I'm using sumo-rl library that supposed to do reinforcement learning using gym and SuMO.
import gym
import sumo_rl
env = gym.make('sumo-rl-v0',
net_file='path_to_your_network.net.xml',
route_file='path_to_your_routefile.rou.xml',
out_csv_name='path_to_output.csv',
use_gui=True,
num_seconds=100000)
I got the error Environment sumo-rl doesn't exist when running the code provided in the documentation.
I already:
Installed the latest version of SUMO
Installed gym=="0.24.0"
Do I need to register sumo-rl env somewhere?
Related
The following testcase gives a warning:
import trio, httpx
async def amain():
async with httpx.AsyncClient() as client:
r = await client.get('https://icanhazip.com/')
print(r.text)
trio.run(amain)
Output:
> python test.py
/path/to/.venv/lib/python3.10/site-packages/anyio/_backends/_trio.py:164:
TrioDeprecationWarning: trio.MultiError is deprecated since Trio 0.22.0;
use BaseExceptionGroup (on Python 3.11 and later) or exceptiongroup.BaseExceptionGroup
(earlier versions) instead (https://github.com/python-trio/trio/issues/2211)
class ExceptionGroup(BaseExceptionGroup, trio.MultiError):
193.37.32.201
Fresh .venv using latest Python (installed with latest pyenv (installed with up-to-date brew)).
pip show trio reports 0.22.0. pip show httpx reports 0.23.0. Both of these are latest releases on pypi.
What's going on here? And how to silence the warning?
I raised this in https://github.com/encode/httpx/discussions/2409
To silence the warning:
import warnings
from trio import TrioDeprecationWarning
warnings.filterwarnings(action='ignore', category=TrioDeprecationWarning)
As far as I understand, lastest Trio release is using some exception-handling machinery that's only just been added into Python in 3.11.0, which hasn't been released yet (it SHOULD have been, but release-date got pushed back). Presumably that's what has created this unusual situation, where a deprecation warning requires a Python-version that does not yet exist.
I am trying to run the following code to train paddleOCR.
import paddle
import paddle.distributed as dist
But I'm getting this error:
ModuleNotFoundError: No module named 'paddle.distributed'
Even after I have installed paddle-client.
docker pull paddlepaddle/paddle:2.3.0-gpu-cuda11.2-cudnn8
I use this images which can work well.
You can try the paddlepaddle with 2.3.1 version，and quick install can refer to: https://www.paddlepaddle.org.cn/en
I am trying to use ImageDataBunch from fastai, and it worked fine, but recently when I ran my code, it showed this error ModuleNotFoundError: No module named 'fastai.vision'
Then, I upgraded my fastai version pip install fastai --upgrade. This error got cleared but landed in NameError: name 'ImageDataBunch' is not defined
Here's my code:
import warnings
import numpy as np
from fastai.vision import *
warnings.filterwarnings("ignore", category=UserWarning, module="torch.nn.functional")
np.random.seed(42)
data = ImageDataBunch.from_folder(path, train='.', valid_pct=0.2,
ds_tfms=get_transforms(), size=224, num_workers=4, no_check=True).normalize(imagenet_stats)
How can I fix this?
I actually ran into this same issue when I started using Colab, but haven't been able to reproduce it. Here was the thread describing what I and another developer did to troubleshoot: https://forums.fast.ai/t/no-module-named-fastai-data-in-google-colab/78164/4
I would recommend trying to factory reset your runtime ( "Runtime" -> "Factory Reset Runtime")
Then you can check which version of fastai you have (you have to restart the runtime to use the new version if you've already imported it)
import fastai
fastai.__version__
I'm able to run fastai.vision import * on fastai version 1.0.61 and 2.0.13
In Google Colab:
Upgrade fastai on colab:
! [ -e /content ] && pip install -Uqq fastai
Import necessary libraries:
from fastai.vision.all import *
from fastai.text.all import *
from fastai.collab import *
from fastai.tabular.all import *
Get the images and annotations:
path = untar_data(URLs.PETS)
path_anno = path/'annotations'
path_img = path/'images'
print( path_img.ls() ) # print all images
fnames = get_image_files(path_img) # -->> 7390 images
print(fnames[:5]) # print first 5 images
The solution that worked for me is to copy to (connect) my google drive & then run the cells. Source
You might have installed the older version of fastai. You need to upgrade to fastaiv2. You can upgrade fastai by using pip as shown below.
!pip install fastai --upgrade
Also check your fastai version using
import fastai
print(fastai.__version__)
I try to deploy an AWS lambda application, I implemented with the Chalice Python Framework. My app.py connects to a MySQL server and therefore has to
import mysql.connector
But on every invocation of one of my lambda functions I get an error in the log
'Unable to import module 'app': No module named mysql.connector'
I tried to add the mysql.connector to the requirements.txt file in the chalice project:
mysql_connector==2.1.6
And if I do so, 2 additional folders containing several files appear in the AWS lambda environment:
/mysql_connector-2.1.6.data
/mysql_connector-2.1.6.dist-info
But the error remains the same. How to deploy python mysql.connector with Chalice?
This finally worked for me:
lib_path=os.path.abspath(os.path.join(__file__, '..', 'mysql_connector-2.1.6.data', 'purelib'))
sys.path.append(lib_path)
import mysql.connector
Putting the "mysql_connector==2.1.6" into the "requirements.txt" file did install the mysql connector in lambda environment. I added the path of the package (../mysql_connector-2.1.6.data/purelib) to system path.
I want to create a database within a pipeline script to be used by the deployed app. But first I started testing the connection. I got this problem:
java.sql.SQLException: No suitable driver found for jdbc:mysql://mysql:3306/test_db
I have the database plugin and the MySQL database plugin installed.
How do I get the JDBC driver?
import groovy.sql.Sql
node{
def sql = Sql.newInstance("jdbc:mysql://mysql:3306/test_db", "user","passwd", "com.mysql.jdbc.Driver")
def rows = sql.execute "select count(*) from test_table;"
echo rows.dump()
}
Update after albciff answer:
My versions of:
Jenkins = 2.19.1
Database plugin = 1.5
Mysql database plugin = 1.1
The latest test script.
import groovy.sql.Sql
Class.forName("com.mysql.jdbc.Driver")
Which throws:
java.lang.ClassNotFoundException: com.mysql.jdbc.Driver
From the MySQL DataBase Plugin documentation you can see that jdbc drivers for MySQL are included:
Note that MySQL JDBC driver is under GPLv2 with FOSS exception. This
plugin by itself qualifies under the FOSS exception, but if you are
redistributing this plugin, please do check the license terms.
Drizzle(+MySQL) Database Plugin is available as an alternative to this
plugin, and that one is under the BSD license.
More concretely the actual last version (1.1) for this plugin contains connector version 5.1.38:
Version 1.1 (May 21, 2016) mysql-connector version 5.1.38
So probably in order to have the driver available you have to force the driver to be registered.
To do so use Class.forName("com.mysql.jdbc.Driver") before instantiate the connection in your code:
import groovy.sql.Sql
node{
Class.forName("com.mysql.jdbc.Driver")
def sql = Sql.newInstance("jdbc:mysql://mysql:3306/test_db", "user","passwd", "com.mysql.jdbc.Driver")
def rows = sql.execute "select count(*) from test_table;"
echo rows.dump()
}
UPDATE:
In order to has the JDBC connector classes available in the Jenkins pipeline groovy scripts you need to update the DataBase plugin to last currently version:
Version 1.5 (May 30, 2016) Pipeline Support
You can simply add the java connector in the java class path.
If jenkins is running java < 9 you probably will find the right place inside something like that:
<java_home>/jre/lib/ext
If jenkins is running java >= 9 you probably will find the right place inside something like that:
/usr/share/jenkins/jenkins.war
To find your paths you can check:
http://your.jenkins.host/systemInfo (or navigate system info path by GUI) and search for java.ext.dirs or java.class.path
http://your.jenkins.host/script (running console script such as System.getProperty("java.ext.dirs") or System.getProperty("java.class.path"))
This snippet can help you with the jenkins.war thing when running inside docker:
#adding extra jars to default jenkins java classpath (/usr/share/jenkins/jenkins.war)
RUN sudo mkdir -p /usr/share/jenkins/WEB-INF/lib/
RUN whereis jar #just to find full jar command classpath to use with sudo
COPY ./jar-ext/groovy/mysql-connector-java-8.0.21.jar /usr/share/jenkins/WEB-INF/lib/
RUN cd /usr/share/jenkins && sudo /opt/java/openjdk/bin/jar -uvf jenkins.war ./WEB-INF/lib/mysql-connector-java-8.0.21.jar
For Jenkins running on Java >= 9 add the jdbc drivers under ${JENKINS_HOME}/war/WEB-INF/lib and under the --webroot directory.