Adding cpp binding and proper installation

build-scripts/install_tensorflow.sh

@@ -3,16 +3,3 @@ cd /root/src/tflite
 
 git clone https://github.com/tensorflow/tensorflow.git tensorflow_src \
     --branch v2.8.2 
-
-mkdir -p build
-cd build
-
-cmake ../tensorflow_src/tensorflow/lite 
-
-cmake --build . -j $(grep -c ^processor /proc/cpuinfo)
-
-mkdir /usr/local/lib/tflite; find . | grep -E "\.a$" | xargs cp -t /usr/local/lib/tflite
-
-cp -r flatbuffers/include/flatbuffers /usr/local/include
-
-cp -r ../tensorflow_src/tensorflow /usr/local/include

build-scripts/runtime_lib.cmake

@@ -80,6 +80,11 @@ if (WAMR_BUILD_WASI_NN EQUAL 1)
     execute_process(COMMAND ${WAMR_ROOT_DIR}/build-scripts/install_tensorflow.sh
                     RESULT_VARIABLE TENSORFLOW_RESULT
     )
+    set(TENSORFLOW_SOURCE_DIR "/root/src/tflite/tensorflow_src")
+
+    add_subdirectory(
+        "${TENSORFLOW_SOURCE_DIR}/tensorflow/lite"
+        "${CMAKE_CURRENT_BINARY_DIR}/tensorflow-lite" EXCLUDE_FROM_ALL)
     include (${IWASM_DIR}/libraries/wasi-nn/wasi_nn.cmake)
 endif ()
 

core/iwasm/libraries/wasi-nn/lib_run_inference.cpp

@@ -0,0 +1,23 @@
+#include "lib_run_inference.hpp"
+
+#include <tensorflow/lite/interpreter.h>
+#include <tensorflow/lite/kernels/register.h>
+#include <tensorflow/lite/model.h>
+#include <tensorflow/lite/optional_debug_tools.h> 
+
+std::unique_ptr<tflite::Interpreter> interpreter = NULL;
+std::unique_ptr<tflite::FlatBufferModel> model = NULL;
+
+uint32_t _load(graph_builder_array builder, graph_encoding encoding) {
+	uint32_t *size = (uint32_t*) builder[1];
+	printf("inside _load: %d\n", *size);
+	return suces;
+    // tflite::ErrorReporter *error_reporter;
+    // model = tflite::FlatBufferModel::BuildFromBuffer(
+    //     (const char *)builder[0],
+    //     1000, // TODO: find how to pass buffer size
+    //     error_reporter
+    // );
+    // tflite::ops::builtin::BuiltinOpResolver resolver;
+	// tflite::InterpreterBuilder(*model, resolver)(&interpreter);
+}

core/iwasm/libraries/wasi-nn/lib_run_inference.hpp

@@ -0,0 +1,18 @@
+#ifndef LIB_RUN_INFERENCE_HPP
+#define LIB_RUN_INFERENCE_HPP
+
+#include <stdio.h>
+
+#include "wasi_nn.h"
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+uint32_t _load(graph_builder_array builder, graph_encoding encoding);
+
+#ifdef __cplusplus
+}
+#endif
+
+#endif

core/iwasm/libraries/wasi-nn/wasi_nn.c

@@ -1,5 +1,5 @@
 #include "wasi_nn.h"
-
+#include <stdio.h>
 #include <assert.h>
 #include <errno.h>
 #include <string.h>
@@ -7,25 +7,35 @@
 
 #include "wasm_export.h"
 
-// #include <tensorflow/lite/interpreter.h>
-// #include <tensorflow/lite/kernels/register.h>
-// #include <tensorflow/lite/model.h>
-// #include <tensorflow/lite/optional_debug_tools.h> 
+#include "lib_run_inference.hpp"
 
-// std::unique_ptr<tflite::Interpreter> interpreter = NULL;
-// std::unique_ptr<tflite::FlatBufferModel> model = NULL;
+/**
+ * @brief loader of tensorflow
+ * 
+ * @param builder array of 2 pointers: first its the buffer, second its the size 
+ */
+void load_tensorflow(wasm_module_inst_t instance, graph_builder_array builder) {
+    printf("Loading tensorflow...\n");
+    for (int i = 0; i < 2; ++i)
+        builder[i] = (graph_builder) wasm_runtime_addr_app_to_native(instance, builder[i]);
+}
 
-void wasi_nn_load(wasm_exec_env_t exec_env, graph_builder_array builder, graph_encoding encoding)
+uint32_t wasi_nn_load(wasm_exec_env_t exec_env, uint32_t builder, uint32_t encoding)
 {
-    // tflite::ErrorReporter *error_reporter;
-    // model = tflite::FlatBufferModel::BuildFromBuffer(
-    //     (const char *)builder[0],
-    //     1000, // TODO: find how to pass buffer size
-    //     error_reporter
-    // );
-    // tflite::ops::builtin::BuiltinOpResolver resolver;
-	// tflite::InterpreterBuilder(*model, resolver)(&interpreter);
     printf("Inside wasi_nn_load!\n\n");
+    wasm_module_inst_t instance = wasm_runtime_get_module_inst(exec_env);
+    graph_builder_array buf = (graph_builder_array) wasm_runtime_addr_app_to_native(instance, builder);
+    load_return res;
+    switch ((graph_encoding) encoding) {
+        case openvino:
+            return invalid_argument;
+        case tensorflow:
+            load_tensorflow(instance, buf);
+            break;
+        case onnx:
+            return invalid_argument;
+    }
+    return _load(buf, (graph_encoding) encoding);
 }
 
 void wasi_nn_init_execution_context()
@@ -54,7 +64,7 @@ void wasi_nn_get_output()
 /* clang-format on */
 
 static NativeSymbol native_symbols_wasi_nn[] = {
-    REG_NATIVE_FUNC(load, "(ii)"),
+    REG_NATIVE_FUNC(load, "(ii)i"),
 };
 
 uint32_t

core/iwasm/libraries/wasi-nn/wasi_nn.cmake

@@ -2,6 +2,6 @@ set (WASI_NN_DIR ${CMAKE_CURRENT_LIST_DIR})
 
 add_definitions (-DWASM_ENABLE_WASI_NN=1)
 
-file (GLOB_RECURSE source_all ${WASI_NN_DIR}/*.c)
+file (GLOB_RECURSE source_all ${WASI_NN_DIR}/*.c ${WASI_NN_DIR}/*.cpp)
 
 set (LIBC_WASI_NN_SOURCE ${source_all})

core/iwasm/libraries/wasi-nn/wasi_nn.h

@@ -50,7 +50,7 @@ typedef enum {
     tpu
 } execution_target;
 
-void load(graph_builder_array builder, graph_encoding encoding);
+uint32_t load(graph_builder_array builder, graph_encoding encoding);
 
 void init_execution_context();
 

samples/basic/CMakeLists.txt

@@ -82,5 +82,6 @@ add_executable (basic src/main.c src/native_impl.c ${UNCOMMON_SHARED_SOURCE})
 if (APPLE)
   target_link_libraries (basic vmlib -lm -ldl -lpthread)
 else ()
-  target_link_libraries (basic vmlib -lm -ldl -lpthread -lrt)
+# TODO: add this in the vmlib. Otherwise, it will only work in the samples/basic
+  target_link_libraries (basic vmlib -lm -ldl -lpthread -lrt tensorflow-lite)
 endif ()

samples/basic/wasm-apps/testapp.c

@@ -22,7 +22,12 @@ calculate_native(int32_t n, int32_t func1, int32_t func2);
 float
 generate_float(int iteration, double seed1, float seed2)
 {
-    load(NULL, 0);
+    char *buf = strdup("test_message");
+    uint32_t *size = malloc(sizeof(uint32_t));
+    *size = 4096;
+    graph_builder_array arr[] = {(graph_builder)buf, (graph_builder)size};
+
+    load(arr, 1);
     float ret;
 
     printf("calling into WASM function: %s\n", __FUNCTION__);