how to adjust the dimension of the feature vector output by the ReID module?

[lianghaochen1]

Hello, I am applying SUSHI to a custom MOT dataset I created, with the dataset format following MOT17. Considering that the target size in my dataset is not large (I resized the ReID box images to 48*96), and there are minimal appearance changes during movement, I wanted to reduce the dimension of the feature vector output by the ReID module. So I modified the "--node_dim" in SUSHI-main/configs/config.py from 2048 to 256.

However, after running it, an error occurred:

RuntimeError
mat1 dim 1 must match mat2 dim 0
File "/workspace/lianghaochen/SUSHI-main/src/models/mpntrack.py", line 32, in forward return self.fc_layers(input) File "/workspace/lianghaochen/SUSHI-main/src/models/mpntrack.py", line 153, in forward out_node_feats = self.node_mlp(nodes_feats) File "/workspace/lianghaochen/SUSHI-main/src/models/mpntrack.py", line 368, in forward latent_edge_feats, latent_node_feats = self.encoder(edge_attr, x) File "/workspace/lianghaochen/SUSHI-main/src/models/hiclnet.py", line 59, in forward return self.layers[ix_layer](data, node_level_embed=node_level_embed, edge_level_embed=edge_level_embed) File "/workspace/lianghaochen/SUSHI-main/src/tracker/hicl_tracker.py", line 354, in hicl_forward outputs = self.model(curr_batch, curr_depth) # Forward pass for this specific depth File "/workspace/lianghaochen/SUSHI-main/src/tracker/hicl_tracker.py", line 271, in _train_epoch _, loss, logs = self.hicl_forward(hicl_graphs = hicl_graphs, File "/workspace/lianghaochen/SUSHI-main/src/tracker/hicl_tracker.py", line 479, in train epoch_train_logs = self._train_epoch() File "/workspace/lianghaochen/SUSHI-main/scripts/main.py", line 39, in hicl_tracker.train() RuntimeError: mat1 dim 1 must match mat2 dim 0

So, I modified node_in_dim in SUSHI-main/configs/mpntrack_cfg.yaml from 2048 to 256, but the error remains unchanged.
thank you

[lianghaochen1]

When I changed "--node_dim" and "node_in_dim" back to the original 2048, the model ran normally.

[lianghaochen1]

I adjusted the FASTREID section, changing the dimension of the output feature vectors to 256, and retrained the REID network. This allowed the model to run smoothly.