Assuming you are in src from a CMSSW distribution, start env with the command cmsenv. Then:
- Let's say your file is
test.cc:
#include <iostream>
#include <filesystem>
#include <string>
namespace fs = std::filesystem;Assuming you are in src from a CMSSW distribution, start env with the command cmsenv. Then:
test.cc:#include <iostream>
#include <filesystem>
#include <string>
namespace fs = std::filesystem;When jobs command does not work because you closed your shell, try:
ps aux | grep cmsRunThe command I left running in the background is nohup cmsRun rerun_.py &.
Note: See comment 4 for how Daniel found a new Phase2Spring24 dataset.
My cmsDriver.py failed because of the following --filein "root://cmsxrootd.fnal.gov///store/mc/Phase2Spring23DIGIRECOMiniAOD/MinBias_TuneCP5_14TeV-pythia8/GEN-SIM-DIGI-RAW-MINIAOD/PU200_L1TFix_Trk1GeV_131X_mcRun4_realistic_v9_ext1-v2/80000/0061cc5d-056b-41f5-ba7b-aada40915e3f.root". According to CMS people (Artur Lobanov), the file now only exists "on tape", so I need to find the one that "on disk." We can do this via browser by accessing CMS DAS at https://cmsweb.cern.ch/das/ via the browser.
The package pipdeptree can be used to show a tree of all package dependencies in your environment. Install and use it as:
pip install pipdeptree
pipdeptree > pipdeptree.log
Then, open the pipdeptree.log file to see the tree.
You should be able to ssh into correlator 4 with something like: ssh -L 5908:localhost:5907 <LPCusername>@correlator4.fnal.gov. This ssh command will tunnel from a local port 5908 into remote the port 5907 on correlator4.
Once in correlator 4, check for an existing vncserver with: vncserver -list. If there is one, you will see some output and the port for your server, e.g. you will that a port :01 exists. We shuld kill this port and create a new with vncserver -kill :01. Like check to see with vncserver -list.
Create the new port with: vncserver :07 -geometry 2000x1800 and set a password if you are prompted. You can use your kinit password. Check that port :07 has been created. You can try another geometry to see what looks better on your screen.
Exit correlator 4.
| #Located in my LPC. | |
| from WMCore.Configuration import Configuration | |
| config = Configuration() | |
| config.section_("General") | |
| config.General.requestName = "_ucsd_MinBias" | |
| config.General.workArea = "partial_crab_projects" | |
| config.section_("JobType") | |
| config.JobType.pluginName = "Analysis" | |
| config.JobType.psetName = "rerunL1_cfg.py" #config file resulting from cmsDriver command |
We can't simply activate Jupyter-lab or Notebook from the virtual environment, or in this case, select it on VS code. We need to explicitly install a Jupyter kernel that points to the new Python virtual environment. For that, we run the following:
python3 -m ipykernel install --user --name=projectname
project name is the name of our environment, which contains all of the packages we need.
After this is done, we must restart VS code, then click select kernel on top right corner and select jupyter kernel when promted. The name of your environment should appear, thus select that for it to work.
jupyter kernelspec list lists which kernels you installed.If you are like me you find yourself cloning a repo, making some proposed changes and then deciding to later contributing back using the GitHub Flow convention. Below is a set of instructions I've developed for myself on how to deal with this scenario and an explanation of why it matters based on jagregory's gist.
To follow GitHub flow you should really have created a fork initially as a public representation of the forked repository and the clone that instead. My understanding is that the typical setup would have your local repository pointing to your fork as origin and the original forked repository as upstream so that you can use these keywords in other git commands.
Clone some repo (you've probably already done this step).
git clone [email protected]conda activate your_environment_name git clone --single-branch --branch split_pointwise_conv_by_rf_rebase_latest https://github.com/jmduarte/hls4ml.git cd hls4ml git branch --all #shows you are on your desired branch pip install -e .