mxnet-memonger
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dmlc
Sublinear memory optimization for deep learning, reduce GPU memory cost to train deeper nets
is memonger installed by default with mxnet ? i can't import ``` >>> import mxnet >>> import memonger Traceback (most recent call last): File "", line 1, in ImportError: No...
I used it on DDP ,and an error came out, I dont know if it can be used on DDP. Error maybe occurred in loss.backward(). Thank you ! RuntimeError: Expected...
## Description I want to reduce gpu memory costing when using gluon, I tryed MXNet memonger but it did not work for me, After that I setting os.environ['MXNET_BACKWARD_DO_MIRROR'] = '1',...
When I use the memonger, and I use the function of load_checkpoint(), but in this line assert sys.tojson() == network.tojson() is failed. This means that the structure of the network...
**# my example_googlenet.py as follows:** """References: Szegedy, Christian, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich. "Going deeper with convolutions." arXiv...
I do not dare to question your code and experiment design. Is this a 152 layer Resnet? With 1+3*(3+8+36+3)+1 =152 layer.
