wkcn opened a new issue #13928: MXNet 1.5.0 is slower than 1.3.0 when intputs are variant URL: https://github.com/apache/incubator-mxnet/issues/13928 ## Description Hi! I have an experiment about Object Counting, which needs variant inputs. I write the code with Gluon, and hybridize the model with `static_alloc=True` I found there is obvious difference between MXNet 1.5.0 and MXNet 1.3.0, and I checked it on two servers. GPU: Tesla M40 x 4 - Performance: MXNet 1.5.0: 20 images / sec MXNet 1.3.0: 70+ images / sec ## Environment info (Required) OS: ubuntu 14.04 Package used (Python/R/Scala/Julia): Python 2.7.12, 3.7.1 MXNet is installed by pip: ``` # MXNet 1.5.0 pip install mxnet-cu80 --pre # MXNet 1.3.0 pip install mxnet-cu80==1.3.0 ``` ## Error Message: (Paste the complete error message, including stack trace.) ## Minimum reproducible example Faster R-CNN in GluonCV may be a reproducible example, which need variant input. [Faster R-CNN in GluonCV](https://github.com/dmlc/gluon-cv/blob/master/scripts/detection/faster_rcnn/train_faster_rcnn.py) ## Steps to reproduce (Paste the commands you ran that produced the error.) 1. 2. ## What have you tried to solve it? 1. 2.
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