Merck / Merck/DeepNeuralNet-QSAR

About DeepNeuralNet-QSAR

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Dominant language
Python
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Forks
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Description

Saving the trained Neural Net to models/multi_sparse_1/DeepNeuralNetParameters.npz
Traceback (most recent call last):
File "DeepNeuralNetTrain.py", line 555, in
main()
File "DeepNeuralNetTrain.py", line 534, in main
num.savez(saveModelPath, **NNParametersDict);
File "/root/miniconda3/envs/my-env/lib/python2.7/site-packages/numpy/lib/npyio.py", line 595, in savez
_savez(file, args, kwds, False)
File "/root/miniconda3/envs/my-env/lib/python2.7/site-packages/numpy/lib/npyio.py", line 714, in _savez
format.write_array(fid, np.asanyarray(val),
File "/root/miniconda3/envs/my-env/lib/python2.7/site-packages/numpy/core/numeric.py", line 544, in asanyarray
return array(a, dtype, copy=False, order=order, subok=True)
File "/root/DeepNeuralNet-QSAR-master/gnumpy.py", line 1059, in iter
for i in tuple(xrange(len(self))): yield self[i]
File "/root/DeepNeuralNet-QSAR-master/gnumpy.py", line 1026, in getitem
ret = self[selectors[:axisI] + (_short_slice(_read_single_index(axisSelector, axisLen)),)] .reshape(_deleteT2(self.shape, axisI))
File "/root/DeepNeuralNet-QSAR-master/gnumpy.py", line 1045, in getitem
if axisI==0: return garray(_cm_row_slice_read(self._base_shaped(1), sFrom, sTo), retShape, self) # slice on axis 0 is free, using _cm_row_slice_read
File "/root/DeepNeuralNet-QSAR-master/gnumpy.py", line 587, in _base_shaped
def _base_shaped(self, nDimsAsRows): return _cm_reshape(self._base, (_prodT(self.shape[:nDimsAsRows]), _prodT(self.shape[nDimsAsRows:])))
File "/root/DeepNeuralNet-QSAR-master/gnumpy.py", line 165, in _cm_reshape
else: return cm.reshape(tuple(reversed(newShape)))
File "/root/DeepNeuralNet-QSAR-master/npmat.py", line 99, in reshape
self.numpy_array.resize(*shape)
ValueError: resize only works on single-segment arrays

I have this problem during the training of the model, how can I solve it?
I would appreciate if you can reply!

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First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start at the model-saving call in DeepNeuralNetTrain.py around line 534, then trace the reshape path through gnumpy.py and npmat.py, especially npmat.py line 99. Reproduce the training save step and identify why resize receives a non-single-segment array; done when the trained model saves without the reported ValueError.

Written by the indexing model from the issue text.

Assessment

Tech stack
numpy, python
Domain
machine-learning
Issue type
Bug
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

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