Handle zero-sized TFLite tensor allocations

PiperOrigin-RevId: 200277562

tensorflow/contrib/lite/arena_planner_test.cc

@@ -209,11 +209,8 @@ TEST_F(ArenaPlannerTest, ZeroSizedTensors) {
   TestGraph graph({1}, {{{1}, {2}, {}}}, {2});
   (*graph.tensors())[1].bytes = 0;
   SetGraph(&graph);
-  // TODO(ahentz): this is currently broken because the arena finds two
-  // allocations with the same offset and returns an error.
-  ASSERT_FALSE(planner_->ExecuteAllocations(0, 10) == kTfLiteOk);
-  // EXPECT_EQ(GetOffset(1), 0);
-  // EXPECT_EQ(GetOffset(2), GetOffsetAfter(1));
+  ASSERT_EQ(planner_->ExecuteAllocations(0, 10), kTfLiteOk);
+  EXPECT_EQ((*graph_->tensors())[1].data.raw, nullptr);
 }
 
 TEST_F(ArenaPlannerTest, SimpleGraph) {

tensorflow/contrib/lite/interpreter_test.cc

@@ -211,7 +211,7 @@ TEST(BasicInterpreter, CheckArenaAllocation) {
   TfLiteRegistration reg = {nullptr, nullptr, nullptr, nullptr};
 
   std::vector<int> sizes{2048, 4096, 1023, 2047, 1021,
-                         2047, 1023, 2046, 1021, 2048};
+                         2047, 1023, 2046, 0,    2048};
   for (int i = 0; i < sizes.size(); ++i) {
     interpreter.SetTensorParametersReadWrite(i, kTfLiteUInt8, "", {sizes[i]},
                                              quant);
@@ -228,6 +228,7 @@ TEST(BasicInterpreter, CheckArenaAllocation) {
 
   ASSERT_EQ(interpreter.tensor(0)->data.raw, interpreter.tensor(4)->data.raw);
   ASSERT_EQ(interpreter.tensor(1)->data.raw, interpreter.tensor(7)->data.raw);
+  ASSERT_EQ(interpreter.tensor(8)->data.raw, nullptr);
 
   ASSERT_LT(interpreter.tensor(4)->data.raw, interpreter.tensor(1)->data.raw);
   ASSERT_LT(interpreter.tensor(6)->data.raw, interpreter.tensor(1)->data.raw);
@@ -314,6 +315,18 @@ TEST(BasicInterpreter, ResizingTensors) {
   EXPECT_EQ(tensor->bytes, 8 * sizeof(float));
   ASSERT_EQ(interpreter.AllocateTensors(), kTfLiteOk);
 
+  ASSERT_EQ(interpreter.ResizeInputTensor(t, {}), kTfLiteOk);
+  EXPECT_EQ(tensor->bytes, 1 * sizeof(float));
+  ASSERT_EQ(interpreter.AllocateTensors(), kTfLiteOk);
+
+  ASSERT_EQ(interpreter.ResizeInputTensor(t, {0}), kTfLiteOk);
+  EXPECT_EQ(tensor->bytes, 0);
+  ASSERT_EQ(interpreter.AllocateTensors(), kTfLiteOk);
+
+  ASSERT_EQ(interpreter.ResizeInputTensor(t, {1, 2, 0}), kTfLiteOk);
+  EXPECT_EQ(tensor->bytes, 0);
+  ASSERT_EQ(interpreter.AllocateTensors(), kTfLiteOk);
+
   // TODO(ahentz): We shouldn't have to force reallocation, but
   // ResizeInputTensor doesn't realloc dynamic tensors. Also note that
   // TfLiteTensorRealloc(tensor->bytes, tensor) is a no-op.

tensorflow/contrib/lite/simple_memory_arena.cc

@@ -36,6 +36,12 @@ TfLiteStatus SimpleMemoryArena::Allocate(TfLiteContext* context,
                                          ArenaAlloc* new_alloc) {
   TF_LITE_ENSURE(context, alignment < arena_alignment_);
 
+  if (size == 0) {
+    new_alloc->offset = 0;
+    new_alloc->size = 0;
+    return kTfLiteOk;
+  }
+
   size_t current_top = 0;
 
   if (!allocs_.empty()) {
@@ -75,6 +81,10 @@ TfLiteStatus SimpleMemoryArena::Allocate(TfLiteContext* context,
 
 TfLiteStatus SimpleMemoryArena::Deallocate(TfLiteContext* context,
                                            const ArenaAlloc& alloc) {
+  if (alloc.size == 0) {
+    return kTfLiteOk;
+  }
+
   int erased_allocs_count = 0;
   auto it = allocs_.begin();
   while (it != allocs_.end()) {
@@ -122,7 +132,11 @@ TfLiteStatus SimpleMemoryArena::ResolveAlloc(TfLiteContext* context,
                                              char** output_ptr) {
   TF_LITE_ENSURE(context, committed_);
   TF_LITE_ENSURE(context, output_ptr != nullptr);
-  *output_ptr = underlying_buffer_aligned_ptr_ + alloc.offset;
+  if (alloc.size == 0) {
+    *output_ptr = nullptr;
+  } else {
+    *output_ptr = underlying_buffer_aligned_ptr_ + alloc.offset;
+  }
   return kTfLiteOk;
 }
 

tensorflow/contrib/lite/simple_memory_arena.h

@@ -39,7 +39,8 @@ struct ArenaAlloc {
 // This small class is responsible for allocating, deallocating and reusing
 // dynamic memory from a common underlying buffer. The arena can be used in
 // scenarios when the pattern of memory allocations and deallocations is
-// repetitive, e.g. running NN inference in multiple iterations.
+// repetitive, e.g. running NN inference in multiple iterations. Note that
+// zero-sized allocations are explicitly allowed, and will resolve to null.
 class SimpleMemoryArena {
  public:
   explicit SimpleMemoryArena(size_t arena_alignment)

tensorflow/contrib/lite/simple_memory_arena_test.cc

@@ -43,6 +43,47 @@ TEST(SimpleMemoryArenaTest, BasicArenaOperations) {
   EXPECT_EQ(allocs[5].offset, 1024);
 }
 
+TEST(SimpleMemoryArenaTest, BasicZeroAlloc) {
+  TfLiteContext context;
+  SimpleMemoryArena arena(64);
+  ArenaAlloc alloc;
+
+  // Zero-sized allocs should have a 0 offset and size.
+  ASSERT_EQ(arena.Allocate(&context, 32, 0, &alloc), kTfLiteOk);
+  EXPECT_EQ(alloc.offset, 0);
+  EXPECT_EQ(alloc.size, 0);
+
+  // Deallocation of zero-sized allocs should always succeed (even redundantly).
+  ASSERT_EQ(arena.Deallocate(&context, alloc), kTfLiteOk);
+  ASSERT_EQ(arena.Deallocate(&context, alloc), kTfLiteOk);
+
+  // The zero-sized alloc should resolve to null.
+  char* resolved_ptr = nullptr;
+  ASSERT_EQ(arena.Commit(&context), kTfLiteOk);
+  ASSERT_EQ(arena.ResolveAlloc(&context, alloc, &resolved_ptr), kTfLiteOk);
+  EXPECT_EQ(resolved_ptr, nullptr);
+}
+
+TEST(SimpleMemoryArenaTest, InterleavedZeroAlloc) {
+  TfLiteContext context;
+  SimpleMemoryArena arena(64);
+  ArenaAlloc allocs[4];
+
+  // Interleave some zero and non-zero-sized allocations and deallocations.
+  ASSERT_EQ(arena.Allocate(&context, 32, 2047, &allocs[0]), kTfLiteOk);
+  ASSERT_EQ(arena.Allocate(&context, 32, 0, &allocs[1]), kTfLiteOk);
+  ASSERT_EQ(arena.Allocate(&context, 32, 1023, &allocs[2]), kTfLiteOk);
+  ASSERT_EQ(arena.Deallocate(&context, allocs[1]), kTfLiteOk);
+  ASSERT_EQ(arena.Deallocate(&context, allocs[2]), kTfLiteOk);
+  ASSERT_EQ(arena.Allocate(&context, 32, 2047, &allocs[3]), kTfLiteOk);
+
+  // Deallocation of a zero-sized alloc should not impact the allocator offsets.
+  EXPECT_EQ(allocs[0].offset, 0);
+  EXPECT_EQ(allocs[1].offset, 0);
+  EXPECT_EQ(allocs[2].offset, 2048);
+  EXPECT_EQ(allocs[3].offset, 2048);
+}
+
 TEST(SimpleMemoryArenaTest, TestAfterClear) {
   TfLiteContext context;
   SimpleMemoryArena arena(64);