Optimize KahnsTopologicalSort and PriorityNodeCompare (#19475)
**Description**
1) During SessionInitialization, KahnsTopologicalSort is a major cause
of perf degradation.
The main cause of slow down is that the TopologicalSort needs to keep
track of nodes to visit in order, and reorder them based on priority (as
informed by a comparator). The existing implementation uses a
priority_queue that is backed by a std::vector container. However,
vectors are not good for insertion and reordering. The appropriate data
type for this operation is a linked list. However, linked lists like
std::list are not usable as a container for std::priority_queue. This is
because std::priority_queue requires random access, which linked lists
do not have. However, for this simple implementation, we can leverage a
std::list under the hood and perform insertions manually using
std::upper_bound. This drastically reduces the time taken by the method,
which currently instead causes numerous recopies and a lot of movement
inside the graph nodes to visit list.
2) In the comparator, I hide forward and backward attribute checking
behind the #ifdef ENABLE_TRAINING macro, as I believe it should only be
valid in the training scenario.
3) In noopelimination transformer, I prevent the creation of Initializer
(which unpacks tensorproto data) in every node and only create
initializers when Add/Sub/Mul/Div op nodes are detected.
**Motivation and Context**
Session creation time of many models is quite slow.
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Co-authored-by: Sheil Kumar <sheilk@microsoft.com>
onnxruntime
34c36238 - Optimize KahnsTopologicalSort and PriorityNodeCompare (#19475)
