forked from ecker/DL-Art-School
- Add a network that accomodates this style of approximator while retaining structure - Migrate to SSIM approximation - Add a tool to visualize how these approximators are working - Fix some issues that came up while doign this work |
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| .. | ||
| archs | ||
| experiments | ||
| flownet2@db2b7899ea | ||
| steps | ||
| base_model.py | ||
| ExtensibleTrainer.py | ||
| feature_model.py | ||
| loss.py | ||
| lr_scheduler.py | ||
| networks.py | ||