Comments (7)
This also means clstmimg.cc
is not used at all.
https://github.com/tmbdev/clstm/search?utf8=%E2%9C%93&q=d_inputs
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The Python wrapper can be built after deleting the d_inputs
and d_outputs
fields from INetwork
in clstm.i
. Then in IPython, running net.backward()
outputs Kernel died, restarting
.
from clstm.
Adding d_inputs
and d_outputs
to the INetwork
in both clstm.h
and clstm.i
still has the same problem.
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Yes, I'm in the middle of converting to Eigen::Tensor. I should probably have created a branch, but I had hoped it would go a bit quicker than it has.
Use tag a588c8 for now.
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The tag is the same version that caused the above errors. The backward method can't run.
net.backward()
Kernel died, restarting
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Let me see whether I can track down an older working version and set up the branches so that that becomes the default branch.
from clstm.
The Python swig code has been updated; there is a small test case (test-lstm.py) now.
There is also a separate branch now for the old version with separate derivatives.
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Related Issues (20)
- core dumped, w != 0 failed
- Missing last char of the line. HOT 4
- Sort and Sed commands are causing the model not to train (ERROR 1/OUT is empty) HOT 2
- Arabic 800,000 model cant go below Error Rate 0.5 HOT 4
- Always missing one character in the output HOT 3
- Can I use this tool to do scene text detection + recognition ? HOT 2
- Is it possible to train multiple languages on a one model file ? HOT 6
- Error in training uw3-500
- clstmocr - error opening clstm file (trained model) HOT 8
- Segmentation fault when running clstmocr on pre-trained model HOT 1
- Error while using clstm models that I trained and test it !
- I want to use gpu to speed up training model! How do I do, I follow the previous issu to do but failed
- error: use of undeclared identifier 'environ' HOT 6
- How to optimally prepare the data
- Segmentation Fault when running tests HOT 1
- Inaccurate training
- question: clstmocrtrain on GPU
- How to make predictions using python code
- Is there a graphical depiction of the model being used/trained here? HOT 4
- question HOT 2
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