Comments (6)
This is the code snippet is here
# After GAN is trained
# Load the final checkpoint
gan.load()
# train_data_feature, train_data_attribute are loaded from https://github.com/fjxmlzn/DoppelGANger/blob/e732a4d077ba1504e6e401df9c2d1048c8efb2a9/example_training/gan_task.py#L20-L45
d_train = gan.discriminate_from(
[train_data_feature], [train_data_attribute])
# test_data_feature, test_data_attribute are loaded by the same way, except passing flag="test" to load_data
d_test = gan.discriminate_from(
[test_data_feature], [test_data_attribute])
num_train = train_data_feature.shape[0]
sort_id = np.argsort(list(d_train) + list(d_test))[::-1]
acc = np.where(sort_id[0: num_train] < num_train)[0].shape[0] / float(num_train)
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What is "acc" meaning here?
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The attack accuracy, y-axis of Figure 15
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Thanks.
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Hey,
I need some help.
I understand from here # train_data_feature, train_data_attribute are loaded from https://github.com/fjxmlzn/DoppelGANger/blob/e732a4d077ba1504e6e401df9c2d1048c8efb2a9/example_training/gan_task.py#L20-L45
Could you please explain little bit before that like, "load and call DoppleGANger".
Thanks for your help.
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What I meant is that you can just append these codes at the end of https://github.com/fjxmlzn/DoppelGANger/blob/master/example_training/gan_task.py, where DoppelGANger is trained
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Related Issues (20)
- CLI getting stuck on running example_training/main.py HOT 2
- Dynamic attributes / attributes with time stamp? HOT 6
- Request for min/max used for feature and attribute normalization in input data HOT 2
- The data generated ranges from 0 to 2 HOT 3
- Incomplete training HOT 7
- unreasonable output HOT 6
- Dataset HOT 1
- About two MLPs HOT 1
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- Generating time series with negative values HOT 4
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- Request for availability of the scripts used to reproduce figures HOT 8
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