def featurizing_smis(smi): featurized = featurizer(smi) return featurized
vectorized_featurizing = np.vectorize(featurizing_smis) array_of_feats = vectorized_featurizing(array_of_smis)
@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.
@MasunNabhanHoms_twitter Can you report more details about the error that you're seeing? I'm not sure what the issue is
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
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.
@Tonylac77 dataset.itersamples() might be what you’re looking for.