DL-Art-School/.idea/mmsr.iml
James Betker 44b89330c2 Support inference across batches, support inference on cpu, checkpoint
This is a checkpoint of a set of long tests with reduced-complexity networks. Some takeaways:
1) A full GAN using the resnet discriminator does appear to converge, but the quality is capped.
2) Likewise, a combination GAN/feature loss does not converge. The feature loss is optimized but
    the model appears unable to fight the discriminator, so the G-loss steadily increases.

Going forwards, I want to try some bigger models. In particular, I want to change the generator
to increase complexity and capacity. I also want to add skip connections between the
disc and generator.
2020-05-04 08:48:25 -06:00

19 lines
880 B
XML

<?xml version="1.0" encoding="UTF-8"?>
<module type="PYTHON_MODULE" version="4">
<component name="NewModuleRootManager">
<content url="file://$MODULE_DIR$">
<sourceFolder url="file://$MODULE_DIR$/codes" isTestSource="false" />
<excludeFolder url="file://$MODULE_DIR$/codes/temp" />
<excludeFolder url="file://$MODULE_DIR$/datasets" />
<excludeFolder url="file://$MODULE_DIR$/experiments" />
<excludeFolder url="file://$MODULE_DIR$/results" />
<excludeFolder url="file://$MODULE_DIR$/tb_logger" />
</content>
<orderEntry type="jdk" jdkName="Python 3.7 (python37-torch)" jdkType="Python SDK" />
<orderEntry type="sourceFolder" forTests="false" />
</component>
<component name="PyDocumentationSettings">
<option name="format" value="PLAIN" />
<option name="myDocStringFormat" value="Plain" />
</component>
</module>