Transfer Learning Errors

[FryLaurie]

First, Transfer Learning documentation needs an update. It references

`
data = dp.Data("your_file.csv")

model_results = data_labeler.fit(x=data['samples'], y=data['labels'],
validation_split=0.2, epochs=2, labels=labels)
`

Accessing the dp.Data object directly isn't subscriptable - you need the data property of the BaseData child class to access the embedded dataframe.

eg:
data = dp.Data("your_file.csv") data_frame = data.data model_results = data_labeler.fit(x=data_frame['samples'], y=data_frame['labels'], validation_split=0.2, epochs=2, labels=labels)

Second, when running a transfer learning per documented process, the package returns the following error:

ValueError: The default_label of UNKNOWN must exist in the label mapping.

This makes sense when extending with a new label, but transfer learning doesn't work as documented.