we used import deepchem.models.tensorgraph.layers as layers for defining our arbitrary architecture in deepchem, now when I am going to use this I can not. Is there any sugesstion, thank you.
    9H-Fluorene (Kasitinard M.)
    @ninehfluorene:matrix.org
    [m]
    @AshW360: if you mean delaney dataset you can use pandas 'drop' , here the example from my code
    Atreya Majumdar
    @atreyamaj
    @OmidTarkhaneh something like this might work:
    layer = dc.models.layers.GraphConv(64)
    Omid Tarkhaneh
    @OmidTarkhaneh
    @atreyamaj Thanks a lot for your help.
    Atreya Majumdar
    @atreyamaj
    :D
    9H-Fluorene (Kasitinard M.)
    @ninehfluorene:matrix.org
    [m]
    after i drop label (properties) from 15 to just 3 label my loss is increse from 0.6XXX to 0.80XX this is really nice
    i reference activation function vs property tabel is really gone up
    https://www.sciencedirect.com/science/article/abs/pii/S0255270120306358
    (LUMO, energy gap (E gap) and dipole moment (u) in QM9)
    Omid Tarkhaneh
    @OmidTarkhaneh
    @ninehfluorene: Can you share the source code of the paper??
    3 replies
    9H-Fluorene (Kasitinard M.)
    @ninehfluorene:matrix.org
    [m]
    by used tensorflow
    Bharath Ramsundar
    @rbharath
    Hey folks, I'm mostly offline this week (my wedding is at the end of the week) so won't be able to answer many questions here. I'll be back online as usual mid next week
    2 replies
    Arthur Funnell
    @elemets
    Best wishes!
    Omid Tarkhaneh
    @OmidTarkhaneh
    hello. Is anyone help how can I work with CML and XML datasets. I have some xml datasets but do not know how to feed network with them
    Vignesh Venkataraman
    @VIGNESHinZONE
    Hi @OmidTarkhaneh
    At present, I don't think deepchem provides any featurization support for XML datasets but I was curious, Are you by any chance working on OPSIN datasets(They also happen to be XML representations of Molecules)?
    Omid Tarkhaneh
    @OmidTarkhaneh
    @VIGNESHinZONE Hi. Thanks for your response. No my datasets are related to DUDE
    Masun Nabhan Homsi
    @MasunNabhanHoms_twitter
    Hello!, I am rerunning in Google-colab a script that I programmed it with Deepchem two months ago, but now when I run it the colab's session is crashing.
    I can run another script that uses a different deep neural network library without any problem. Please, give me some hints to solve this this problem. Thank you.
    James Y
    @yuanjames
    Does anyone have the idea for improving GPU utility?
    ignaczgerg
    @ignaczgerg
    Hi all, is there any news regarding the migration to python=3.8/3.9?
    Arthur Funnell
    @elemets
    Hey does anyone know a way of featurizing molecules quickly? e.g. vectorized featurization, specifically with the WeaveFeaturizer? I have ~500k molecules I'd like to train on...
    Bharath Ramsundar
    @rbharath
    Sorry just starting to come back online
    I'll try to work backwords and answer questions
    @elemets You should definitely be able to featurize 500K compounds on a decent CPU. I've featurized 1M+ datasets within an hour or two. What issues are you seeing?
    @ignaczgerg I'm currently working on this! I was offline most of the last week but just starting to come back online and get to work on the migration. I'll post more information soon
    @MasunNabhanHoms_twitter Can you report more details about the error that you're seeing? I'm not sure what the issue is
    @yuanjames I think GPU utilization should be pretty good for most models, from 50-90%. Which models are you seeing poor utilization with?