I'm using Kubernetes, and a training job runs on the cluster. I'm using TQDM as progress bar, but unlike what I've expected, the progress bar doesn't show up when I check Kubernetes Pod logs. Does anyone have a solution to this problem?
Usage. Using tqdm is very simple, you just need to add your code between tqdm() after importing the library in your code. You need to make sure that the code you put in between the tqdm() function must be iterable or it would not work at all.
tqdm derives from the Arabic word taqaddum (تقدّم) which can mean "progress," and is an abbreviation for "I love you so much" in Spanish (te quiero demasiado). Instantly make your loops show a smart progress meter - just wrap any iterable with tqdm(iterable) , and you're done!
tqdm 's command line interface (CLI) can be used in a script or on the terminal/console.
tqdm is a Python library that allows you to output a smart progress bar by wrapping around any iterable. A tqdm progress bar not only shows you how much time has elapsed, but also shows the estimated time remaining for the iterable.
Tqdm is a Python library used to display smart progress bars that show the progress of your Python code execution. This library can also be used to see the progress of a machine learning model while training the model on a very large data set. Sometimes it takes a lot of time while training a machine learning model on a very huge dataset.
The tqdm Python library helps make progress explicit. The tqdm module works with the console, but it also has special support for one of my favorite environments: Jupyter. To use tqdm in Jupyter, you need to import the notebook submodule and have ipywidgets installed. The notebook submodule is interface-compatible with tqdm.
There are multiple parameters in a tqdm; let us understand them one by one. Iterable – It can be a range, a list whose progress we have to check. The above output shows that a total of 200 iterations took place at a speed of 94.85 iterations per second. The total time was approx. 2 seconds.
Tutorials This section of the Kubernetes documentation contains tutorials. A tutorial shows how to accomplish a goal that is larger than a single task. Typically a tutorial has several sections, each of which has a sequence of steps.
I don't have a good solution, but this one helped me:
tqdm progress bar will show as expected if you use:
kubectl attach <pod_name>
instead of:
kubectl logs <pod_name>
So far unfortunately I haven't found a satisfying answer to this either. Depending on whether you use kubectl or k9s for example or even how the iterable looks like inside tqdm, or what else you log via for example the logging module, the results can be wildly different from no progress bar shown at all, to sporadic flushes of dozens of iterations. The only way I have found to get consistent kubernetes logs is printing them yourself every iteration and redirecting tqdm output to somewhere else.
For example as follows:
import time
import sys
from tqdm import tqdm
iterator = tqdm(range(99), file=open("/dev/null", "w"))
for x in iterator:
print(iterator.__str__())
sys.stdout.flush()
time.sleep(0.2)
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