caiqi opened a new issue #8041: out of memory error on windows URL: https://github.com/apache/incubator-mxnet/issues/8041 ## Environment info Operating System: Windows Server 2016 MXNet version: 0.11.0 Or if installed from source: Install with pip install mxnet-cu80 Python version and distribution: 2.7 run python train_mnist.py in examples folder would cause out of memory error, which is weird since the memory is sufficient enough. > [17:45:39] G:\deeplearn\mxnet\dmlc-core\include\dmlc/logging.h:308: [17:45:39] g:\deeplearn\mxnet\src\storage\./pinned_memory_storage.h:54: Check failed: e == cudaSuccess || e == cudaErrorCudartUnloading CUDA: out of memory > [17:45:39] G:\deeplearn\mxnet\dmlc-core\include\dmlc/logging.h:308: [17:45:39] g:\deeplearn\mxnet\src\engine\./threaded_engine.h:347: [17:45:39] g:\deeplearn\mxnet\src\storage\./pinned_memory_storage.h:54: Check failed: e == cudaSuccess || e == cudaErrorCudartUnloading CUDA: out of memory > An fatal error occurred in asynchronous engine operation. If you do not know what caused this error, you can try set environment variable MXNET_ENGINE_TYPE to NaiveEngine and run with debugger (i.e. gdb). This will force all operations to be synchronous and backtrace will give you the series of calls that lead to this error. Remember to set MXNET_ENGINE_TYPE back to empty after debugging. > ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: [email protected]
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