While reading the docs of System.Process and trying to use callCommand I discovered that it is not available:
test.hs:1:24: Module `System.Process' does not export `callCommand'
Why?
callProcess was added to the process library in version 1.2.0.0. I suspect you are using an earlier version.
Related
I want to import TensorMetric :
from pytorch_lightning.metrics.metric import TensorMetric
The program throws an exception:
ModuleNotFoundError: No module named 'pytorch_lightning.metrics'
My environment is:
Python 3.8.13
tokenizers==0.9.2
torch==1.5.1
transformers==3.4.0
pytorch-lightning==0.9.0
tensorboard==2.2.0
0.9 is a very old version of Lightning and a lot has changed/improved since then. I would recommend you to use the latest version of PyTorch Lightning (1.6).
Also, we have metrics as a separate library now TorchMetrics.
I am trying to build a python 3.5 environment that supports an old hddm library. Standard approaches fail due to my/anaconda's apparent inability in ignore (or downgrade) the 10.1 cuda library in favor of an older one that works with hddm.
There is a yml file available that describes a successful environment. But the advertised command
conda env create -file hddm_py35.yml
fails with an error listing all of the packages "not found." Here are the errors.
(base) PS C:\Users\Peter\anaconda3_Sep2020> conda env create --file .\hddm_py35.yml
Collecting package metadata (repodata.json): done
Solving environment: failed
ResolvePackageNotFound:
odo==0.5.0=py35_1
cffi==1.7.0=py35_0
dill==0.2.5=py35_0
singledispatch==3.4.0.3=py35_0
nb_conda_kernels==2.0.0=py35_0
requests==2.14.2=py35_0
scikit-learn==0.17.1=np111py35_1
wheel==0.29.0=py35_0
jedi==0.9.0=py35_1
widgetsnbextension==1.2.6=py35_0
bitarray==0.8.1=py35_1
theano==1.0.2=py35_0
pytz==2016.6.1=py35_0
pylint==1.5.4=py35_1
ruamel_yaml==0.11.14=py35_0
partd==0.3.6=py35_0
llvmlite==0.13.0=py35_0
multipledispatch==0.4.8=py35_0
pyparsing==2.1.4=py35_0
console_shortcut==0.1.1=py35_1
ipython_genutils==0.1.0=py35_0
patsy==0.4.1=py35_0
pytest==2.9.2=py35_0
heapdict==1.0.0=py35_1
ipywidgets==5.2.2=py35_0
bokeh==0.12.2=py35_0
hdf5==1.8.15.1=2
networkx==1.11=py35_0
backports==1.0=py35_0
pyasn1==0.1.9=py35_0
pyqt==5.6.0=py35h6538335_6
zlib==1.2.11=hbb18732_2
et_xmlfile==1.0.1=py35_0
traitlets==4.3.0=py35_0
colorama==0.3.7=py35_0
argcomplete==1.0.0=py35_1
pywin32==220=py35_1
astropy==1.2.1=np111py35_0
nose==1.3.7=py35_1
freetype==2.8=h0224ed4_1
pkginfo==1.3.2=py35_0
cloudpickle==0.2.1=py35_0
sqlalchemy==1.0.13=py35_0
lazy-object-proxy==1.2.1=py35_0
markupsafe==0.23=py35_2
prompt_toolkit==1.0.3=py35_0
pickleshare==0.7.4=py35_0
itsdangerous==0.24=py35_0
babel==2.3.4=py35_0
click==6.6=py35_0
six==1.10.0=py35_0
libdynd==0.7.2=0
jdcal==1.2=py35_1
pymc==2.3.6=np111py35_2
pathlib2==2.1.0=py35_0
astroid==1.4.7=py35_0
numba==0.28.1=np111py35_0
qtconsole==4.2.1=py35_2
wrapt==1.10.6=py35_0
idna==2.1=py35_0
pytables==3.2.2=np111py35_4
_nb_ext_conf==0.3.0=py35_0
dynd-python==0.7.2=py35_0
numexpr==2.6.1=np111py35_0
werkzeug==0.11.11=py35_0
rope==0.9.4=py35_1
jupyter_client==4.4.0=py35_0
pyzmq==15.4.0=py35_0
python-dateutil==2.5.3=py35_0
beautifulsoup4==4.5.1=py35_0
blaze==0.10.1=py35_0
nbformat==4.1.0=py35_0
nbpresent==3.0.2=py35_0
sip==4.18=py35_0
chest==0.2.3=py35_0
glob2==0.5=py35_0
locket==0.2.0=py35_1
mistune==0.7.3=py35_0
alabaster==0.7.9=py35_0
setuptools==27.2.0=py35_1
win_unicode_console==0.5=py35_0
filelock==2.0.6=py35_0
_license==1.1=py35_1
ipykernel==4.5.0=py35_0
qt==5.6.2=vc14h6f76a7e_12
pep8==1.7.0=py35_0
xlwings==0.10.0=py35_0
spyder==3.0.0=py35_0
xlrd==1.0.0=py35_0
scipy==0.18.1=np111py35_0
dask==0.11.0=py35_0
nbconvert==4.2.0=py35_0
pip==8.1.2=py35_0
mkl==11.3.3=1
nb_anacondacloud==1.2.0=py35_0
cython==0.24.1=py35_0
flask-cors==2.1.2=py35_0
ipython==5.1.0=py35_0
cycler==0.10.0=py35_0
jpeg==9b=he27b436_2
menuinst==1.4.1=py35_0
anaconda==4.2.0=np111py35_0
configobj==5.0.6=py35_0
boto==2.42.0=py35_0
unicodecsv==0.14.1=py35_0
scikit-image==0.12.3=np111py35_1
contextlib2==0.5.3=py35_0
conda-build==3.0.19=py35h15d37ab_0
jinja2==2.8=py35_1
conda-verify==2.0.0=py35_0
get_terminal_size==1.0.0=py35_0
qtpy==1.1.2=py35_0
anaconda-client==1.5.1=py35_0
decorator==4.0.10=py35_0
ply==3.9=py35_0
openpyxl==2.3.2=py35_0
sockjs-tornado==1.0.3=py35_0
pyyaml==3.12=py35_0
snowballstemmer==1.2.1=py35_0
toolz==0.8.0=py35_0
py==1.4.31=py35_0
xlwt==1.1.2=py35_0
clyent==1.2.2=py35_0
bottleneck==1.1.0=np111py35_0
jupyter==1.0.0=py35_3
mkl-service==1.1.2=py35_2
simplegeneric==0.8.1=py35_1
wcwidth==0.1.7=py35_0
h5py==2.6.0=np111py35_2
gevent==1.1.2=py35_0
pycrypto==2.6.1=py35_4
datashape==0.5.2=py35_0
psutil==4.3.1=py35_0
nltk==3.2.1=py35_0
jsonschema==2.5.1=py35_0
notebook==4.2.3=py35_0
pycparser==2.14=py35_1
xlsxwriter==0.9.3=py35_0
jupyter_core==4.2.0=py35_0
qtawesome==0.3.3=py35_0
fastcache==1.0.2=py35_1
jupyter_console==5.0.0=py35_0
tornado==4.4.1=py35_0
path.py==8.2.1=py35_0
pyflakes==1.3.0=py35_0
sympy==1.0=py35_0
pandas==0.20.1=np111py35_0
pygments==2.1.3=py35_0
anaconda-clean==1.0.0=py35_0
mpmath==0.19=py35_1
comtypes==1.1.2=py35_0
cryptography==1.5=py35_0
chardet==3.0.4=py35_0
entrypoints==0.2.2=py35_0
sphinx==1.4.6=py35_0
greenlet==0.4.10=py35_0
anaconda-navigator==1.3.1=py35_0
flask==0.11.1=py35_0
pyopenssl==16.2.0=py35_0
lxml==3.6.4=py35_0
icu==58.2=h3fcc66b_1
docutils==0.12=py35_2
statsmodels==0.6.1=np111py35_1
nb_conda==2.0.0=py35_0
imagesize==0.7.1=py35_0
(base) PS C:\Users\Peter\anaconda3_Sep2020>
The failure occurred within seconds. I get the feeling that conda didn't even try to look for these packages!?!?
Am I supposed to download these packages, put them somewhere, and then tell conda to find them on my hard drive?
Is there a flag that tells conda to do its usually find-and-load for all "missing" packages -- but only in the environment I'm describing? In my base environment (3.8) I don't wish to downgrade.
Should make a new 3.5 environment and then work through the list one-by-one and uninstall/remove/downgrade each package by hand?
Meta question: This must be a FAQ, and yet I'm not able to google for the answer. That usually means googling for "conda install environment from yaml file" doesn't contain the appropriate vocabulary for, well, trying to induce conda to install an environment from a yaml file. What question should I have asked?
1) Am I supposed to download these packages, put them somewhere, and then
tell conda to find them on my hard drive?
Not necessary. But searching for the versions on anaconda.org helps identify channels for one-by-one manual download.
2) Is there a flag that tells conda to do its usually find-and-load for all
"missing" packages -- but only in the environment I'm describing? In my base
environment (3.8) I don't wish to downgrade.
There is no evidence that conda will automatically download files listed in a yaml file that are missing in the present environment.
3) Should make a new 3.5 environment and then work through the list one-by-
one and uninstall/remove/downgrade each package by hand?
Yes.
4) Meta question: This must be a FAQ, and yet I'm not able to google for the
answer. That usually means googling for "conda install environment from yaml
file" doesn't contain the appropriate vocabulary for, well, trying to induce
conda to install an environment from a yaml file. What question should I have
asked?
There is no evidence that yaml files are anything other than lists of version of packages in an environment. They cannot be used to make new environments (unless all of the components are already present in the host environment, maybe) so their value is largely annotative. Evidently.
For the case of making an environment for hddm in 2020, well, don't try. Cuda support will work against you. There is a hddm host at https://colab.research.google.com/ that is properly configured (without cuda disruption) so that you can use it to kick tires, etc. Getting hddm to work in any other context probably requires dedicated hardware so that the cuda driver can be manipulated for this application only and not break any other applications in the process.
I am trying to play a wav file in a very simple program that looks like this, currently attempting to use nim-csfml:
import csfml_audio
var alarmsong = newMusic("alarm.wav")
alarmsong.play()
but it appears to be relying on the existence of libcsfml.audio, and while my program compiles just fine, when I try to actually run it I get an error
| => ./alarm
could not load: libcsfml-audio.so
(I have a libcsfml-audio.dylib instead, being that I used the OSX shared libraries for csfml/sfml)
Is there some other way to play a .wav file in Nim?
Edit 1:
After the PR made by #def-, I now get a different, slightly more comforting error, which is probably due to some poor understanding of how nim deals with shared libraries:
| => ./alarm
could not load: libcsfml-audio.dylib
I added path = "/usr/local/lib" to my nim.cfg file, but it didn't seem to be affect anything. I also exported $LD_LIBRARY_PATH="/usr/local/lib" (/usr/local/bin is where libcsfml-audio.dylib is.), and tried compilation through
nim c alarm.nim --clib:/usr/local/lib/libcsfml-audio.dylib
Thanks for the help!
This program would just exit immediately; you need to keep it alive while the sound plays. Append this to the program:
import csfml_system
while alarmsong.status == SoundStatus.Playing:
sleep 100.milliseconds
For nim-csfml to work you'll need SFML 2.1 and CSFML 2.1. Also, it seems that nim-csfml is actually broken for Mac OS X, so I've made a pull request with a fix: https://github.com/BlaXpirit/nim-csfml/pull/4
Other modules that could play sound are sdl_mixer, sdl2/audio and allegro5.
As an OSX-only alternative without using any libraries, by calling the afplay binary:
import osproc
discard execProcess("afplay", ["file.wav"])
Edit1:
When Nim reports "could not load: libcsfml-audio.dynlib" that could also mean that one of the dependencies of that library are missing or in a wrong version. Especially SFML 2.2 doesn't work with CSFML 2.1. Make sure libsfml-audio.dynlib is in your LD_LIBRARY_PATH as well. If that doesn't work either, you could try to compile and run a regular C CSFML example like this one: https://gist.github.com/def-/fee8bb041719337c8812
Compile it with clang -o mainpage -lcsfml-graphics -lcsfml-audio -lGL -lGLEW mainpage.c to see the errors/warnings about missing libraries.
I recently installed ATG 10.2 on my Mac using the instructions found here.
After successfully installing ATG I then tried to compile my ATG code using the runAssembler script provided, however I encountered the following error:
[ERROR] ./bin/dynamoEnv.sh: line 355: -Djava.security.policy=lib/java.policy: No such file or directory
Why does my ATG build fail?
In the spirit of SO I am answering my own question:
It turns out I encountered a known bug with the ATG installers which fail to update the <DYNAMO_HOME>/home/localconfig/dasEnv.sh with the correct values (dasEnv.bat for Windows). The values which you need to add to this file are:
# Note: I am using WebLogic (change if you are using jBoss or WebSpere)
export ATGJRE=<YOUR_PATH_TO_JAVA>
# e.g. export ATGJRE=/usr/bin/java
export WL_HOME=<WLS_HOME>
# e.g. export WL_HOME=/Users/my_user/Applications/weblogic/wlserver10_3
export WL_VERSION=10.3.6
# self explanatory ...
Please note that this bug affects Windows installs too. More information can be found here.
I want to perform a HTTP request using the simplest way. I decided to use conduits. Here is my main file:
{-# LANGUAGE OverloadedStrings #-}
import Network.HTTP.Conduit -- the main module
-- The streaming interface uses conduits
import Data.Conduit
import Data.Conduit.Binary (sinkFile)
import qualified Data.ByteString.Lazy as L
import Control.Monad.IO.Class (liftIO)
main :: IO ()
main = do
simpleHttp "http://www.example.com/foo.txt" >>= L.writeFile "foo.txt"
And .cabal:
executable AAA
main-is: Main.hs
hs-source-dirs: src
build-depends: base ==4.6.*, text ==0.11.*, http-conduit, transformers, bytestring
I can't build it, the error is:
$ cabal build
Building AAA-0.1.0.0...
Preprocessing executable 'AAA' for
AAA-0.1.0.0...
src/Main.hs:6:8:
Could not find module `Data.Conduit.Binary'
Perhaps you meant
Data.Conduit.List (needs flag -package conduit-1.1.4)
Data.Conduit.Lift (needs flag -package conduit-1.1.4)
Use -v to see a list of the files searched for.
I've already installed all the libraries shown in the .cabal file by saying cabal install xxx.
What's up with this?
Update:
Couldn't match type `L.ByteString'
with `bytestring-0.10.0.2:Data.ByteString.Lazy.Internal.ByteString'
Expected type: bytestring-0.10.0.2:Data.ByteString.Lazy.Internal.ByteString
-> IO ()
Actual type: L.ByteString -> IO ()
In the return type of a call of `L.writeFile'
In the second argument of `(>>=)', namely `L.writeFile "foo.txt"'
In a stmt of a 'do' block:
simpleHttp "http://www.example.com/foo.txt"
>>= L.writeFile "foo.txt"
So the problem is that your program imports Data.Conduit.Binary which isn't installed. It lives in the conduit-extra package, so you have to add it to your dependencies and install it if you want to use it.
Your main function doesn't actually use it though, so you can just remove the import and it should fix the current error. You will however get a new error when attempting to build since you also import Data.Conduit which isn't listed in your cabal file either. To fix this error remove the import or add conduit to your build-depends.
Seems like now you have two (at least) versions of bytestring installed, and different packages don't agree on which one has to be used.
I suggest reinstalling http-conduit.