launch tensorboard in colab - python

i try launch tensorboard on colab, my code:
LOG_DIR = model_dir
get_ipython().system_raw(
'tensorboard --logdir {} --host 0.0.0.0 --port 6060 &'
.format(LOG_DIR)
)
get_ipython().system_raw('./ngrok http 6060 &')
! curl -s http://localhost:4040/api/tunnels | python3 -c \
"import sys, json; print(json.load(sys.stdin)['tunnels'][0]['public_url'])"
two days ago everything worked, but now such an error:
error

The error linked suggests the port you're using is 6006, but the code example you gave above has the port as 6060. So may just be a typo there.
It's also possible you want a TCP tunnel, not an HTTP tunnel.
In either case, might I suggest trying something like pyngrok to programmatically manage your ngrok tunnel for you? Full disclosure, I am the developer of it. Here are the docs if you're interest.

Related

Execute Host OS Command from Flask container [duplicate]

How to control host from docker container?
For example, how to execute copied to host bash script?
This answer is just a more detailed version of Bradford Medeiros's solution, which for me as well turned out to be the best answer, so credit goes to him.
In his answer, he explains WHAT to do (named pipes) but not exactly HOW to do it.
I have to admit I didn't know what named pipes were when I read his solution. So I struggled to implement it (while it's actually very simple), but I did succeed.
So the point of my answer is just detailing the commands you need to run in order to get it working, but again, credit goes to him.
PART 1 - Testing the named pipe concept without docker
On the main host, chose the folder where you want to put your named pipe file, for instance /path/to/pipe/ and a pipe name, for instance mypipe, and then run:
mkfifo /path/to/pipe/mypipe
The pipe is created.
Type
ls -l /path/to/pipe/mypipe
And check the access rights start with "p", such as
prw-r--r-- 1 root root 0 mypipe
Now run:
tail -f /path/to/pipe/mypipe
The terminal is now waiting for data to be sent into this pipe
Now open another terminal window.
And then run:
echo "hello world" > /path/to/pipe/mypipe
Check the first terminal (the one with tail -f), it should display "hello world"
PART 2 - Run commands through the pipe
On the host container, instead of running tail -f which just outputs whatever is sent as input, run this command that will execute it as commands:
eval "$(cat /path/to/pipe/mypipe)"
Then, from the other terminal, try running:
echo "ls -l" > /path/to/pipe/mypipe
Go back to the first terminal and you should see the result of the ls -l command.
PART 3 - Make it listen forever
You may have noticed that in the previous part, right after ls -l output is displayed, it stops listening for commands.
Instead of eval "$(cat /path/to/pipe/mypipe)", run:
while true; do eval "$(cat /path/to/pipe/mypipe)"; done
(you can nohup that)
Now you can send unlimited number of commands one after the other, they will all be executed, not just the first one.
PART 4 - Make it work even when reboot happens
The only caveat is if the host has to reboot, the "while" loop will stop working.
To handle reboot, here what I've done:
Put the while true; do eval "$(cat /path/to/pipe/mypipe)"; done in a file called execpipe.sh with #!/bin/bash header
Don't forget to chmod +x it
Add it to crontab by running
crontab -e
And then adding
#reboot /path/to/execpipe.sh
At this point, test it: reboot your server, and when it's back up, echo some commands into the pipe and check if they are executed.
Of course, you aren't able to see the output of commands, so ls -l won't help, but touch somefile will help.
Another option is to modify the script to put the output in a file, such as:
while true; do eval "$(cat /path/to/pipe/mypipe)" &> /somepath/output.txt; done
Now you can run ls -l and the output (both stdout and stderr using &> in bash) should be in output.txt.
PART 5 - Make it work with docker
If you are using both docker compose and dockerfile like I do, here is what I've done:
Let's assume you want to mount the mypipe's parent folder as /hostpipe in your container
Add this:
VOLUME /hostpipe
in your dockerfile in order to create a mount point
Then add this:
volumes:
- /path/to/pipe:/hostpipe
in your docker compose file in order to mount /path/to/pipe as /hostpipe
Restart your docker containers.
PART 6 - Testing
Exec into your docker container:
docker exec -it <container> bash
Go into the mount folder and check you can see the pipe:
cd /hostpipe && ls -l
Now try running a command from within the container:
echo "touch this_file_was_created_on_main_host_from_a_container.txt" > /hostpipe/mypipe
And it should work!
WARNING: If you have an OSX (Mac OS) host and a Linux container, it won't work (explanation here https://stackoverflow.com/a/43474708/10018801 and issue here https://github.com/docker/for-mac/issues/483 ) because the pipe implementation is not the same, so what you write into the pipe from Linux can be read only by a Linux and what you write into the pipe from Mac OS can be read only by a Mac OS (this sentence might not be very accurate, but just be aware that a cross-platform issue exists).
For instance, when I run my docker setup in DEV from my Mac OS computer, the named pipe as explained above does not work. But in staging and production, I have Linux host and Linux containers, and it works perfectly.
PART 7 - Example from Node.JS container
Here is how I send a command from my Node.JS container to the main host and retrieve the output:
const pipePath = "/hostpipe/mypipe"
const outputPath = "/hostpipe/output.txt"
const commandToRun = "pwd && ls-l"
console.log("delete previous output")
if (fs.existsSync(outputPath)) fs.unlinkSync(outputPath)
console.log("writing to pipe...")
const wstream = fs.createWriteStream(pipePath)
wstream.write(commandToRun)
wstream.close()
console.log("waiting for output.txt...") //there are better ways to do that than setInterval
let timeout = 10000 //stop waiting after 10 seconds (something might be wrong)
const timeoutStart = Date.now()
const myLoop = setInterval(function () {
if (Date.now() - timeoutStart > timeout) {
clearInterval(myLoop);
console.log("timed out")
} else {
//if output.txt exists, read it
if (fs.existsSync(outputPath)) {
clearInterval(myLoop);
const data = fs.readFileSync(outputPath).toString()
if (fs.existsSync(outputPath)) fs.unlinkSync(outputPath) //delete the output file
console.log(data) //log the output of the command
}
}
}, 300);
Use a named pipe.
On the host OS, create a script to loop and read commands, and then you call eval on that.
Have the docker container read to that named pipe.
To be able to access the pipe, you need to mount it via a volume.
This is similar to the SSH mechanism (or a similar socket-based method), but restricts you properly to the host device, which is probably better. Plus you don't have to be passing around authentication information.
My only warning is to be cautious about why you are doing this. It's totally something to do if you want to create a method to self-upgrade with user input or whatever, but you probably don't want to call a command to get some config data, as the proper way would be to pass that in as args/volume into docker. Also, be cautious about the fact that you are evaling, so just give the permission model a thought.
Some of the other answers such as running a script. Under a volume won't work generically since they won't have access to the full system resources, but it might be more appropriate depending on your usage.
The solution I use is to connect to the host over SSH and execute the command like this:
ssh -l ${USERNAME} ${HOSTNAME} "${SCRIPT}"
UPDATE
As this answer keeps getting up votes, I would like to remind (and highly recommend), that the account which is being used to invoke the script should be an account with no permissions at all, but only executing that script as sudo (that can be done from sudoers file).
UPDATE: Named Pipes
The solution I suggested above was only the one I used while I was relatively new to Docker. Now in 2021 take a look on the answers that talk about Named Pipes. This seems to be a better solution.
However, nobody there mentioned anything about security. The script that will evaluate the commands sent through the pipe (the script that calls eval) must actually not use eval for the whole pipe output, but to handle specific cases and call the required commands according to the text sent, otherwise any command that can do anything can be sent through the pipe.
That REALLY depends on what you need that bash script to do!
For example, if the bash script just echoes some output, you could just do
docker run --rm -v $(pwd)/mybashscript.sh:/mybashscript.sh ubuntu bash /mybashscript.sh
Another possibility is that you want the bash script to install some software- say the script to install docker-compose. you could do something like
docker run --rm -v /usr/bin:/usr/bin --privileged -v $(pwd)/mybashscript.sh:/mybashscript.sh ubuntu bash /mybashscript.sh
But at this point you're really getting into having to know intimately what the script is doing to allow the specific permissions it needs on your host from inside the container.
My laziness led me to find the easiest solution that wasn't published as an answer here.
It is based on the great article by luc juggery.
All you need to do in order to gain a full shell to your linux host from within your docker container is:
docker run --privileged --pid=host -it alpine:3.8 \
nsenter -t 1 -m -u -n -i sh
Explanation:
--privileged : grants additional permissions to the container, it allows the container to gain access to the devices of the host (/dev)
--pid=host : allows the containers to use the processes tree of the Docker host (the VM in which the Docker daemon is running)
nsenter utility: allows to run a process in existing namespaces (the building blocks that provide isolation to containers)
nsenter (-t 1 -m -u -n -i sh) allows to run the process sh in the same isolation context as the process with PID 1.
The whole command will then provide an interactive sh shell in the VM
This setup has major security implications and should be used with cautions (if any).
Write a simple server python server listening on a port (say 8080), bind the port -p 8080:8080 with the container, make a HTTP request to localhost:8080 to ask the python server running shell scripts with popen, run a curl or writing code to make a HTTP request curl -d '{"foo":"bar"}' localhost:8080
#!/usr/bin/python
from BaseHTTPServer import BaseHTTPRequestHandler,HTTPServer
import subprocess
import json
PORT_NUMBER = 8080
# This class will handles any incoming request from
# the browser
class myHandler(BaseHTTPRequestHandler):
def do_POST(self):
content_len = int(self.headers.getheader('content-length'))
post_body = self.rfile.read(content_len)
self.send_response(200)
self.end_headers()
data = json.loads(post_body)
# Use the post data
cmd = "your shell cmd"
p = subprocess.Popen(cmd, stdout=subprocess.PIPE, shell=True)
p_status = p.wait()
(output, err) = p.communicate()
print "Command output : ", output
print "Command exit status/return code : ", p_status
self.wfile.write(cmd + "\n")
return
try:
# Create a web server and define the handler to manage the
# incoming request
server = HTTPServer(('', PORT_NUMBER), myHandler)
print 'Started httpserver on port ' , PORT_NUMBER
# Wait forever for incoming http requests
server.serve_forever()
except KeyboardInterrupt:
print '^C received, shutting down the web server'
server.socket.close()
If you are not worried about security and you're simply looking to start a docker container on the host from within another docker container like the OP, you can share the docker server running on the host with the docker container by sharing it's listen socket.
Please see https://docs.docker.com/engine/security/security/#docker-daemon-attack-surface and see if your personal risk tolerance allows this for this particular application.
You can do this by adding the following volume args to your start command
docker run -v /var/run/docker.sock:/var/run/docker.sock ...
or by sharing /var/run/docker.sock within your docker compose file like this:
version: '3'
services:
ci:
command: ...
image: ...
volumes:
- /var/run/docker.sock:/var/run/docker.sock
When you run the docker start command within your docker container,
the docker server running on your host will see the request and provision the sibling container.
credit: http://jpetazzo.github.io/2015/09/03/do-not-use-docker-in-docker-for-ci/
As Marcus reminds, docker is basically process isolation. Starting with docker 1.8, you can copy files both ways between the host and the container, see the doc of docker cp
https://docs.docker.com/reference/commandline/cp/
Once a file is copied, you can run it locally
docker run --detach-keys="ctrl-p" -it -v /:/mnt/rootdir --name testing busybox
# chroot /mnt/rootdir
#
I have a simple approach.
Step 1: Mount /var/run/docker.sock:/var/run/docker.sock (So you will be able to execute docker commands inside your container)
Step 2: Execute this below inside your container. The key part here is (--network host as this will execute from host context)
docker run -i --rm --network host -v /opt/test.sh:/test.sh alpine:3.7
sh /test.sh
test.sh should contain the some commands (ifconfig, netstat etc...) whatever you need.
Now you will be able to get host context output.
You can use the pipe concept, but use a file on the host and fswatch to accomplish the goal to execute a script on the host machine from a docker container. Like so (Use at your own risk):
#! /bin/bash
touch .command_pipe
chmod +x .command_pipe
# Use fswatch to execute a command on the host machine and log result
fswatch -o --event Updated .command_pipe | \
xargs -n1 -I "{}" .command_pipe >> .command_pipe_log &
docker run -it --rm \
--name alpine \
-w /home/test \
-v $PWD/.command_pipe:/dev/command_pipe \
alpine:3.7 sh
rm -rf .command_pipe
kill %1
In this example, inside the container send commands to /dev/command_pipe, like so:
/home/test # echo 'docker network create test2.network.com' > /dev/command_pipe
On the host, you can check if the network was created:
$ docker network ls | grep test2
8e029ec83afe test2.network.com bridge local
In my scenario I just ssh login the host (via host ip) within a container and then I can do anything I want to the host machine
I found answers using named pipes awesome. But I was wondering if there is a way to get the output of the executed command.
The solution is to create two named pipes:
mkfifo /path/to/pipe/exec_in
mkfifo /path/to/pipe/exec_out
Then, the solution using a loop, as suggested by #Vincent, would become:
# on the host
while true; do eval "$(cat exec_in)" > exec_out; done
And then on the docker container, we can execute the command and get the output using:
# on the container
echo "ls -l" > /path/to/pipe/exec_in
cat /path/to/pipe/exec_out
If anyone interested, my need was to use a failover IP on the host from the container, I created this simple ruby method:
def fifo_exec(cmd)
exec_in = '/path/to/pipe/exec_in'
exec_out = '/path/to/pipe/exec_out'
%x[ echo #{cmd} > #{exec_in} ]
%x[ cat #{exec_out} ]
end
# example
fifo_exec "curl https://ip4.seeip.org"
Depending on the situation, this could be a helpful resource.
This uses a job queue (Celery) that can be run on the host, commands/data could be passed to this through Redis (or rabbitmq). In the example below, this is occurring in a django application (which is commonly dockerized).
https://www.codingforentrepreneurs.com/blog/celery-redis-django/
To expand on user2915097's response:
The idea of isolation is to be able to restrict what an application/process/container (whatever your angle at this is) can do to the host system very clearly. Hence, being able to copy and execute a file would really break the whole concept.
Yes. But it's sometimes necessary.
No. That's not the case, or Docker is not the right thing to use. What you should do is declare a clear interface for what you want to do (e.g. updating a host config), and write a minimal client/server to do exactly that and nothing more. Generally, however, this doesn't seem to be very desirable. In many cases, you should simply rethink your approach and eradicate that need. Docker came into an existence when basically everything was a service that was reachable using some protocol. I can't think of any proper usecase of a Docker container getting the rights to execute arbitrary stuff on the host.

TensorBoard in TensorFlow 1 using Google Colab

I would like to use TensorBoard in TensorFlow 1 in Google Colab. The tutorials I have found seem to be on TensorFlow 2 and the suggestions do not seem to work in TensorFlow 1.
It seems I need some equivalent to tf.summary.create_file_writer and tf.summary.scalar. I have tried tf.contrib.summary.create_file_writer and tf.contrib.summary.scalar, but these do not seem to work.
Here is the recreation of my problem:
https://colab.research.google.com/drive/1M3CL0oasd8pCjXLaaHl15I1yz-LUXNhq
!wget https://bin.equinox.io/c/4VmDzA7iaHb/ngrok-stable-linux-amd64.zip
!unzip ngrok-stable-linux-amd64.zip
get_ipython().system_raw('tensorboard --logdir /content/trainingdata/objectdetection/ckpt_output/trainingImatges/ --host 0.0.0.0 --port 6006 &')
get_ipython().system_raw('./ngrok http 6006 &')
! curl -s http://localhost:4040/api/tunnels | python3 -c \
"import sys, json; print(json.load(sys.stdin)['tunnels'][0]['public_url'])"
This gives you a tensorboard from the log files created. And it works with TF1.13

Run localhost server in Google Colab notebook

I am trying to implement Tacotron speech synthesis with Tensorflow in Google Colab using this code form a repo in Github, below is my code and working good till the step of using localhost server, how I can to run a localhost server in a notebook in Google Colab?
My code:
!pip install tensorflow==1.3.0
import tensorflow as tf
print("You are using Tensorflow",tf.__version__)
!git clone https://github.com/keithito/tacotron.git
cd tacotron
pip install -r requirements.txt
!curl https://data.keithito.com/data/speech/tacotron-20180906.tar.gz | tar xzC /tmp
!python demo_server.py --checkpoint /tmp/tacotron-20180906/model.ckpt #requires localhost
Unfortunately running in local mode from Google Colab will not help me because to do this I need to download the data in my machine which are too large.
Below is my last output and here I am supposed to open the localhost:8888 to complete the work, so as I mentioned before is there any way to run localhost in Google Colaboratory?
You can do this by using tools like ngrok or remote.it
They give you a URL that you can access from any browser to access your web server running on 8888
Example 1: Tunneling tensorboard running on
!wget https://bin.equinox.io/c/4VmDzA7iaHb/ngrok-stable-linux-amd64.zip
!unzip ngrok-stable-linux-amd64.zip
get_ipython().system_raw('tensorboard --logdir /content/trainingdata/objectdetection/ckpt_output/trainingImatges/ --host 0.0.0.0 --port 6006 &')
get_ipython().system_raw('./ngrok http 6006 &')
! curl -s http://localhost:4040/api/tunnels | python3 -c \
"import sys, json; print(json.load(sys.stdin)['tunnels'][0]['public_url'])"
Running this install ngrok on colab, and makes a link like http://c11e1b53.ngrok.io/
Documentaion for NGROK
Another way of running a publicly accessible server using ngrok:
!pip install pyngrok --quiet
from pyngrok import ngrok
# Terminate open tunnels if exist
ngrok.kill()
# Setting the authtoken (optional)
# Get your authtoken from https://dashboard.ngrok.com/auth
NGROK_AUTH_TOKEN = ""
ngrok.set_auth_token(NGROK_AUTH_TOKEN)
# Open an HTTPs tunnel on port 5000 for http://localhost:5000
public_url = ngrok.connect(port="5000", proto="http", options={"bind_tls": True})
print("Tracking URL:", public_url)
You can use localtunnel to expose the port to the public internet.
Install localtinnel:
!npm install -g localtunnel
Start localtunnel:
!lt --port 8888
Navigate to the url it returns to access your web UI.

Unable to access locust on web-UI using docker

I have installed locust inside docker, i mapped docker port as well but when I run locust command I get below error, I am able to run locust on command line but not on Web-ui, may be i may miss-understood which host or port should use while accessing.
COMMAND:
locust -f locustfile.py
Error:
oserror errno 97 address family not supported by protocol
Command:
locust -f locustfile.py --web-host=localhost
Result:
[2019-12-18 11:24:47,101] ABZ-218/INFO/locust.main: Starting web
monitor at http://localhost:8089
[2019-12-18 11:24:47,102] ABZ-218/INFO/locust.main: Starting Locust 0.13.2
but not able to access it on browser.
I have mapped port 0.0.0.0:8089->80
so which command should i use while hitting locust and which command should i use while accessing it from chrome browser?
--web-host=localhost is not needed, by default locust will listen on all interfaces. Try removing it and seeing if that helps.
You can find the IP Address of where your application is running and pass that as an argument to --host e.g. --host http://127.0.0.1:8000.

Running HTML file in localhost:8080

I want to run an HTML file in localhost:8080, I'm using the command:
python3 -m http.server
Problem is when I try to open localhost:8080 it downloads the HTML file instead of displaying it.
Problem is when I try to open localhost:8080 it downloads the HTML file instead of displaying it.
You want to open http://localhost:8000 instead.
When you use the command you mentioned, python3 -m http.server, it defaults to port 8000, as explained in its startup output:
$ python3 -m http.server
Serving HTTP on 0.0.0.0 port 8000 (http://0.0.0.0:8000/) ...
We don't know what different server you have running on port 8080, but apparently it doesn't put Content-type: text/html in its output headers.
viewing webserver http headers
It's easy to view those headers, e.g. with wget use the -S switch.
You need to add an option that'll put your website on port 8080 because the http.server command defaults to port 8000.
You can do this using:
python3 -m http.server 8080
Then when you go to 0.0.0.0:8080 it should show you your webpage instead of a download prompt.
Also, you might have another instance of http.server running on port 8080.
You can find the PID of this task using:
ps -A | grep "python3"
Which should show something that looks like this:
Then you could kill it using:
kill <PID-FOR-PYTHON3-INSTANCE>
Or in my case the task that's running on port 8080 is:
kill 6856
Or, if you don't mind, just kill all Python3 tasks using:
killall python3
Which in my case would kill both Python3 tasks.
WARNING: be very, VERY careful before running the killall command, because this command will NOT save your work.
UPDATE: that blurry section in the picture is my username, I wasn't sure if it would be against the rules to include it.
Good luck.

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