Merge branch 'ci/sync_gh_tflite-micro' into 'master'

Sync esp-tflite-micro from github - 744684

See merge request app-frameworks/esp-tflite-micro!150

Author: vikramdattu

CMakeLists.txt

@@ -4,6 +4,7 @@ cmake_minimum_required(VERSION 3.5)
 
 set(tflite_dir "${CMAKE_CURRENT_SOURCE_DIR}/tensorflow/lite")
 set(signal_dir "${CMAKE_CURRENT_SOURCE_DIR}/signal")
+set(compiler_mlir_dir "${CMAKE_CURRENT_SOURCE_DIR}/tensorflow/compiler/mlir/")
 set(tfmicro_dir "${tflite_dir}/micro")
 set(tfmicro_frontend_dir "${tflite_dir}/experimental/microfrontend/lib")
 set(tfmicro_kernels_dir "${tfmicro_dir}/kernels")
@@ -77,7 +78,7 @@ set(lib_srcs
           "${tflite_dir}/kernels/internal/tensor_ctypes.cc"
           "${tflite_dir}/kernels/internal/reference/portable_tensor_utils.cc"
           "${tflite_dir}/kernels/internal/reference/comparisons.cc"
-          "${tflite_dir}/schema/schema_utils.cc")
+          "${compiler_mlir_dir}/lite/schema/schema_utils.cc")
 
 set(priv_req)
 

tensorflow/compiler/mlir/lite/kernels/internal/compatibility_macros.h

@@ -0,0 +1,21 @@
+/* Copyright 2024 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#ifndef TENSORFLOW_COMPILER_MLIR_LITE_KERNELS_INTERNAL_COMPATABILITY_MACROS_H_
+#define TENSORFLOW_COMPILER_MLIR_LITE_KERNELS_INTERNAL_COMPATABILITY_MACROS_H_
+
+#include "tensorflow/lite/kernels/internal/compatibility.h"  // IWYU pragma: keep
+
+#endif  // TENSORFLOW_COMPILER_MLIR_LITE_KERNELS_INTERNAL_COMPATABILITY_MACROS_H_

tensorflow/compiler/mlir/lite/schema/schema_generated.h

@@ -0,0 +1,22 @@
+/* Copyright 2024 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_COMPILER_MLIR_LITE_SCHEMA_SCHEMA_GENERATED_H_
+#define TENSORFLOW_COMPILER_MLIR_LITE_SCHEMA_SCHEMA_GENERATED_H_
+
+// This file should only be used by the make build to redirect schema_utils.cc
+// usage of the generated schema to the proper location.
+#include "tensorflow/lite/schema/schema_generated.h"  // IWYU pragma: keep
+
+#endif  // TENSORFLOW_LITE_SCHEMA_SCHEMA_UTILS_H_

tensorflow/lite/schema/schema_utils.cc renamed to tensorflow/compiler/mlir/lite/schema/schema_utils.cc

@@ -12,11 +12,11 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 See the License for the specific language governing permissions and
 limitations under the License.
 ==============================================================================*/
-#include "tensorflow/lite/schema/schema_utils.h"
+#include "tensorflow/compiler/mlir/lite/schema/schema_utils.h"
 
 #include <algorithm>
 
-#include "tensorflow/lite/kernels/internal/compatibility.h"
+#include "tensorflow/compiler/mlir/lite/kernels/internal/compatibility_macros.h"
 
 namespace tflite {
 

tensorflow/compiler/mlir/lite/schema/schema_utils.h

@@ -0,0 +1,33 @@
+/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_COMPILER_MLIR_LITE_SCHEMA_SCHEMA_UTILS_H_
+#define TENSORFLOW_COMPILER_MLIR_LITE_SCHEMA_SCHEMA_UTILS_H_
+
+#include "flatbuffers/flatbuffers.h"
+#include "tensorflow/compiler/mlir/lite/schema/schema_generated.h"
+
+namespace tflite {
+
+// The following methods are introduced to resolve op builtin code shortage
+// problem. The new builtin operator will be assigned to the extended builtin
+// code field in the flatbuffer schema. Those methods helps to hide builtin code
+// details.
+BuiltinOperator GetBuiltinCode(const OperatorCode *op_code);
+
+BuiltinOperator GetBuiltinCode(const OperatorCodeT *op_code);
+
+}  // namespace tflite
+
+#endif  // TENSORFLOW_COMPILER_MLIR_LITE_SCHEMA_SCHEMA_UTILS_H_

tensorflow/lite/core/macros.h

@@ -65,16 +65,4 @@ limitations under the License.
 #define TFLITE_HAS_ATTRIBUTE_WEAK 0
 #endif
 
-#ifndef TF_LITE_STATIC_MEMORY
-// maximum size of a valid flatbuffer
-inline constexpr unsigned int flatbuffer_size_max = 2147483648;
-// If none zero then the buffer is stored outside of the flatbuffers, string
-inline constexpr char tflite_metadata_buffer_location[] = "buffer_location";
-// field for minimum runtime version, string
-inline constexpr char tflite_metadata_min_runtime_version[] =
-    "min_runtime_version";
-// the stablehlo op version is supported by the tflite runtime
-inline constexpr char tflite_supported_stablehlo_version[] = "1.0.0";
-#endif
-
 #endif  // TENSORFLOW_LITE_CORE_MACROS_H_

tensorflow/lite/kernels/internal/portable_tensor_utils.cc

@@ -70,6 +70,12 @@ void ApplySignbitToVector(const float* __restrict__ vector, int v_size,
 
 void UnpackDenseInt4IntoInt8(const int8_t* src_buffer, int num_elements,
                              int8_t* dst_buffer) {
+  // num_elements means the number of elements regardless of packed or unpacked.
+  // For example, 3 elements means both
+  //   1) Packed: 3 int4's = 12 bit -> 16 bits (padded) = 2 bytes.
+  //      stored in src_buffer[0] and src_buffer[1] (i = 0..1)
+  //   2) Unpacked: 3 int8's = 3 bytes.
+  //.     stored in dst_buffer[0], dst_buffer[1] and dst_buffer[2] (j = 0..2)
   for (int i = 0; i < num_elements / 2; i++) {
     int8_t byte = src_buffer[i];
     // Shift left first so that sign is properly extended when shifted right

tensorflow/lite/micro/micro_allocation_info.h

@@ -129,7 +129,8 @@ class AllocationInfoBuilder {
 
   const tflite::Model* model_ = nullptr;
   INonPersistentBufferAllocator* non_persistent_allocator_ = nullptr;
-  GraphAllocationInfo info_;
+  GraphAllocationInfo info_ =
+      {};  // Prevents problems caused by accessing uninitialized memory.
   int allocation_scope_count_ = 0;
 };
 

tensorflow/lite/micro/micro_allocator.h

@@ -322,7 +322,9 @@ class MicroAllocator {
   IPersistentBufferAllocator* persistent_buffer_allocator_;
 
   // Allocator used to allocate persistent builtin data.
-  TfLiteBridgeBuiltinDataAllocator* builtin_data_allocator_;
+  TfLiteBridgeBuiltinDataAllocator* builtin_data_allocator_ =
+      nullptr;  // Initialized as nullptr to prevent any possible issues related
+                // to accessing uninitialized memory.
 
   // Activation buffer memory planner.
   MicroMemoryPlanner* memory_planner_;

tensorflow/lite/micro/micro_interpreter_graph.h

@@ -106,7 +106,9 @@ class MicroInterpreterGraph : public MicroGraph {
   int current_subgraph_index_;
   uint32_t current_operator_index_;
   MicroResourceVariables* resource_variables_;
-  const flatbuffers::Vector<flatbuffers::Offset<SubGraph>>* subgraphs_;
+  const flatbuffers::Vector<flatbuffers::Offset<SubGraph>>* subgraphs_ =
+      nullptr;  // Initialized as nullptr to prevent any possible issues
+                // related to accessing uninitialized memory.
 
   TF_LITE_REMOVE_VIRTUAL_DELETE
 };