Disable profiling when getGraphExecutorOptimize is unset (pytorch#46479)

Summary:
`getGraphExecutorOptimize` mandates we don't do any optimizations beyond what's required to run graphs. In this scenario, we don't want to do any profiling as profiling information will not be used.

Pull Request resolved: pytorch#46479

Reviewed By: ZolotukhinM

Differential Revision: D24368292

Pulled By: Krovatkin

fbshipit-source-id: a2c7618d459efca9cb0700c4d64d829b352792a8

Author: Krovatkin

torch/csrc/jit/runtime/profiling_graph_executor_impl.cpp

@@ -452,6 +452,21 @@ ExecutionPlan ProfilingGraphExecutorImpl::getPlanFor(
   std::lock_guard<std::mutex> lock(compile_mutex);
   GRAPH_DEBUG("Running ProfilingGraphExecutorImpl ", this);
 
+  // no opt mode
+  if (!getGraphExecutorOptimize()) {
+    if (!fallback_plan_) {
+      auto copy = graph->copy();
+      GRAPH_DEBUG(
+          "Before LowerGradOf (beginning of runNooptPassPipeline)\n", *graph);
+      LowerGradOf(*copy);
+      GRAPH_DEBUG("After LowerGradOf, before RemoveExpands\n", *graph);
+      RemoveExpands(copy);
+      fallback_plan_ = ExecutionPlan(copy, function_name_);
+      GRAPH_DUMP("NoOpt Graph: ", copy);
+    }
+    return *fallback_plan_;
+  }
+
   // if tensorExprFuserEnabled() returns true we need to persist the very first
   // time ProfilingGraphExecutorImpl is called, so we can update it correctly
   // for fallback functions in ProfilingGraphExecutorImpl Else,

torch/csrc/jit/runtime/profiling_graph_executor_impl.h

@@ -22,6 +22,8 @@ struct ProfilingGraphExecutorImpl : public GraphExecutorImplBase {
   c10::optional<ExecutionPlan>
       profiling_plan_; // plan to run in order to profiling the code
   c10::optional<ExecutionPlan> optimized_plan_;
+  // this plan is used if getGraphExecutorOptimize is unset
+  c10::optional<ExecutionPlan> fallback_plan_;
   // fallback functions are inserted for tensorexpr fusion groups
   // and by specialize_autogradzero. Whenever, at runtime, input
   // tensor don't match profiled properties, fallback functions are called