Shift memory allocation parameters to lite/util. Also make specifying these parameters explicit in runtime code.

PiperOrigin-RevId: 320416196
Change-Id: I3e321b7ca6a83a968600d64278e991a6280ebd80

tensorflow/lite/BUILD

@@ -106,6 +106,7 @@ cc_library(
         ":graph_info",
         ":memory_planner",
         ":simple_memory_arena",
+        ":util",
         "//tensorflow/lite/c:common",
     ],
 )

tensorflow/lite/arena_planner.h

@@ -23,13 +23,11 @@ limitations under the License.
 #include "tensorflow/lite/graph_info.h"
 #include "tensorflow/lite/memory_planner.h"
 #include "tensorflow/lite/simple_memory_arena.h"
+#include "tensorflow/lite/util.h"
 
 namespace tflite {
 
-// Memory allocation tuning
 constexpr const int kDefaultArenaAlignment = 64;
-constexpr const int kDefaultTensorAlignment = 64;
-
 struct AllocationInfo;
 
 // A memory planner that makes all the allocations using arenas.
@@ -53,7 +51,7 @@ class ArenaPlanner : public MemoryPlanner {
   // them until the end of inference.
   ArenaPlanner(TfLiteContext* context, std::unique_ptr<GraphInfo> graph_info,
                bool preserve_inputs, bool preserve_intermediates,
-               int tensor_alignment = kDefaultTensorAlignment);
+               int tensor_alignment);
   ~ArenaPlanner() override;
   ArenaPlanner(const ArenaPlanner&) = delete;
   ArenaPlanner& operator=(const ArenaPlanner&) = delete;

tensorflow/lite/core/subgraph.cc

@@ -859,7 +859,8 @@ TfLiteStatus Subgraph::PrepareOpsAndTensors() {
   if (!memory_planner_) {
     memory_planner_.reset(new ArenaPlanner(
         &context_, std::unique_ptr<GraphInfo>(new InterpreterInfo(this)),
-        /*preserve_inputs=*/true, /*preserve_intermediates*/ false));
+        /*preserve_inputs=*/true, /*preserve_intermediates*/ false,
+        kDefaultTensorAlignment));
     memory_planner_->PlanAllocations();
   }
 

tensorflow/lite/util.h

@@ -29,6 +29,12 @@ limitations under the License.
 
 namespace tflite {
 
+// Memory allocation parameter used by ArenaPlanner.
+// Clients (such as delegates) might look at this to ensure interop between
+// TFLite memory & hardware buffers.
+// NOTE: This only holds for tensors allocated on the arena.
+constexpr int kDefaultTensorAlignment = 64;
+
 // The prefix of Flex op custom code.
 // This will be matched agains the `custom_code` field in `OperatorCode`
 // Flatbuffer Table.