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TensorFlow and Cloud
In case you require to install a specific version or a module not part of the default
Colaboratory environment you can use pip install or apt-get install. For
example, the following command on being executed in the Colab notebook cell will
install TensorFlow GPU 2.0 version:
! pip install tensorflow-gpu
At the time of writing this book the default version of TensorFlow
was 1.15, with a message that it will be shifting soon to TensorFlow
2.0, the NumPy version was 1.17.3, Matplotlib 3.1.1, and Pandas
0.25.3.
If you are interested to know the hardware details of the environment where
Colaboratory notebooks run, you can get the info using the cat command:
For processor:
!cat /proc/cpuinfo
For memory:
!cat /proc/meminfo
To run these starting commands and get the version information for your region, you
can use the following Colaboratory Notebook:
https://colab.research.google.com/drive/1i60H5hcJShrMKhytBUlItJ7Win0o
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Just like the standard Jupyter notebook, you can run the Unix command line
commands directly in the Notebook prefixed by an exclamation mark "!".
You can also mount your Google Drive and access the files you have saved in your
drive. To do this you will use:
from google.colab import drive
drive.mount('/content/drive/')
This will generate a link. After clicking the link you will get an authorization code,
and entering the authorization code will give the notebook access to your drive. You
can check the content of your drive using !ls "/content/drive/My Drive" and
access any of the folders in it by specifying the path.
The Colab interface is very similar to Jupyter, so now you are all set to run your
machine learning experiments on Colaboratory. One disadvantage of Colaboratory is
that it does not work well in presentation mode. Fortunately, for that we have Azure
Notebooks.
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