Kernel Util component file list

tensorflow-build/add/templates/tflite_main.cpp

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+#include "tensorflow/lite/micro/micro_mutable_op_resolver.h"
+#include "tensorflow/lite/micro/tflite_bridge/micro_error_reporter.h"
+#include "tensorflow/lite/micro/micro_interpreter.h"
+#include "tensorflow/lite/schema/schema_generated.h"
+
+// Include your model data. Replace this with the header file for your model.
+#include "model.h"
+
+// Define the number of elements in the input tensor
+#define INPUT_SIZE 300*300
+
+using MyOpResolver = tflite::MicroMutableOpResolver<10>;
+
+// Replace this with your model's input and output tensor sizes
+const int tensor_arena_size = 2 * 1024;
+uint8_t tensor_arena[tensor_arena_size] __align(16);
+
+void RunModel(int8_t* input_data) {
+    tflite::MicroErrorReporter micro_error_reporter;
+    tflite::ErrorReporter* error_reporter = &micro_error_reporter;
+
+    const tflite::Model* model = ::tflite::GetModel(g_model);
+
+    MyOpResolver op_resolver;
+    // Register your model's operations here
+
+    tflite::MicroInterpreter interpreter(model, op_resolver, tensor_arena,
+                                         tensor_arena_size, error_reporter);
+
+    interpreter.AllocateTensors();
+
+    TfLiteTensor* input = interpreter.input(0);
+    // Add checks for input tensor properties here if needed
+
+    // Copy image data to model's input tensor
+    for (int i = 0; i < INPUT_SIZE; ++i) {
+        input->data.int8[i] = input_data[i];
+    }
+
+    TfLiteStatus invoke_status = interpreter.Invoke();
+    // Add checks for successful inference here if needed
+
+    TfLiteTensor* output = interpreter.output(0);
+    // Add checks for output tensor properties here if needed
+
+    // Process your output value here
+    // For example, SSD models typically produce an array of bounding boxes
+}

tensorflow-build/kernelutil.lst

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+tensorflow/lite/micro/recording_micro_allocator.cpp