KellenSunderland commented on a change in pull request #14860: Update TRT 
tutorial with new APIs
URL: https://github.com/apache/incubator-mxnet/pull/14860#discussion_r319642470
 
 

 ##########
 File path: docs/tutorials/tensorrt/inference_with_trt.md
 ##########
 @@ -118,7 +108,7 @@ for i in range(0, 10000):
 end = time.time()
 print(time.process_time() - start)
 ```
-We run timing with a warmup once more, and on the same machine, run in 
**18.99s**. A 1.8x speed improvement!  Speed improvements when using libraries 
like TensorRT can come from a variety of optimizations, but in this case our 
speedups are coming from a technique known as [operator 
fusion](http://dmlc.ml/2016/11/21/fusion-and-runtime-compilation-for-nnvm-and-tinyflow.html).
+We run timing with a warmup once more, and on the same machine, run in 
**9.83s**. A 1.75x speed improvement!  Speed improvements when using libraries 
like TensorRT can come from a variety of optimizations, but in this case our 
speedups are coming from a technique known as [operator 
fusion](http://dmlc.ml/2016/11/21/fusion-and-runtime-compilation-for-nnvm-and-tinyflow.html).
 
 Review comment:
   Darn, that was a good guide.  Will update.

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