Closed jojker closed 4 years ago
The examples need work if anyone is to learn talos from nothing.
I used a work around (just used wget to fetch the datasets.py file). However, most other things in the example are also broken. ta.Scan
does not work (the downsampling feature is broken as in issue #299). Changing to the daily-dev (and changing the names of input arguments) fixes issue #299 but leaves more things broken. Commands like r.high()
do not function with the latest version (it now requires inputs), and none of the plotting functions will display (which may be an astetik failure in colab). The evaluate section includes the average='macro'
argument which does not exist in the daily-dev version.
EDIT: the plotting functions work if you enter these commands at the beginning:
import seaborn as sns
sns.set()
For now, my recommendation is to use a >=0.6.2 version and refer to the examples in the docs. But you are right, the notebook examples need to be synced with the latest version. Some of those were done very early in Talos development.
Regarding datasets, the way to access that is:
talos.templates.datasets.iris()
as it is explained in the templates section of the docs.
Closing here as this is resolved.
The examples cannot run because they rely on the datasets attribute of the talos module, and this attribute is not included with the installation. At least this is true on colab.
Go to the example: https://colab.research.google.com/github/autonomio/talos/blob/master/examples/Hyperparameter%20Optimization%20with%20Keras%20for%20the%20Iris%20Prediction.ipynb
Before running add a new first cell containing only:
!pip install talos
When trying to run all, the code cell containing
x, y = ta.datasets.iris()
will result in the following error:The full code to copy into an arbitray notebook on colab is (you may try restarting the runtime and running a second time with the requirements installed):