mkolod edited a comment on issue #11325: Added TensorRT runtime integration
URL: https://github.com/apache/incubator-mxnet/pull/11325#issuecomment-404320678
 
 
   @reminisce Regarding your question about the cycle check, I'd like to 
juxtapose two approaches, one of which is the one taken here, and the other is 
more typical but probably less efficient for large graphs.
   
   Here's your graph (starred nodes are TensorRT-compatible, unstarred ones are 
not):
   
   ```
   A* → D
   ↓    ↓
   B* → C*
   ```
   
   **Approach 1 - greedily growing the subgraph and checking for cycles each 
time**
   
   This approach tests adding a new node while greedily growing the subgraph 
and if a cycle is formed while adding a new node, the node is rejected from the 
growing subgraph. Taking your graph as an example, say we start with A*. 
Clearly TensorRT only helps when there are 2 or more nodes, due to its benefit 
being mainly due to fusion. So, we get (A*, B*) in the set of nodes in the 
TensorRT graph. This is fine, there's no cycle, because the edge from the node 
replacing the subgraph is from B* to C*, not the other way around. So, we have 
the following:
   
   ```
       ↗    D  
   T*       ↓
       ↘    C*
   ```
   
   Now we try adding C*, to get (A*, B*, C*) in the TensorRT subgraph. Let's 
call this subgraph T*. Now D is the only node outside the subgraph and we have 
a cycle from T* to D, back to T*. This was an illegal contraction, so the last 
step is rejected, and only A* → B* gets substituted with T*. Hence, the most 
contracted legal subgraph contains the nodes T*, D and C*. This is in fact how 
TensorRT integration with TensorFlow works, or used to, the last time I checked.
   
   
   **Approach 2 - Examining sets of pairs**
   
   Instead of the greedy subgraph growth with cycle checks after each node 
addition to the subgraph, let's enumerate all pairs of nodes that are 
TensorRT-compatible or incompatible. A pair is compatible if both nodes between 
the edge are TensorRT-compatible - only then can they go into the TensorRT 
subgraph. 
   
   For the graph above, this would be A* → B* and B* → C*.
   
   A* → D is incompatible because D is incompatible, so the whole pair is 
incompatible.
   Similarly, D → C* is incompatible because D is incompatible.
   
   However, if there is a node which is part of both a compatible pair and of 
an incompatible pair, it's no longer a candidate for the TensorRT graph. The 
contradiction forces it into the incompatible class. Such a node is A*. That's 
because even though it's compatible in one pair (A* → B*), it's incompatible in 
another (A* → D). So, the only edge that can be collapsed is B* → C* and these 
two nodes become T*. Now the graph after the rewrite will look as follows:
   
   ```
   A*  →   D 
    ↘  T* ↙
   ```
   
   The graph partitioner for this PR takes Approach 2. The nice thing is that 
the pair compatibility can be determined once to test all possibilities of 
subgraph growing, instead of having to do a full search (e.g. DFS, DFS with 
graph coloring, Kahn's algorithm, whatever) every time a node is greedily added 
and substituted.
   
   Approach 2 works. We will add a unit test for this to show that it works for 
your scenario.
   
   I hope this clarifies your question as to how we handle cycles.

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