[GitHub] larroy commented on a change in pull request #12007: Add tutorial Gotchas using NumPy

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larroy commented on a change in pull request #12007: Add tutorial Gotchas using NumPy
URL: https://github.com/apache/incubator-mxnet/pull/12007#discussion_r207382189
 
 

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 File path: docs/tutorials/gluon/gotchas_numpy_in_mxnet.md
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+# Gotchas using NumPy in Apache MXNet
+
+The goal of this tutorial is to explain some common misconceptions about using [NumPy](http://www.numpy.org/) arrays in Apache MXNet. We are going to explain why you need to minimize or completely remove usage of NumPy from your Apache MXNet code. We also going to show how to minimize NumPy performance impact, when you have to use NumPy.
+
+## Asynchronous and non-blocking nature of Apache MXNet
+
+Instead of using NumPy arrays Apache MXNet offers its own array implementation named [NDArray](https://mxnet.incubator.apache.org/api/python/ndarray/ndarray.html). `NDArray API` was intentionally designed to be similar to `NumPy`, but there are differences.
+
+One key difference is in the way calculations are executed. Every `NDArray` manipulation in Apache MXNet is done in asynchronous, non-blocking way. That means, that when we write code like `c = a * b`, where both `a` and `b` are `NDArrays`, the function got pushed to the [Execution Engine](https://mxnet.incubator.apache.org/architecture/overview.html#execution-engine), which starts the calculation. The function immediately returns back, and the  user thread can continue execution, despite the fact that the calculation may not have been completed yet. 
+
+`Execution Engine` builds computation graph which may reorder or combine some calculations, but it honors dependency order: if there are other manipulation with `c` done later in the code, the `Execution Engine` will start doing them once the result of `c` is available. We don't need to write callbacks to start execution of subsequent code - the `Execution Engine` is going to do it for us. 
 
 Review comment:
   builds *the* 

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