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Help request to reproduce the Table 2 results

Hi @AdamDHines,

I was trying to reproduce Table 2 results in your paper. Would you share the code that generated the VPRSNN results? I previously asked Somayeh's help here a month ago. However, I have not heard back from her yet.

I would like to ask your help for reproducing VPRTempo's results as well. I started with working on the Nordland data first. I downloaded the data and organized the directories accordingly. This is my input to the terminal.

python main.py --train_new_model --max_module 3300 --database_places 3300

It does not throw any errors during the training. However, it looks like it is terminating the training process prematurely.

adamq1

When I try to test the trained model by using the following command in the terminal

python main.py --max_module 3300 --database_places 3300

I get the error below

Click to expand
Initializing modules: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00,  2.48it/s]
Model name: springfall_VPRTempo_IN3136_FN6272_DB3300.pth
Running the test network:  70%|█████████████████████████████████████████████████████████████████████████████████████████████████▍                                          | 348/500 [00:01<00:00, 212.59it/s]
Traceback (most recent call last): File "main.py", line 269, in parse_network(use_quantize=False, File "main.py", line 265, in parse_network initialize_and_run_model(args,dims) File "main.py", line 200, in initialize_and_run_model run_inference(models, model_name) File "/home/bertha/Documents/VPRTempo/vprtempo/VPRTempo.py", line 320, in run_inference model.evaluate(models, test_loader) File "/home/bertha/Documents/VPRTempo/vprtempo/VPRTempo.py", line 144, in evaluate for spikes, label in test_loader: File "/home/bertha/.pyenv/versions/vprtempo_env/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 631, in __next__ data = self._next_data() File "/home/bertha/.pyenv/versions/vprtempo_env/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 1326, in _next_data return self._process_data(data) File "/home/bertha/.pyenv/versions/vprtempo_env/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 1372, in _process_data data.reraise() File "/home/bertha/.pyenv/versions/vprtempo_env/lib/python3.8/site-packages/torch/_utils.py", line 705, in reraise raise exception IndexError: Caught IndexError in DataLoader worker process 5. Original Traceback (most recent call last): File "/home/bertha/.pyenv/versions/vprtempo_env/lib/python3.8/site-packages/torch/utils/data/_utils/worker.py", line 308, in _worker_loop data = fetcher.fetch(index) # type: ignore[possibly-undefined] File "/home/bertha/.pyenv/versions/vprtempo_env/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py", line 49, in fetch data = self.dataset.__getitems__(possibly_batched_index) File "/home/bertha/.pyenv/versions/vprtempo_env/lib/python3.8/site-packages/torch/utils/data/dataset.py", line 419, in __getitems__ return [self.dataset[self.indices[idx]] for idx in indices] File "/home/bertha/.pyenv/versions/vprtempo_env/lib/python3.8/site-packages/torch/utils/data/dataset.py", line 419, in return [self.dataset[self.indices[idx]] for idx in indices] File "/home/bertha/Documents/VPRTempo/vprtempo/src/dataset.py", line 195, in __getitem__ img_path = self.img_labels.iloc[idx]['file_path'] File "/home/bertha/.pyenv/versions/vprtempo_env/lib/python3.8/site-packages/pandas/core/indexing.py", line 1103, in __getitem__ return self._getitem_axis(maybe_callable, axis=axis) File "/home/bertha/.pyenv/versions/vprtempo_env/lib/python3.8/site-packages/pandas/core/indexing.py", line 1656, in _getitem_axis self._validate_integer(key, axis) File "/home/bertha/.pyenv/versions/vprtempo_env/lib/python3.8/site-packages/pandas/core/indexing.py", line 1589, in _validate_integer raise IndexError("single positional indexer is out-of-bounds") IndexError: single positional indexer is out-of-bounds
Running the test network:  71%|███████████████████████████                                     | 357/500 [00:01<00:00, 191.34it/s]

I would appreciate it if you could help me.

Thanks in advance.

Best,
Bertha

RuntimeWarning: All-NaN slice encountered

This error occurs when testing the network. If a particular query does not give any output spikes and you try to calculate the PR curves.

Solution is to detect when no output spikes present and select the output neuron with the highest sub-threshold input.

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