I have a query that I am using qiskit.aqua.algorithms.QGAN library and using the qgan function and I am having difficulty in loading data of dimension 1000 rows x 10 columns. I am following qiskit's github tutorial for qgan learning and loading, however I did tested out that the tutorial was with 1000 rows and 1 column and is working fine. It did works till 2 columns but for more than 2 columns the function returns error. I don't understand if the same dataset is of 1 or 2 column it works but as soon as the data is reshaped to 3 or more columns, it returns this error:

AttributeError                            Traceback (most recent call last)
<ipython-input-36-1df19589f511> in <module>
      7  # Initialize qGAN
----> 8 qgan = QGAN(real_data, bounds, num_qubits, batch_size, num_epochs, snapshot_dir=None)
      9 qgan.seed = 1
D:\Users\Bro\anaconda3\lib\site-packages\qiskit\aqua\algorithms\distribution_learners\qgan.py in __init__(self, data, bounds, num_qubits, batch_size, num_epochs, seed, discriminator, generator, tol_rel_ent, snapshot_dir, quantum_instance)
    126                 self._num_qubits = np.array([3])
    127         self._data, self._data_grid, self._grid_elements, self._prob_data = \
--> 128             discretize_and_truncate(self._data, self._bounds, self._num_qubits,
    129                                     return_data_grid_elements=True,
    130                                     return_prob=True, prob_non_zero=True)
D:\Users\Bro\anaconda3\lib\site-packages\qiskit\aqua\utils\dataset_helper.py in discretize_and_truncate(data, bounds, num_qubits, return_data_grid_elements, return_prob, prob_non_zero)
    214             for grid_element in grid_elements:
    215                 for element_current in elements_current_dim:
--> 216                     temp.append(deepcopy(grid_element).append(element_current))
    217             grid_elements = deepcopy(temp)
    218             data_grid.append(elements_current_dim)
AttributeError: 'NoneType' object has no attribute 'append'

Any solution for the same?? PS:- I am trying to load even bigger dimensional dataset so please help in this.


Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Browse other questions tagged or ask your own question.