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@@ -56,6 +56,9 @@ class ConvGAN(GanBaseClass):
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self.maj_min_discriminator = None
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self.cg = None
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+ if neb > gen:
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+ raise ValueError(f"Expected neb <= gen but got neb={neb} and gen={gen}.")
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+
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def reset(self):
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"""
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Resets the trained GAN to an random state.
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@@ -70,6 +73,16 @@ class ConvGAN(GanBaseClass):
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## instanciate network and visualize architecture
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self.cg = self._convGAN(self.conv_sample_generator, self.maj_min_discriminator)
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+ if self.debug:
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+ print(self.conv_sample_generator.summary())
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+ print('\n')
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+
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+ print(self.maj_min_discriminator.summary())
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+ print('\n')
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+
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+ print(self.cg.summary())
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+ print('\n')
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+
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def train(self, dataSet):
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"""
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Trains the GAN.
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@@ -212,7 +225,7 @@ class ConvGAN(GanBaseClass):
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min_batch = Lambda(lambda x: x[:self.neb])(batch_data)
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## extract majority batch
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- maj_batch = Lambda(lambda x: x[self.neb:])(batch_data)
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+ maj_batch = Lambda(lambda x: x[self.gen:])(batch_data)
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## pass minority batch into generator to obtain convex space transformation
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## (synthetic samples) of the minority neighbourhood input batch
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