kevinid / molecule_generator Goto Github PK

how can i get Bemis-Murcko scaffolds and ring assemblies in my own dataset？

This smart is in the structural alert list. This means that all esters are unwanted structures. Is that so, or the '#6' should be removed from the first square bracket. At this time, it means that compounds like carbonates are containning the alert structures. Thanks!

Hi! Thanks for providing the source code. I've been trying to get the mx_net implementation to work on an M1 Macbook Pro on Google Colab, since there were quite some issues with the MXNet + Cuda integration locally. I've made the neccesary changes where needed, adapted the imports of the files, but when trying to run the training code, it gives the following error in Colab:

!python3 train.py scaffold /content/molecule_generator

Traceback (most recent call last):
File "/content/molecule_generator/train.py", line 535, in
_engine(**params)
File "/content/molecule_generator/train.py", line 146, in _engine
inputs = [next(it_train) for _ in range(len(gpu_ids))]
File "/content/molecule_generator/train.py", line 146, in
inputs = [next(it_train) for _ in range(len(gpu_ids))]
File "/usr/local/lib/python3.10/dist-packages/mxnet/gluon/data/dataloader.py", line 689, in iter
for item in t:
File "/usr/local/lib/python3.10/dist-packages/mxnet/gluon/data/dataloader.py", line 484, in next
batch = pickle.loads(ret.get(self._timeout))
File "/usr/lib/python3.10/multiprocessing/pool.py", line 774, in get
raise self._value
File "/usr/lib/python3.10/multiprocessing/pool.py", line 540, in _handle_tasks
put(task)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 206, in send
self._send_bytes(_ForkingPickler.dumps(obj))
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 51, in dumps
cls(buf, protocol).dump(obj)
File "/usr/lib/python3.10/multiprocessing/pool.py", line 643, in reduce
raise NotImplementedError(
NotImplementedError: pool objects cannot be passed between processes or pickled

I was wondering if anyone else had a similar error, and whether someone manages to fix this one.

I converted the entire code into Python-3.7 using 2to3 package provided by Python. While running the converted code, I got following error:
AttributeError: Can't pickle local object '_engine.<locals>.<lambda>'

Complete error is as follows:

$ ./train.py molmp logs
Traceback (most recent call last):
  File "./train.py", line 551, in <module>
    _engine(**params)
  File "./train.py", line 133, in _engine
    inputs = [next(it_train) for _ in range(len(gpu_ids))]
  File "./train.py", line 133, in <listcomp>
    inputs = [next(it_train) for _ in range(len(gpu_ids))]
  File "/home/iit/anaconda3/envs/kevinid_experiments/lib/python3.7/site-packages/mxnet/gluon/data/dataloader.py", line 505, in __next__
    batch = pickle.loads(ret.get(self._timeout))
  File "/home/iit/anaconda3/envs/kevinid_experiments/lib/python3.7/multiprocessing/pool.py", line 657, in get
    raise self._value
  File "/home/iit/anaconda3/envs/kevinid_experiments/lib/python3.7/multiprocessing/pool.py", line 431, in _handle_tasks
    put(task)
  File "/home/iit/anaconda3/envs/kevinid_experiments/lib/python3.7/multiprocessing/connection.py", line 206, in send
    self._send_bytes(_ForkingPickler.dumps(obj))
  File "/home/iit/anaconda3/envs/kevinid_experiments/lib/python3.7/multiprocessing/reduction.py", line 51, in dumps
    cls(buf, protocol).dump(obj)
AttributeError: Can't pickle local object '_engine.<locals>.<lambda>'

Can someone please help me resolve this issue?

When I run the example codes as follows

# loading models
mol_mp = builders.Vanilla_Builder('ckpt/molmp_0/', gpu_id=0)
res = mol_mp.sample(100)

I got the error info as follows:

[09:24:17] Can't kekulize mol.  Unkekulized atoms: 1 2 3 5 7 8 9 11 12 13 17

RDKit ERROR: [09:24:17] Can't kekulize mol.  Unkekulized atoms: 1 2 3 5 7 8 9 11 12 13 17
RDKit ERROR: 
[09:24:17] Can't kekulize mol.  Unkekulized atoms: 3 5 7

RDKit ERROR: [09:24:17] Can't kekulize mol.  Unkekulized atoms: 3 5 7
RDKit ERROR: 
[09:24:22] Can't kekulize mol.  Unkekulized atoms: 3 4 5 6 8 9 10 11 12 13 27

RDKit ERROR: [09:24:22] Can't kekulize mol.  Unkekulized atoms: 3 4 5 6 8 9 10 11 12 13 27
RDKit ERROR: 
[09:24:22] Explicit valence for atom # 38 N, 4, is greater than permitted
RDKit ERROR: [09:24:22] Explicit valence for atom # 38 N, 4, is greater than permitted
98

Is this a normal phenomenon? Many thanks.

Additional Files

Additional file 1 — Supplementary Text
Containing additional information about the model architecture and
implementation details of experiments.

Additional file 2 — Supplementary Figures
Containing supplementary figures.

Unable to find model.json and trainer.json files for tensorflow mg branch.

I run exmples.ipynb, but received error message like this
No module named 'utils'

I found file utils.py at /data/ folder. Can you tell me why?
I am using python 3.5

Thanks

I only found tf_mg, but your example file still uses mxnet

I am trying to work my way through the tf branch of the code. How do I run the branch using tensorflow?

Hi, I can not find the file"datasets/atom_types.txt", would you mind uploading this file to your program?