Dear Community, As some of you may have already encountered, MXNet has a limitation in supporting tensors of size greater than ~4.3 billion elements (2^32). The root cause is because in MXNet backend 32-bit integer type is used as the default integer data type for both computation and storage in many places.
Uplifting this limitation, however, is not simply replacing all 32-bit integers by a larger data type (64-bit integer) as I detailed them in the design proposal at https://cwiki.apache.org/confluence/display/MXNET/Large+Tensor+Support. It requires a systematic approach to address this problem in MXNet backend as well as all APIs in different language bindings. I will appreciate your suggestions in solving this problem systematically and elegantly, as well as your help to support in different language bindings other than Python. Please add your comment in the design proposal or create tickets in the JIRA epic: https://issues.apache.org/jira/browse/MXNET-1184 Best Regards, Lin
