Buffer dtype mismatch, expected 'int' but got 'long'

[BelkissDS]

File "/opt/ml/processing/input/code/train.py", line 934, in <module> output_dir=args.output_dir File "/opt/ml/processing/input/code/train.py", line 903, in run_model output_dir File "/opt/ml/processing/input/code/train.py", line 867, in run_lightfm_model num_threads=num_threads, File "/opt/ml/processing/input/code/train.py", line 832, in fit_model num_threads=num_threads, File "/usr/local/lib/python3.7/site-packages/lightfm/lightfm.py", line 540, in fit verbose=verbose, File "/opt/ml/processing/input/code/train.py", line 755, in fit_partial verbose, File "/usr/local/lib/python3.7/site-packages/lightfm/lightfm.py", line 644, in fit_partial self.loss, File "/usr/local/lib/python3.7/site-packages/lightfm/lightfm.py", line 668, in _run_epoch self._get_positives_lookup_matrix(interactions) File "lightfm/_lightfm_fast_openmp.pyx", line 167, in lightfm._lightfm_fast_openmp.CSRMatrix.__init__ | Traceback (most recent call last): File "/opt/ml/processing/input/code/train.py", line 934, in <module> output_dir=args.output_dir File "/opt/ml/processing/input/code/train.py", line 903, in run_model output_dir File "/opt/ml/processing/input/code/train.py", line 867, in run_lightfm_model num_threads=num_threads, File "/opt/ml/processing/input/code/train.py", line 832, in fit_model num_threads=num_threads, File "/usr/local/lib/python3.7/site-packages/lightfm/lightfm.py", line 540, in fit verbose=verbose, File "/opt/ml/processing/input/code/train.py", line 755, in fit_partial verbose, File "/usr/local/lib/python3.7/site-packages/lightfm/lightfm.py", line 644, in fit_partial self.loss, File "/usr/local/lib/python3.7/site-packages/lightfm/lightfm.py", line 668, in _run_epoch self._get_positives_lookup_matrix(interactions) File "lightfm/_lightfm_fast_openmp.pyx", line 167, in lightfm._lightfm_fast_openmp.CSRMatrix.__init__

After looking, I guess large sparse matrices are not supported and this is basically happening due to the handling of large_indices directly in Cython. The interactions matrix shape is (10.000.000, 190.000)

[sijdev]

@BelkissDS I am currently experiencing this as well. I'm considering splitting my items into two and training the model a second time. How did you end up addressing this?