Hi all, are there any plans (or existing implementations) for exporting deepchem models into a standard format such as ONNX or PMML?
@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
@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
@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
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
@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
I want to run a standard regression like solubility can you point me to an example ?
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
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 ?
Hi, how do we separate compounds from .csv file with water solubility?
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.
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.
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
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
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)?
@VIGNESHinZONE Hi. Thanks for your response. No my datasets are related to DUDE
Masun Nabhan Homsi
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.
Does anyone have the idea for improving GPU utility?
Hi all, is there any news regarding the migration to python=3.8/3.9?
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...
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?