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    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?
    Arthur Funnell
    @elemets
    @rbharath Thanks, I guess I'm using an inefficient method then? It's taken over 8 hours to featurize 600k SMILES. Given they are peptides so are quite long if that makes a difference?
    The code I am using to featurize is:
    def featurizing_smis(smi):
        featurized = featurizer(smi)
        return featurized
    Should I be using a pandas loop instead?
    vectorized_featurizing = np.vectorize(featurizing_smis)
    array_of_feats = vectorized_featurizing(array_of_smis)
    ignaczgerg
    @ignaczgerg

    @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

    @rbharath That is awesome, thank you! If I could help with anything regarding this, I am more than happy to help.

    Bharath Ramsundar
    @rbharath
    @elemets Ah, being peptides would explain the slowdown! The numbers I mentioned above are for small molecules. Featurization time is either linear or quadratic in molecular length (depending on featurization) so there will definitely be a slowdown. Weave is quadratic, but convmol is linear so perhaps it might be useful to experiment with different featurizations?
    @ignaczgerg Will do! I'll be posting issues and updates at deepchem/deepchem#2512 as I work on the upgrades
    James Y
    @yuanjames
    @rbharath Thanks, from deepchem.models import GCNModel, I am using RTX 3090, it only gives me 2% utility. and deepchem.models.GraphConvModel is around 10%, but MPNN from pytorch could reach 70% all on delaney datasets.
    1 reply
    Akhil Pandey
    @akhilpandey95
    @rbharath what is a good place to start for implementing bayesian GCN using deepchem ?
    Masun Nabhan Homsi
    @MasunNabhanHoms_twitter
    @MasunNabhanHoms_twitter Can you report more details about the error that you're seeing? I'm not sure what the issue is
    @rbharath
    When it crashes, it say "Session crashes with no reason". The log messages are :
    WARNING:root:kernel dab80b04-c3b5-45ae-827c-33975f71d502 restarted
    KernelRestarter: restarting kernel (1/5), keep random ports 2021-06-04 08:15:54.625105: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0
    Akhil Pandey
    @akhilpandey95
    Can anyone help me on this ?
    :point_up:
    su-chao
    @su-chao
    NotImplementedError: Cannot convert a symbolic Tensor (gradient_tape/private__graph_conv_keras_model/graph_gather/sub:0) to a numpy array. This error may indicate that you're trying to pass a Tensor to a NumPy call, which is not supported
    how to deal this Error?
    ignaczgerg
    @ignaczgerg

    NotImplementedError: Cannot convert a symbolic Tensor (gradient_tape/private__graph_conv_keras_model/graph_gather/sub:0) to a numpy array. This error may indicate that you're trying to pass a Tensor to a NumPy call, which is not supported

    Hi, which python version are you using?
    I got this error when I accidentally used python=3.9 with deepchem. Try to downgrade to python=3.7 and you will be fine.

    su-chao
    @su-chao
    My version : Python 3.7.10 ; deepchem 2.5 ;tensorflow-gpu 2.41 @ignaczgerg
    su-chao
    @su-chao
    Where can I see the update logs about deepchem-version? I found some "import * "code can't work when run the examples files
    kingscolour
    @kingscolour
    Anyone know if dc=2.5.0 is incompatible with tf=2.5.0? On linux, dc would not import with tf-gpu=2.5.0: AttributeError: module 'deepchem' has no attribute 'data'
    I had to uninstall tf-gpu=2.5.0 and install tf=2.4.0 to resolve the error.
    Bharath Ramsundar
    @rbharath
    Sorry for the lack of responses folks
    I've been travellign and just starting to catch up
    @kingscolour Hmm, we don't support tf 2.5.0 right now (I hadn't realized it was out already!)
    We'll have to bump our versions but for now tf 2.4.0 is the same way to start
    1 reply
    Bharath Ramsundar
    @rbharath
    @su-chao Your error is basically due to numpy 1.20. Make sure you have numpy 1.19.5 installed. Tensorflow doesn't yet support numpy 1.20.*
    su-chao
    @su-chao
    Thanks! :)
    Masun Nabhan Homsi
    @MasunNabhanHoms_twitter
    @rbharath : please, any solution for colab problem (Session crash)? thank you
    Bharath Ramsundar
    @rbharath
    @MasunNabhanHoms_twitter Unfortunately I don't have a good idea for you right now! I'll keep an eye out and see if I come across this myself
    Tonylac77
    @Tonylac77
    Hi everyone, I am trying to do a k-fold split on my dataset, then convert all the folds to pandas dataframes. I've tried a for loop, iterating on a list of the folds but get the following error : 'DiskDataset' object is not iterable. Any ideas?
    alat-rights
    @alat-rights

    @Tonylac77 dataset.itersamples() might be what you’re looking for.

    For more info: https://deepchem.readthedocs.io/en/latest/api_reference/data.html#deepchem.data.DiskDataset

    Bharath Ramsundar
    @rbharath
    @Tonylac77 Can you share your code? I've definitely done something similar to what you're describing so I'm not sure what the difference is
    su-chao
    @su-chao
    @Tonylac77 In my ideas if you want use deepchem.model, you should use load_dataset to load you dataset, The ' deepchem.molnet.load_function.molnet_loader' hava a good explain and example
    davidRFB
    @davidRFB
    Hi I am tring yo run some local test for the inclusion of swissprot to molnet. However I am getting this error in the pytest execution :
    image.png
    I already add the function load_swissprot in swissprot_datasets.py
    I already add the line from deepchem.molnet.load_function.swissprot_datasets import load_swissprot
    in the init.py file of molnet
    I dont know if anyone can helpme
    davidRFB
    @davidRFB
    thank u very much
    Bharath Ramsundar
    @rbharath
    Oh this is weird
    Can you run other test files normally?