Hi,
I’m migrating my code from fastai1 and there it was easy to get the confusion matrix through TextClassificationInterpretation. However, in fastai2, there is no specific TextClassificationInterpretation and if I try something similar with just ClassificationInterpretation, like this:
interpreter = ClassificationInterpretation.from_learner(self._classifier, ds_idx=1)
interpreter.confusion_matrix()
I get this error:
interpreter = ClassificationInterpretation.from_learner(self._classifier, ds_idx=0)
File "/usr/local/lib/python3.8/site-packages/fastai/interpret.py", line 29, in from_learner
return cls(dl, *learn.get_preds(dl=dl, with_input=True, with_loss=True, with_decoded=True, act=None))
File "/usr/local/lib/python3.8/site-packages/fastai/learner.py", line 260, in get_preds
if reorder and hasattr(dl, 'get_idxs'): res = nested_reorder(res, tensor(idxs).argsort())
File "/usr/local/lib/python3.8/site-packages/fastai/torch_core.py", line 135, in tensor
else _array2tensor(array(x), **kwargs))
File "/usr/local/lib/python3.8/site-packages/fastai/torch_core.py", line 121, in _array2tensor
return torch.from_numpy(x)
TypeError: can't convert np.ndarray of type numpy.object_. The only supported types are: float64, float32, float16, complex64, complex128, int64, int32, int16, int8, uint8, and bool.
My input dataframe looks like this:
phrase object
intent object
is_validation int64
dtype: object
How can I make it work?