However, memory pattern optimization will allocate memory from the second run - If memory pattern optimization will always allocate memory on the second run, how come this doesn't repro universally for all models (Seem to recall we had a C++ test for a simple model and this issue never happens there)? Is it possible, that while memory pattern optimization kicks in always (based on the session option), it only triggers an arena extension for some models based on the peak memory usage identified by the planner in the first run and the arena's state at that point in time ?

However, memory pattern optimization will allocate memory from the second run - If memory pattern optimization will always allocate memory on the second run, how come this doesn't repro universally for all models (Seem to recall we had a C++ test for a simple model and this issue never happens there)? Is it possible, that while memory pattern optimization kicks in based on the session option, it only triggers an arena extension for some models based on the peak memory usage identified by the planner in the first run and the arena's state at that point in time ?

I think the default Arena setting make it. Let me change the Arena setting in the test case, and it shall be able to reproduce.

However, memory pattern optimization will allocate memory from the second run - If memory pattern optimization will always allocate memory on the second run, how come this doesn't repro universally for all models (Seem to recall we had a C++ test for a simple model and this issue never happens there)? Is it possible, that while memory pattern optimization kicks in always (based on the session option), it only triggers an arena extension for some models based on the peak memory usage identified by the planner in the first run and the arena's state at that point in time ?

It is due to Arena setting of 1M default initial buffer bytes and the NextPowerOfTwo extend strategy could have extra memory covering small memory allocation. I updated the Arena setting to use SameAsRequest, also use large batch size so that 1M is not enough. Now the new test can reproduce the bug.

However, memory pattern optimization will allocate memory from the second run - If memory pattern optimization will always allocate memory on the second run, how come this doesn't repro universally for all models (Seem to recall we had a C++ test for a simple model and this issue never happens there)? Is it possible, that while memory pattern optimization kicks in always (based on the session option), it only triggers an arena extension for some models based on the peak memory usage identified by the planner in the first run and the arena's state at that point in time ?

It is due to Arena setting of 1M default initial buffer bytes and the NextPowerOfTwo extend strategy could have extra memory covering small memory allocation. I updated the Arena setting to use SameAsRequest, also use large batch size so that 1M is not enough. Now the new test can reproduce the bug.

Thanks for catching this.