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src/aiia/model/Model.py
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@ -193,8 +193,8 @@ class AIIAmoe(AIIA):
# To generate gating weights, we first need to determine the feature dimension.
# Each expert is assumed to return an output of shape (B, C, H, W); after averaging over H and W,
# we obtain a tensor of shape (B, C) where C is the number of channels (here assumed to be 224).
gate_in_features = 512 # Adjust this if your expert output changes.
# we obtain a tensor of shape (B, C) where C is the number of channels (here assumed to be 410).
gate_in_features = 410 # Adjust this if your expert output changes.
# Create a gating network that maps the aggregated features to num_experts weights.
self.gate = nn.Sequential(