server.py
contains the API code for the Flask server (back-end)main.py
contains the streamlit code (front-end)
pip install plotly streamlit pandas requests flask
To run access a remote jupyter notebook, you will need to do the following:
~/.ssh/config
):Host FLIP # access point server
HostName access.engr.oregonstate.edu
User ONIDusername
Host DGX # target server
HostName submit-b.hpc.engr.oregonstate.edu
User ONIDusername
name: Automated Experiments | |
on: | |
push: | |
branches: [ main ] | |
jobs: | |
build_on_cn-gpu5: | |
runs-on: [ cn-gpu5 ] | |
timeout-minutes: 4320 | |
defaults: | |
run: |
# Create 4 tunnels, each for different ports, with only https enabled | |
# This way the ngrok process stays bellow the Free plan limit (4 tunnels) | |
# command: ngrok start --all # to start all of them | |
# command: ngrok start note tb # to run jupyter notebook server and tensorboard server only | |
# refer to this page for more info: https://ngrok.com/docs#multiple-tunnels | |
authtoken: ... | |
log: ngrok.log | |
tunnels: | |
# to run jupyter notebook server |
It wasn't obvious on PyTorch's documentation of how to use PyTorch Profiler (as of today, 8/12/2021), so I have spent some time to understand how to use it and this gist contains a simple example to use.
python>=1.9.0
torchvision>=0.10.0
numpy
matplotlib
# source: https://twitter.com/PrasoonPratham/status/1461267623266635778/photo/1 (@PrasoonPratham on Twitter) | |
import datetime | |
import hashlib | |
class Block: | |
def __init__(self, data): | |
self.data = data | |
self.blockNo = 0 | |
self.next = None | |
self.nonce = 0 |