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License: MIT License
The official implementation for Sequential Recommendation with Latent Relations based on Large Language Model
License: MIT License
Traceback (most recent call last):
File "main.py", line 132, in
main()
File "main.py", line 90, in main
logging.info('Test Before Training: ' + runner.print_res(model, data_dict['test']))
File "E:\LRD-main\src\helpers\BaseRunner.py", line 243, in print_res
result_dict = self.evaluate(model, data, self.topk, self.metrics)
File "E:\LRD-main\src\helpers\BaseRunner.py", line 206, in evaluate
predictions = self.predict(model, data)
File "E:\LRD-main\src\helpers\BaseRunner.py", line 225, in predict
out_dict = model(utils.batch_to_gpu(batch, model.device))
File "D:\Software\Anaconda\envs\dccf\lib\site-packages\torch\nn\modules\module.py", line 1110, in _call_impl
return forward_call(*input, **kwargs)
File "E:\LRD-main\src\models\sequential\KDAPlus.py", line 148, in forward
prediction = self.rec_forward(feed_dict)
File "E:\LRD-main\src\models\sequential\KDAPlus.py", line 251, in rec_forward
context, target_attention = self.relational_dynamic_aggregation(
File "D:\Software\Anaconda\envs\dccf\lib\site-packages\torch\nn\modules\module.py", line 1110, in _call_impl
return forward_call(*input, **kwargs)
File "E:\LRD-main\src\models\sequential\KDAPlus.py", line 466, in forward
target_attention = torch.where(valid_mask.squeeze(1).repeat(1,1,self.n_relation), target_attention, 0.)
RuntimeError: expected scalar type float but found double
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