forked from ecker/DL-Art-School
Got rid of the converged multiplexer bases but kept the configurable architecture. The new multiplexers look a lot like the old one. Took some queues from the transformer architecture: translate image to a higher filter-space and stay there for the duration of the models computation. Also perform convs after each switch to allow the model to anneal issues that arise. |
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| .. | ||
| .idea | ||
| data | ||
| data_scripts | ||
| metrics | ||
| models | ||
| options | ||
| scripts | ||
| temp | ||
| utils | ||
| distill_torchscript.py | ||
| onnx_inference.py | ||
| process_video.py | ||
| requirements.txt | ||
| run_scripts.sh | ||
| test.py | ||
| train.py | ||