THIS IS A TEST INSTANCE. ALL YOUR CHANGES WILL BE LOST!!!!
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https://jira.apache.org/jira/browse/MXNET-1085
Conditional Checkout and Compilation of Dependencies
TensorRT integration required us to add a number of third party code sub-repositories to the project. This is not ideal for users who would like to checkout and build MXNet without using the TensorRT feature. In the future we should migrate the feature to be CMake only, and checkout the project at pre-compilation time to avoid forcing all users to checkout these subrepos. We can also model these dependencies using CMake such that they're automatically built and linked against when required, which would make building from scratch easier for those that do want to use TensorRT integration.
Increased Operator (/Layer) Coverage
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Currently supported operators:
| Operator Name | Operator Description | Status |
|---|---|---|
| Convolution | Complete | |
| BatchNorm | Complete | |
elemwise_add | Complete | |
| elemwise_sub | Complete | |
| elemwise_mul | Complete | |
| rsqrt | Complete | |
| Pad | Complete | |
| mean | Complete | |
| FullyConnected | Complete | |
| Flatten | Complete | |
| SoftmaxOutput | Complete | |
| Activation | relu, tanh, sigmoid | Complete |
Operators to be added:
| Operator Name | Operator Description | Status |
|---|---|---|
| Deconvolution Op | Required for several Computer Vision models. | In Progress |
| elemwise_div | Required for some Wavenet implementations. | In Progress |
Benchmarks
TensorRT is still an experimental feature, so benchmarks are likely to improve over time. As of Oct 11, 2018 we've measured the following improvements which have all been run with FP32 weighted networks.
| Model Name | Relative TensorRT Speedup | Hardware |
|---|---|---|
cifar_resnet20_v2 | 1.21x | Titan V |
cifar_resnext29_16x64d | 1.26x | Titan V |
| Resnet 18 | 1.8x | Titan V |
| Resnet 18 | 1.54x | Jetson TX1 |
Related articles
https://mxnet.incubator.apache.org/tutorials/tensorrt/inference_with_trt.html
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