befelix / safe_learning Goto Github PK
View Code? Open in Web Editor NEWSafe reinforcement learning with stability guarantees
License: MIT License
Safe reinforcement learning with stability guarantees
License: MIT License
Hi, with reference to your earlier comments (9fc7475) I have made the necessary changes , but still I am getting these errors ,
Failed building wheel for cvxpy
Failed building wheel for subprocess32
Failed building wheel for fastcache
error: command 'x86_64-linux-gnu-gcc' failed with exit status 1
How to resolve, thanks
Hi, please let me know what are the modifications required to run these code on GPU server.
I am trying to install the package with pip version 19.0.2. It seems that gpflow==0.4.0 can not be installed by this pip. I have tried using pip 8.1.1 also where it says matplotlib is unable to install. Is there any pip version in between for which I can install both gpflow==0.4.0 as well as matplotlib.
I tried installing the package within a conda environment with the instructions given but failed.
EDIT:
I managed to find an alternative way that works
conda create -new "safe_learning" python=3.6
conda activate safe_learning
conda install tensorflow==1.12.0
Remove the following lines from requirements.txt
Do:
pip install pip==18.1
pip install . --process-dependency-links
On MacOS:
export KMP_DUPLICATE_LIB_OK=TRUE
The above should be done before running jupyter notebooks.
Hi Felix,
it would appear that pip no longer supports the version of tensorflow (<=12.0,>=1.6) that you are requiring. I did set pip to 18.1 and numpy to 1.14.5.
I get the message
Could not find a version that satisfies the requirement tensorflow<=1.12.0,>=1.6.0 (from safe-learning==0.0.1) (from versions: 1.13.0rc1, 1.13.0rc2, 1.13.1, 1.13.2, 1.14.0rc0, 1.14.0rc1, 1.14.0, 1.15.0rc0, 1.15.0rc1, 1.15.0rc2, 1.15.0rc3, 1.15.0, 1.15.2, 2.0.0a0, 2.0.0b0, 2.0.0b1, 2.0.0rc0, 2.0.0rc1, 2.0.0rc2, 2.0.0, 2.0.1, 2.1.0rc0, 2.1.0rc1, 2.1.0rc2, 2.1.0)
No matching distribution found for tensorflow<=1.12.0,>=1.6.0 (from safe-learning==0.0.1)
I instead tried setting the requirement to tensorflow==1.13.0 just to see what happens. It installed fine.
I went to try and run 1d_example.ipynb and got an error from gpflow
---------------------------------------------------------------------------
ModuleNotFoundError Traceback (most recent call last)
ModuleNotFoundError: No module named 'numpy.core._multiarray_umath'
---------------------------------------------------------------------------
ModuleNotFoundError Traceback (most recent call last)
ModuleNotFoundError: No module named 'numpy.core._multiarray_umath'
---------------------------------------------------------------------------
ModuleNotFoundError Traceback (most recent call last)
ModuleNotFoundError: No module named 'numpy.core._multiarray_umath'
---------------------------------------------------------------------------
ModuleNotFoundError Traceback (most recent call last)
ModuleNotFoundError: No module named 'numpy.core._multiarray_umath'
---------------------------------------------------------------------------
ModuleNotFoundError Traceback (most recent call last)
ModuleNotFoundError: No module named 'numpy.core._multiarray_umath'
---------------------------------------------------------------------------
ImportError Traceback (most recent call last)
<ipython-input-1-4ef92e5e9104> in <module>
3 from functools import partial
4
----> 5 import gpflow
6 import tensorflow as tf
7 import pkg_resources
/usr/local/lib/python3.7/site-packages/gpflow/__init__.py in <module>
16 # flake8: noqa
17 from __future__ import absolute_import
---> 18 from . import (likelihoods, kernels, ekernels, param,
19 model, gpmc, sgpmc, priors, gpr, svgp,
20 vgp, sgpr, gplvm, tf_wraps, tf_hacks)
/usr/local/lib/python3.7/site-packages/gpflow/model.py in <module>
17 from .param import Parameterized, AutoFlow, DataHolder
18 from .mean_functions import Zero
---> 19 from scipy.optimize import minimize, OptimizeResult
20 import numpy as np
21 import tensorflow as tf
/usr/local/lib/python3.7/site-packages/scipy/optimize/__init__.py in <module>
388 from __future__ import division, print_function, absolute_import
389
--> 390 from .optimize import *
391 from ._minimize import *
392 from ._root import *
/usr/local/lib/python3.7/site-packages/scipy/optimize/optimize.py in <module>
35 asarray, sqrt, Inf, asfarray, isinf)
36 import numpy as np
---> 37 from .linesearch import (line_search_wolfe1, line_search_wolfe2,
38 line_search_wolfe2 as line_search,
39 LineSearchWarning)
/usr/local/lib/python3.7/site-packages/scipy/optimize/linesearch.py in <module>
16 from warnings import warn
17
---> 18 from scipy.optimize import minpack2
19 import numpy as np
20 from scipy._lib.six import xrange
ImportError: numpy.core.multiarray failed to import
I double checked that numpy 1.14.5 was being used and even forced it by adding the code
import pkg_resources
pkg_resources.require("numpy==`1.14.5")
Any thoughts?
Hi Felix,
I have these questions.
I run lyapunov_function_learning.ipynb and got an error like this.
ModuleNotFoundError: No module named 'safe_learning'
And I don't quite understand how the initialization parameters of the Lyapunov function are obtained.
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