A question

[cailv]

Hello, I read your paper on DP_CGAN and installed DP_CGAN on pytorch. But I got an error when I ran the code example you gave me. I would like to know what solutions you have?
My code:
from dp_cgans import DP_CGAN
import pandas as pd

tabular_data=pd.read_csv("C:/Users/lenovo/Desktop/workbook1.csv")

model = DP_CGAN(epochs=100)

print("Start training model")
model.fit(tabular_data)

#Generate 100 synthetic rows
syn_data = model.sample(100)
syn_data.to_csv("C:/Users/lenovo/Desktop/workbook.csv")

Error content:

TypeError Traceback (most recent call last)
Cell In[4], line 10
7 model = DP_CGAN(epochs=100)
9 print("Start training model")
---> 10 model.fit(tabular_data)
12 # Generate 100 synthetic rows
13 syn_data = model.sample(100)

File E:\anaconda3\envs\pytorch\lib\site-packages\dp_cgans\base.py:143, in BaseTabularModel.fit(self, data)
140 if self.metadata.get_dtypes(ids=False):
141 LOGGER.debug(
142 'Fitting %s model to table %s', self.class.name, self.metadata.name)
--> 143 self._fit(transformed)

File E:\anaconda3\envs\pytorch\lib\site-packages\dp_cgans\dp_cgan_init.py:59, in DPCGANModel._fit(self, table_data)
55 categories.append(field)
57 # print(table_data[categoricals])
---> 59 self._model.fit(
60 table_data,
61 discrete_columns=categoricals
62)

File E:\anaconda3\envs\pytorch\lib\site-packages\dp_cgans\synthesizers\dp_cgan.py:488, in DPCGANSynthesizer.fit(self, train_data, discrete_columns, epochs)
485 # condvec = self._data_sampler.sample_condvec(self._batch_size)
487 condvec_pair = self._data_sampler.sample_condvec_pair(self._batch_size)
--> 488 c_pair_1, m_pair_1, col_pair_1, opt_pair_1 = condvec_pair
490 # if condvec is None:
491 # c1, m1, col, opt = None, None, None, None
492 # real = self._data_sampler.sample_data(self._batch_size, col, opt)
(...)
502 # self._batch_size, col[perm], opt[perm])
503 # c2 = c1[perm]
505 if condvec_pair is None:

TypeError: cannot unpack non-iterable NoneType object

Looking forward to your reply!