- qiskit version : 0.18.0
- numpy version : 1.21.1
- qiskit_machine_learning version : 0.2.0
- qiskit.aqua version : 0.9.4
I am trying to run a simple code as described in Qiskit's tutorial on Machine Learning.
feature_dim=2
training_dataset_size=20
testing_dataset_size=10
random_seed=10598
shots=10000
sample_Total,training_input,test_input,class_labels =
ad_hoc_data(training_size=training_dataset_size,
test_size=testing_dataset_size,
gap=0.3,
n=feature_dim,
plot_data=True)
datapoints,class_to_label=split_dataset_to_data_and_labels(test_input)
But I receive the error
AttributeError Traceback (most recent call last)
<ipython-input-11-f11e4f763266> in <module>
10 n=feature_dim,
11 plot_data=True)
---> 12 datapoints,class_to_label=split_dataset_to_data_and_labels(test_input)
~\anaconda3\lib\site-packages\qiskit\aqua\utils\dataset_helper.py in split_dataset_to_data_and_labels(dataset, class_names)
83 labels = []
84 if class_names is None:
---> 85 sorted_classes_name = sorted(list(dataset.keys()))
86 class_to_label = {k: idx for idx, k in enumerate(sorted_classes_name)}
87 else:
AttributeError: 'numpy.ndarray' object has no attribute 'keys'
By which I assume (and checked by printing it) that ad_hoc_data(...)
is resulting in test_input
in numpy.ndarray type as opposed to the expected dict type.
Is there something trivial I'm missing here or is there an actual issue with the code?
Thanks in advance