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Backup final base/rotation-layer and latest conv-layer experiments
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#!/usr/bin/env python3
"""Run the shared SiT trainer with the convolutional-layer model implementation."""
import os
import runpy
# Select models_conv.py before train.py imports the model registry, and require
# the shared trainer to fail closed if another model module is selected.
os.environ["SIT_MODEL_MODULE"] = "models_conv"
os.environ["SIT_EXPECTED_MODEL_MODULE"] = "models_conv"
runpy.run_module("train", run_name="__main__")