Automated rollback of commit 37123e9e82bf34002b656753970fde832c2708af
PiperOrigin-RevId: 295709352
Change-Id: I57f6223335cec07ddb701fa369be31452a72c34d
diff --git a/tensorflow/lite/micro/micro_interpreter.cc b/tensorflow/lite/micro/micro_interpreter.cc
index 31e7569..2326c2d 100644
--- a/tensorflow/lite/micro/micro_interpreter.cc
+++ b/tensorflow/lite/micro/micro_interpreter.cc
@@ -52,8 +52,7 @@
error_reporter_(error_reporter),
allocator_(&context_, model_, tensor_arena, tensor_arena_size,
error_reporter_),
- tensors_allocated_(false),
- tensors_prepared_(false) {
+ tensors_allocated_(false) {
const flatbuffers::Vector<flatbuffers::Offset<SubGraph>>* subgraphs =
model->subgraphs();
if (subgraphs->size() != 1) {
@@ -86,6 +85,21 @@
initialization_status_ = kTfLiteOk;
}
+MicroInterpreter::~MicroInterpreter() {
+ if (node_and_registrations_ != nullptr) {
+ for (size_t i = 0; i < operators_->size(); ++i) {
+ TfLiteNode* node = &(node_and_registrations_[i].node);
+ const TfLiteRegistration* registration =
+ node_and_registrations_[i].registration;
+ // registration is allocated outside the interpreter, so double check to
+ // make sure it's not nullptr;
+ if (registration != nullptr && registration->free != nullptr) {
+ registration->free(&context_, node->user_data);
+ }
+ }
+ }
+}
+
void MicroInterpreter::CorrectTensorEndianness(TfLiteTensor* tensorCorr) {
int32_t tensorSize = 1;
for (int d = 0; d < tensorCorr->dims->size; ++d)
@@ -128,8 +142,41 @@
op_resolver_, &node_and_registrations_));
TF_LITE_ENSURE_OK(&context_, allocator_.FinishTensorAllocation());
- tensors_allocated_ = true;
- return kTfLiteOk;
+ // Init method is not yet implemented.
+ for (size_t i = 0; i < operators_->size(); ++i) {
+ auto* node = &(node_and_registrations_[i].node);
+ auto* registration = node_and_registrations_[i].registration;
+ size_t init_data_size;
+ const char* init_data;
+ if (registration->builtin_code == BuiltinOperator_CUSTOM) {
+ init_data = reinterpret_cast<const char*>(node->custom_initial_data);
+ init_data_size = node->custom_initial_data_size;
+ } else {
+ init_data = reinterpret_cast<const char*>(node->builtin_data);
+ init_data_size = 0;
+ }
+ if (registration->init) {
+ node->user_data =
+ registration->init(&context_, init_data, init_data_size);
+ }
+ }
+
+ for (size_t i = 0; i < operators_->size(); ++i) {
+ auto* node = &(node_and_registrations_[i].node);
+ auto* registration = node_and_registrations_[i].registration;
+ if (registration->prepare) {
+ TfLiteStatus prepare_status = registration->prepare(&context_, node);
+ if (prepare_status != kTfLiteOk) {
+ error_reporter_->Report(
+ "Node %s (number %d) failed to prepare with status %d",
+ OpNameFromRegistration(registration), i, prepare_status);
+ return kTfLiteError;
+ }
+ }
+ }
+
+ tensors_allocated_ = true;
+ return kTfLiteOk;
}
TfLiteStatus MicroInterpreter::Invoke() {
@@ -144,45 +191,6 @@
AllocateTensors();
}
- // Init method is not yet implemented.
- for (size_t i = 0; i < operators_->size(); ++i) {
- auto* node = &(node_and_registrations_[i].node);
- auto* registration = node_and_registrations_[i].registration;
- size_t init_data_size;
- const char* init_data;
- if (registration->builtin_code == BuiltinOperator_CUSTOM) {
- init_data = reinterpret_cast<const char*>(node->custom_initial_data);
- init_data_size = node->custom_initial_data_size;
- } else {
- init_data = reinterpret_cast<const char*>(node->builtin_data);
- init_data_size = 0;
- }
- if (!tensors_prepared_ && registration->init) {
- node->user_data =
- registration->init(&context_, init_data, init_data_size);
- }
- }
-
- if (!tensors_prepared_) {
- for (size_t i = 0; i < operators_->size(); ++i) {
- auto* node = &(node_and_registrations_[i].node);
- auto* registration = node_and_registrations_[i].registration;
- if (registration->prepare) {
- TfLiteStatus prepare_status = registration->prepare(&context_, node);
- if (prepare_status != kTfLiteOk) {
- error_reporter_->Report(
- "Node %s (number %d) failed to prepare with status %d",
- OpNameFromRegistration(registration), i, prepare_status);
- return kTfLiteError;
- }
- }
- }
-#ifdef TF_LITE_MICRO_TENSORS_PREPARED
- // TODO(b/148085107): Turn this value on by default.
- tensors_prepared_ = true;
-#endif
- }
-
for (size_t i = 0; i < operators_->size(); ++i) {
auto* node = &(node_and_registrations_[i].node);
auto* registration = node_and_registrations_[i].registration;
@@ -197,16 +205,6 @@
}
}
}
-
- // This is actually a no-op.
- // TODO(wangtz): Consider removing this code to slightly reduce binary size.
- for (size_t i = 0; i < operators_->size(); ++i) {
- auto* node = &(node_and_registrations_[i].node);
- auto* registration = node_and_registrations_[i].registration;
- if (registration->free) {
- registration->free(&context_, node->user_data);
- }
- }
return kTfLiteOk;
}
diff --git a/tensorflow/lite/micro/micro_interpreter.h b/tensorflow/lite/micro/micro_interpreter.h
index 941960a..4d02769 100644
--- a/tensorflow/lite/micro/micro_interpreter.h
+++ b/tensorflow/lite/micro/micro_interpreter.h
@@ -39,6 +39,8 @@
uint8_t* tensor_arena, size_t tensor_arena_size,
ErrorReporter* error_reporter);
+ ~MicroInterpreter();
+
// Runs through the model and allocates all necessary input, output and
// intermediate tensors.
TfLiteStatus AllocateTensors();
@@ -109,7 +111,7 @@
template <class T>
void CorrectTensorDataEndianness(T* data, int32_t size);
- NodeAndRegistration* node_and_registrations_;
+ NodeAndRegistration* node_and_registrations_ = nullptr;
const Model* model_;
const OpResolver& op_resolver_;
@@ -117,7 +119,6 @@
TfLiteContext context_ = {};
MicroAllocator allocator_;
bool tensors_allocated_;
- bool tensors_prepared_;
TfLiteStatus initialization_status_;
const flatbuffers::Vector<flatbuffers::Offset<Tensor>>* tensors_;
diff --git a/tensorflow/lite/micro/micro_interpreter_test.cc b/tensorflow/lite/micro/micro_interpreter_test.cc
index 6d0deca..5ca2c3a 100644
--- a/tensorflow/lite/micro/micro_interpreter_test.cc
+++ b/tensorflow/lite/micro/micro_interpreter_test.cc
@@ -22,6 +22,7 @@
namespace tflite {
namespace {
+
void* MockInit(TfLiteContext* context, const char* buffer, size_t length) {
// We don't support delegate in TFL micro. This is a weak check to test if
// context struct being zero-initialized.
@@ -31,9 +32,8 @@
return nullptr;
}
-void MockFree(TfLiteContext* context, void* buffer) {
- // Do nothing.
-}
+bool freed = false;
+void MockFree(TfLiteContext* context, void* buffer) { freed = true; }
TfLiteStatus MockPrepare(TfLiteContext* context, TfLiteNode* node) {
return kTfLiteOk;
@@ -75,49 +75,56 @@
TF_LITE_MICRO_TESTS_BEGIN
TF_LITE_MICRO_TEST(TestInterpreter) {
+ tflite::freed = false;
const tflite::Model* model = tflite::testing::GetSimpleMockModel();
TF_LITE_MICRO_EXPECT_NE(nullptr, model);
tflite::MockOpResolver mock_resolver;
constexpr size_t allocator_buffer_size = 1024;
uint8_t allocator_buffer[allocator_buffer_size];
- tflite::MicroInterpreter interpreter(model, mock_resolver, allocator_buffer,
- allocator_buffer_size,
- micro_test::reporter);
- TF_LITE_MICRO_EXPECT_EQ(interpreter.AllocateTensors(), kTfLiteOk);
- TF_LITE_MICRO_EXPECT_EQ(1, interpreter.inputs_size());
- TF_LITE_MICRO_EXPECT_EQ(2, interpreter.outputs_size());
- TfLiteTensor* input = interpreter.input(0);
- TF_LITE_MICRO_EXPECT_NE(nullptr, input);
- TF_LITE_MICRO_EXPECT_EQ(kTfLiteInt32, input->type);
- TF_LITE_MICRO_EXPECT_EQ(1, input->dims->size);
- TF_LITE_MICRO_EXPECT_EQ(1, input->dims->data[0]);
- TF_LITE_MICRO_EXPECT_EQ(4, input->bytes);
- TF_LITE_MICRO_EXPECT_NE(nullptr, input->data.i32);
- input->data.i32[0] = 21;
+ // Create a new scope so that we can test the destructor.
+ {
+ tflite::MicroInterpreter interpreter(model, mock_resolver, allocator_buffer,
+ allocator_buffer_size,
+ micro_test::reporter);
+ TF_LITE_MICRO_EXPECT_EQ(interpreter.AllocateTensors(), kTfLiteOk);
+ TF_LITE_MICRO_EXPECT_EQ(1, interpreter.inputs_size());
+ TF_LITE_MICRO_EXPECT_EQ(2, interpreter.outputs_size());
- TF_LITE_MICRO_EXPECT_EQ(kTfLiteOk, interpreter.Invoke());
+ TfLiteTensor* input = interpreter.input(0);
+ TF_LITE_MICRO_EXPECT_NE(nullptr, input);
+ TF_LITE_MICRO_EXPECT_EQ(kTfLiteInt32, input->type);
+ TF_LITE_MICRO_EXPECT_EQ(1, input->dims->size);
+ TF_LITE_MICRO_EXPECT_EQ(1, input->dims->data[0]);
+ TF_LITE_MICRO_EXPECT_EQ(4, input->bytes);
+ TF_LITE_MICRO_EXPECT_NE(nullptr, input->data.i32);
+ input->data.i32[0] = 21;
- TfLiteTensor* output = interpreter.output(0);
- TF_LITE_MICRO_EXPECT_NE(nullptr, output);
- TF_LITE_MICRO_EXPECT_EQ(kTfLiteInt32, output->type);
- TF_LITE_MICRO_EXPECT_EQ(1, output->dims->size);
- TF_LITE_MICRO_EXPECT_EQ(1, output->dims->data[0]);
- TF_LITE_MICRO_EXPECT_EQ(4, output->bytes);
- TF_LITE_MICRO_EXPECT_NE(nullptr, output->data.i32);
- TF_LITE_MICRO_EXPECT_EQ(42, output->data.i32[0]);
+ TF_LITE_MICRO_EXPECT_EQ(kTfLiteOk, interpreter.Invoke());
- output = interpreter.output(1);
- TF_LITE_MICRO_EXPECT_NE(nullptr, output);
- TF_LITE_MICRO_EXPECT_EQ(kTfLiteInt32, output->type);
- TF_LITE_MICRO_EXPECT_EQ(1, output->dims->size);
- TF_LITE_MICRO_EXPECT_EQ(1, output->dims->data[0]);
- TF_LITE_MICRO_EXPECT_EQ(4, output->bytes);
- TF_LITE_MICRO_EXPECT_NE(nullptr, output->data.i32);
- TF_LITE_MICRO_EXPECT_EQ(42, output->data.i32[0]);
+ TfLiteTensor* output = interpreter.output(0);
+ TF_LITE_MICRO_EXPECT_NE(nullptr, output);
+ TF_LITE_MICRO_EXPECT_EQ(kTfLiteInt32, output->type);
+ TF_LITE_MICRO_EXPECT_EQ(1, output->dims->size);
+ TF_LITE_MICRO_EXPECT_EQ(1, output->dims->data[0]);
+ TF_LITE_MICRO_EXPECT_EQ(4, output->bytes);
+ TF_LITE_MICRO_EXPECT_NE(nullptr, output->data.i32);
+ TF_LITE_MICRO_EXPECT_EQ(42, output->data.i32[0]);
- // Just to make sure that this method works.
- tflite::PrintInterpreterState(&interpreter);
+ output = interpreter.output(1);
+ TF_LITE_MICRO_EXPECT_NE(nullptr, output);
+ TF_LITE_MICRO_EXPECT_EQ(kTfLiteInt32, output->type);
+ TF_LITE_MICRO_EXPECT_EQ(1, output->dims->size);
+ TF_LITE_MICRO_EXPECT_EQ(1, output->dims->data[0]);
+ TF_LITE_MICRO_EXPECT_EQ(4, output->bytes);
+ TF_LITE_MICRO_EXPECT_NE(nullptr, output->data.i32);
+ TF_LITE_MICRO_EXPECT_EQ(42, output->data.i32[0]);
+
+ // Just to make sure that this method works.
+ tflite::PrintInterpreterState(&interpreter);
+ }
+
+ TF_LITE_MICRO_EXPECT_EQ(tflite::freed, true);
}
TF_LITE_MICRO_TEST(TestVariableTensorReset) {
