Update tutorials to revise the pip installation command for TFQ 0.7.5 and also avoid a couple of problems #949
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`docs/tutorial/mnist.ipynb` imports the `seaborn` package, but does not install it. It seems to come preinstalled in Colab and the DevSite toolchain, but someone running the notebook outside of those environments may hit a "module not found error". By adding a `!pip install seaborn` after installing TF and TFQ, we can not only save users the annoyance; we can also save future TFQ maintainers the time to debug the problem if they encounter the problem during local testing.
mhucka
changed the title
Versions of Gym after 0.24.1 have a compatibility problem with the code in the `quantum_reinforcement_learning.ipynb` tutorial. Making sure to get 0.24.1 solves that problem.
MichaelBroughton
approved these changes
Dec 27, 2025
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Changes:
Update the
!pip installcommand in all the tutorials indocs/tutorials/to usepip install tensorflow==2.16.2 tensorflow-quantum==0.7.5.Add a pip install of the Python package seaborn to the the MNIST tutorial. The tutorial imports
seaborn, but does not install it. Seaborn seems to come preinstalled in Colab and the DevSite toolchain, but someone running the notebook outside of those environments may hit a "module not found" error. By running a!pip install seabornafter installing TF and TFQ, we can not only save users the annoyance; we can also save future TFQ maintainers the time to debug the problem if they encounter the missing module during local testing.Pin the version of the Gym package installed in
docs/tutorials/quantum_reinformcement_learning.ipynb. Previously, the tutorial simply did a!pip install gymwithout a version constraint. Versions higher than 0.24.1 are incompatible some code in that tutorial (at least in TFQ 0.7.5), leading to an error during execution in some environments. Version 0.24.1 is what is installed byscripts/ci_validate_tutorials.sh; that's how I found the right version to make things work.