Expected tensor for argument #1 'indices' to have scalar type Long; but got torch.IntTensor instead (while checking arguments for embedding)

[drishyamlabs]

Getting this error while running sample on windows 10, torch 1.7.1

Traceback (most recent call last):
File "main.py", line 116, in
main()
File "main.py", line 74, in main
logging.info('Test Before Training: ' + runner.print_res(model, data_dict['test']))
File "xxx\ReChorus-master\src\helpers\BaseRunner.py", line 221, in print_res
result_dict = self.evaluate(model, data, self.topk, self.metrics)
File "xxx\ReChorus-master\src\helpers\BaseRunner.py", line 197, in evaluate
predictions = self.predict(model, data)
File "xxx\ReChorus-master\src\helpers\BaseRunner.py", line 212, in predict
prediction = model(utils.batch_to_gpu(batch, model.device))['prediction']
File "xxx\lib\site-packages\torch\nn\modules\module.py", line 727, in _call_impl
result = self.forward(*input, **kwargs)
File "xxx\ReChorus-master\src\models\general\BPR.py", line 30, in forward
cf_u_vectors = self.u_embeddings(u_ids)
File "xxx\lib\site-packages\torch\nn\modules\module.py", line 727, in _call_impl
result = self.forward(*input, **kwargs)
File "xxx\lib\site-packages\torch\nn\modules\sparse.py", line 126, in forward
self.norm_type, self.scale_grad_by_freq, self.sparse)
File "xxx\lib\site-packages\torch\nn\functional.py", line 1852, in embedding
return torch.embedding(weight, input, padding_idx, scale_grad_by_freq, sparse)
RuntimeError: Expected tensor for argument #1 'indices' to have scalar type Long; but got torch.IntTensor instead (while checking arguments for embedding)

[THUwangcy]

Maybe it's the problem caused by PyTorch version (mine is 1.0). The direct solution is converting uid and iid to LongTensor in the beginning of the forward function:

u_ids = feed_dict['user_id'].long()
i_ids = feed_dict['item_id'].long()

[drishyamlabs]

Thanks a lot for your quick reply! this works