Comments (5)
v0.3.0 support Python 3
Original comment by [email protected]
on 11 Feb 2014 at 2:26
- Changed state: Fixed
from neurolab.
Wonderful! Thanks for the heads up.
Original comment by [email protected]
on 11 Feb 2014 at 3:27
from neurolab.
Oops! I spoke too soon. Tried to install with 3.2 and got this error...any
ideas about what I am doing wrong?
pi@raspdev ~ $ pip-3.2 install neurolab
Downloading/unpacking neurolab
Downloading neurolab-0.3.0.tar.gz (206Kb): 206Kb downloaded
Running setup.py egg_info for package neurolab
Traceback (most recent call last):
File "<string>", line 14, in <module>
File "/home/pi/build/neurolab/setup.py", line 1
""" Setup file for neurolab package """
^
SyntaxError: invalid character in identifier
Complete output from command python setup.py egg_info:
Traceback (most recent call last):
File "<string>", line 14, in <module>
File "/home/pi/build/neurolab/setup.py", line 1
""" Setup file for neurolab package """
^
SyntaxError: invalid character in identifier
Original comment by [email protected]
on 13 Feb 2014 at 12:06
from neurolab.
Try Now, I fix setup.py (ver 0.3.1)
Fuck Py3;)
Original comment by [email protected]
on 13 Feb 2014 at 9:32
from neurolab.
You have done it! Installed successfully. Had to add Scipy for Py3 and
then ran the demo program and all is well.
Thanks for your help. As far as I know you are the only NN out there that
works with Py3.
Original comment by [email protected]
on 13 Feb 2014 at 4:36
from neurolab.
Related Issues (20)
- Failing to add Levenberg-Marquardt-training HOT 5
- Problem when using a modified network property HOT 1
- feedforward network not learning HOT 12
- PureLin in outputl layer does not work HOT 2
- Setup issue HOT 3
- strange result HOT 13
- Learning Rate is not present HOT 2
- Multiprocessing can not pickle unbound function HOT 6
- cannot save nn HOT 2
- output norm and different resutls HOT 1
- Citing neurolab HOT 3
- Parameters Ignored in Training Function Construction HOT 2
- Training Fails for Non-Default Activation Functions HOT 1
- Linear Activation Leads to NaN minmax HOT 2
- Support for weight decay (regularization parameter) HOT 2
- Missing newelm example in doc HOT 3
- fmin_bfgs() got an unexpected keyword argument 'lr', train func does not take lr as parameter HOT 2
- Added regularization and cross-entropy error to Neurolab HOT 5
- 0.3.5 version not available in pypi HOT 1
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from neurolab.