GitHub actions#364
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predict() cloned the whole model on every call and then used model.predict(). When predict() runs once per solution inside a fitness function, this is slow. It now sets the solution as the model weights, restores the original weights at the end, and calls the model directly when no batching is asked for. The output is the same and it runs much faster. model.predict() is still used when batch_size or steps is given.
📊 Change summary7 files changed · +59 / −11 lines pie showData
title Lines changed per file (70 total)
"pygad/kerasga/kerasga.py" : 28
"docs/source/images/pygad_vilvik_cloud.svg" : 24
"docs/source/index.md" : 12
".gitignore" : 3
"pygad/kerasga/__init__.py" : 2
"pygad/pygad.py" : 1
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