pip install error inside Docker container: Failed to establish a new connection: [Errno -3] Temporary failure in name resolution

Trying to install some Python packages with pip inside a Docker container I ran into this issue:

# pip3 install pytest
Collecting pytest
  Retrying (Retry(total=4, connect=None, read=None, redirect=None, status=None)) after connection broken by 'NewConnectionError('<pip._vendor.urllib3.connection.VerifiedHTTPSConnection object at 0x7feb52c30630>: Failed to establish a new connection: [Errno -3] Temporary failure in name resolution',)': /simple/pytest/

At first I thought this something to do with network restrictions since I’m running this on a Linux AWS Workspace, but I have internet access enabled. Running the command on the Workspace itself works as expected, so this is something specific to the Docker container. Next I thought this might be something to do with the specific container image I was using, but after trying a few others I had the same error on any container.

Searching for the error “Failed to establish a new connection: [Errno -3] Temporary failure in name resolution” online I found this question and answer, and suggested to run the Docker container with the host networking option.

So instead of running bash in the container like this:

$ docker run -it tensorflow/tensorflow:1.12.0-py3 bash

Pass in the network=host option like this:

$ docker run --network=host -it tensorflow/tensorflow:1.12.0-py3 bash
# pip3 install pytest
Collecting pytest
  Downloading https://files.pythonhosted.org/packages/b1/ee/53945d50284906adb1e613fabf2e1b8b25926e8676854bb25b93564c0ce7/pytest-6.1.2-py3-none-any.whl (272kB)
    100% |################################| 276kB 9.4MB/s 

Problem solved!

AWS Workspaces: Web access to Linux Workspaces (not supported)

If you attempt to access an AWS Workspace running Linux via a browser, you’ll get his spinner for what seems like a couple of minutes:

Eventually it times out with this error:

Looking in the docs here this is this note:

Web access to Linux WorkSpaces is currently not supported. Would be nice if it gave you an error when to attempt to logon to tell you it’s not a supported option instead of just falling.

Experimenting with the gpt-2 models and text generation

I’m experimenting with the gpt-2 774M model to generate text based on a prompt. Starting up with:

python3 src/interactive_conditional_samples.py --temperature=0.7 --model_name=774M --nsamples=1 --length=100

And then providing a prompt of something relevant like :

“The problem with training Machine Learning models today is that the model is only as good as the data it is trained with.”

and let’s see what we get:

This almost sounds believable as if it was written by hand. It might not make complete sense, but the sentences are well formed, something that was an issue with my previous experimenting with RNN model text generation.

Here’s. the text for reference:

“There is a desire to train the model on a large data set.

A very big data set is not always a good enough data set.

A good data set is more than just enough. A good data set is always growing.

To take advantage of this growing data set we need to train the model on the latest batch of data. However, there may be a huge amount of data that does not fit in the pre-defined batch size.”

I’m curious how the temperature setting effects what is generated, so let’s bump it up from 0.7 to 0.9 and try again with the same prompt text.

This sounds like it comes straight out of a research paper:

“This is why there is now a trend toward training a workforce of highly trained humans in a search engine optimization function (SRE) to monitor changes in signal and value in the big data.

Whether it is a search engine algorithm like Chi-squared or a machine learning model like a neural network, there is still a lot of work ahead to make those apps more relevant to the data they collect.

The need for better data

Having data that makes the predictions bigger, on”

Not knowing exactly how this works, it almost reads like it’s regurgitating whole chunks of the data it was trained on, but who knows. Given that it was trained from materials and sites online, I guess the easy way to test for this would be to just drop one of these sentences in Google and see if something like the source article comes up. Trying this out:

Huh. So this sentence is not found anywhere in Google’s indexes. That’s quite remarkable if the model actually generates sentences that are this convincing.

What about starting with a line from a recipe (for example from here):

“Heat oil in large pot. Add beef and flour, stirring to coat beef; brown.”

Ok, now this is interesting but slightly weird. It’s clearly recognizable as steps in a recipe, but the order doesn’t make too much sense and some of the steps are repeated variations of themselves:

“Add onions and garlic and cook until onion starts to turn translucent, 3 minutes. Stir in bell pepper, glass tomatoes, and celery; cook 1 minute. Add potatoes, beef broth, and bay leaves; bring to a boil. Reduce heat to low. Reduce heat to medium; cook until beef is no longer pink. Taste and add salt and pepper. Add beef and stir. Add liquid; cover and simmer until meat is tender, 10 minutes.”

What about lines from films?

“I find your lack of faith disturbing”

Now we’re gone off into Crazy Town. This is weird:

“Why do you persist in viewing my appearance with contempt?”

“I want to believe I am worthy of your worship.”

“Therefore, you have no right to demand I lift my gaze.”

“I am unworthy of your reverence; I can only pray that you may address me in a less lewd manner.”

“You call me a beast?”

“You cannot deny the very fact you see me.”

“I see nothing.”


Whoah. Ok, keeping with the Star Wars theme, what does it do if you start it with some Yoda quotes:

“When 900 years old you reach, look as good you will not”

And I got:

“I listen to every guru and I say, good luck with your yoga and counting numbers.”

Does this phrase exist anywhere?

Nope. You have to wonder if there were some Joda quotes or lines from films that went into the model, it’s interesting that ‘yoga’ is mentioned, and you wonder if this is the model generating a variation of the name ‘Yoda’. And ‘When 900 years old you reach” = “Counting numbers”? Very curious.

Ok, one more. How about a line from an HP monitor product description:

“Designed with purpose: multiple customization options allow you to adjust your monitor to best fit the way you work.”


“Customizable paired ergonomics and colors: customize every feature of your new monitor from its basic design and color customization options.

Intuitive control links: there are more than 100

cabling connections provided with each monitor.

Designed for comfort: more than twice as many inches of space between the screen and the desk top than standard monitors.

Dedicated power buttons for powering the monitor on and off.”

Ok, enough playing, I did have a project planned to use with this, so time to get busy 🙂