more updates for pip package

.gitignore

@@ -6,4 +6,5 @@
 rpi-toolchain.tar.gz
 /build
 /.venv
-__pycache__
+__pycache__
+*.whl

README.md

@@ -1,45 +1,50 @@
-<!--ts-->
-   * [TensorFlow Lite for Microcontrollers](#tensorflow-lite-for-microcontrollers)
-   * [Build Status](#build-status)
-      * [Official Builds](#official-builds)
-      * [Community Supported Builds](#community-supported-builds)
-   * [Additional Documentation](#additional-documentation)
+tflite_micro_runtime
+========================
 
-<!-- Added by: advaitjain, at: Thu 29 Apr 2021 12:53:08 PM PDT -->
+This allows for running TF-Lite models on a RaspberryPi Zero using the Tensorflow-Lite Micro (TFLM) interpreter.  
 
-<!--te-->
+This provides the Python package:`tflite_micro_runtime` which uses the same API as `tflite_runtime`. 
+The main difference is `tflite_micro_runtime` uses the Tensorflow-Lite Micro interpreter instead of the 
+Tensorflow-Lite interpreter.
 
-# TensorFlow Lite for Microcontrollers
+Using the Tensorflow-Lite Micro interpeter provides __~8x improvement__ on inference time.
 
-The TFLM code is currently in the process of being refactored out of the
-[Tensorflow github
-repository](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/lite/micro)
-into a standalone repo. This refactoring is currently in the initial stages and
-is expected to be completed towards the end of June 2021.
 
-# Contributing
-See our [contribution documentation](CONTRIBUTING.md).
+More details on the `tflite_runtime` Python package here:  
+https://www.tensorflow.org/lite/guide/python
 
-# Build Status
 
- * [GitHub Status](https://www.githubstatus.com/)
+More details on the Tensorflow-Lite Micro interpreter here:  
+https://github.com/tensorflow/tflite-micro
 
-## Official Builds
+__NOTE:__ This repo is a fork of the `tflite-micro` repo.
 
-Build Type       |    Status     |
------------      | --------------|
-CI (Linux)       | [![CI](https://github.com/tensorflow/tflite-micro/actions/workflows/ci.yml/badge.svg?event=schedule)](https://github.com/tensorflow/tflite-micro/actions/workflows/ci.yml?query=event%3Aschedule) |
-Code Sync        | [![Sync from Upstream TF](https://github.com/tensorflow/tflite-micro/actions/workflows/sync.yml/badge.svg)](https://github.com/tensorflow/tflite-micro/actions/workflows/sync.yml) |
 
-## Community Supported Builds
-Build Type      |    Status     |
------------     | --------------|
-Arduino         | [![Arduino](https://github.com/tensorflow/tflite-micro/actions/workflows/arduino.yml/badge.svg)](https://github.com/tensorflow/tflite-micro/actions/workflows/arduino.yml) [![Antmicro](https://github.com/antmicro/tensorflow-arduino-examples/actions/workflows/test_examples.yml/badge.svg)](https://github.com/antmicro/tensorflow-arduino-examples/actions/workflows/test_examples.yml) |
-Cortex-M        | [![Cortex-M](https://github.com/tensorflow/tflite-micro/actions/workflows/cortex_m.yml/badge.svg)](https://github.com/tensorflow/tflite-micro/actions/workflows/cortex_m.yml) |
-Sparkfun Edge   | [![Sparkfun Edge](https://github.com/tensorflow/tflite-micro/actions/workflows/sparkfun_edge.yml/badge.svg)](https://github.com/tensorflow/tflite-micro/actions/workflows/sparkfun_edge.yml) |
-Xtensa     | [![Xtensa](https://github.com/tensorflow/tflite-micro/actions/workflows/xtensa.yml/badge.svg?event=schedule)](https://github.com/tensorflow/tflite-micro/actions/workflows/xtensa.yml?query=event%3Aschedule) [![Xtensa](https://raw.githubusercontent.com/advaitjain/tflite-micro/local-continuous-builds/tensorflow/lite/micro/docs/local_continuous_builds/xtensa-build-status.svg)](https://github.com/advaitjain/tflite-micro/tree/local-continuous-builds/tensorflow/lite/micro/docs/local_continuous_builds/xtensa.md#summary) |
 
+# Install
 
-# Additional Documentation
+To install the `tflite_micro_runtime` Python package, run the PIP command on the RPI0:
 
- * [Continuous Integration](docs/continuous_integration.md)
+```bash
+pip3 install https://github.com/driedler/tflite-micro-rpi0/releases/download/1.0.0/tflite_micro_runtime-1.0.0-cp37-cp37m-linux_armv6l.whl
+```
+
+# Build
+
+To build the `tflite_micro_runtime` Python package, run the bash scripts in a Linux environment:
+
+```bash
+# Install Python3.7, numpy, and pybind11
+./tensorflow/lite/micro/tools/rpi0_pip_package/install_python.sh
+
+# Build tflite_micro_runtime wheel
+./tensorflow/lite/micro/tools/rpi0_pip_package/build_pip_package.sh
+```
+
+
+# Runtime Comparison Script
+
+A runtime comparsion script is available the compares the `tflite_micro_runtime` and `tflite_runtime` 
+packages at: [./tensorflow/lite/micro/python/runtime_comparison.py](./tensorflow/lite/micro/python/runtime_comparison.py)
+
+Refer to the comments at the top of the script for more details.

tensorflow/lite/micro/python/image_transform.py

@@ -3,9 +3,9 @@
 
 
 try:
-  from tflite_micro_runtime import _pywrap_tensorflow_interpreter_wrapper as _interpreter_wrapper
+  from tflite_micro_runtime import _pywrap_tflm_interpreter_wrapper as _interpreter_wrapper
 except:
-  import _pywrap_tensorflow_interpreter_wrapper as _interpreter_wrapper
+  import _pywrap_tflm_interpreter_wrapper as _interpreter_wrapper
 
 
 

tensorflow/lite/micro/python/interpreter.py

@@ -26,9 +26,9 @@
 
   # This file is part of tflite_runtime package.
 try:
-  from tflite_micro_runtime import _pywrap_tensorflow_interpreter_wrapper as _interpreter_wrapper
+  from tflite_micro_runtime import _pywrap_tflm_interpreter_wrapper as _interpreter_wrapper
 except:
-  import _pywrap_tensorflow_interpreter_wrapper as _interpreter_wrapper
+  import _pywrap_tflm_interpreter_wrapper as _interpreter_wrapper
 
 
 

tensorflow/lite/micro/python/interpreter_wrapper/CMakeLists.txt

@@ -16,8 +16,8 @@ message(STATUS "NUMPY_INCLUDE=${NUMPY_INCLUDE}")
 add_subdirectory(${CMAKE_CURRENT_LIST_DIR}/../../../experimental/image_transform ${CMAKE_CURRENT_BINARY_DIR}/image_transform)
 
 
-add_library(_pywrap_tensorflow_interpreter_wrapper SHARED EXCLUDE_FROM_ALL)
-target_sources(_pywrap_tensorflow_interpreter_wrapper
+add_library(_pywrap_tflm_interpreter_wrapper SHARED EXCLUDE_FROM_ALL)
+target_sources(_pywrap_tflm_interpreter_wrapper
 PUBLIC
   ${CMAKE_CURRENT_LIST_DIR}/interpreter_wrapper.cc
   ${CMAKE_CURRENT_LIST_DIR}/interpreter_wrapper_pybind11.cc
@@ -30,17 +30,17 @@ PUBLIC
 )
 
 # # To remove "lib" prefix.
-set_target_properties(_pywrap_tensorflow_interpreter_wrapper PROPERTIES PREFIX "")
+set_target_properties(_pywrap_tflm_interpreter_wrapper PROPERTIES PREFIX "")
 
-target_include_directories(_pywrap_tensorflow_interpreter_wrapper
+target_include_directories(_pywrap_tflm_interpreter_wrapper
   PUBLIC
     ${TENSORFLOW_SOURCE_DIR}
     ${PYTHON_INCLUDE}
     ${PYBIND11_INCLUDE}
     ${NUMPY_INCLUDE}
 )
 
-target_link_libraries(_pywrap_tensorflow_interpreter_wrapper
+target_link_libraries(_pywrap_tflm_interpreter_wrapper
 PUBLIC
   tensorflow-lite-micro
   image_transform

tensorflow/lite/micro/python/interpreter_wrapper/interpreter_wrapper.cc

@@ -140,7 +140,7 @@ TfLiteStatus GetSizeOfType(TfLiteContext* context, const TfLiteType type,
 }  // namespace
 
 
-InterpreterWrapper::InterpreterWrapper(std::unique_ptr<Model> model,
+MicroInterpreterWrapper::MicroInterpreterWrapper(std::unique_ptr<Model> model,
                      std::unique_ptr<PythonErrorReporter> error_reporter,
                      MicroInterpreter *interpreter, 
                      AllOpsResolver* resolver,
@@ -151,17 +151,17 @@ InterpreterWrapper::InterpreterWrapper(std::unique_ptr<Model> model,
       interpreter_(interpreter),
       tensor_arena_(tensor_arena) {}
 
-InterpreterWrapper::~InterpreterWrapper() {
+MicroInterpreterWrapper::~MicroInterpreterWrapper() {
   delete interpreter_;
 }
 
-PyObject* InterpreterWrapper::AllocateTensors() {
+PyObject* MicroInterpreterWrapper::AllocateTensors() {
   TFLITE_PY_ENSURE_VALID_INTERPRETER();
   TFLITE_PY_CHECK(interpreter_->AllocateTensors());
   Py_RETURN_NONE;
 }
 
-PyObject* InterpreterWrapper::Invoke() {
+PyObject* MicroInterpreterWrapper::Invoke() {
   TFLITE_PY_ENSURE_VALID_INTERPRETER();
 
   // Release the GIL so that we can run multiple interpreters in parallel
@@ -176,29 +176,29 @@ PyObject* InterpreterWrapper::Invoke() {
   Py_RETURN_NONE;
 }
 
-PyObject* InterpreterWrapper::InputIndices() const {
+PyObject* MicroInterpreterWrapper::InputIndices() const {
   TFLITE_PY_ENSURE_VALID_INTERPRETER();
   PyObject* np_array = PyArrayFromIntVector(interpreter_->inputs().data(),
                                             interpreter_->inputs().size());
 
   return PyArray_Return(reinterpret_cast<PyArrayObject*>(np_array));
 }
 
-PyObject* InterpreterWrapper::OutputIndices() const {
+PyObject* MicroInterpreterWrapper::OutputIndices() const {
   PyObject* np_array = PyArrayFromIntVector(interpreter_->outputs().data(),
                                             interpreter_->outputs().size());
 
   return PyArray_Return(reinterpret_cast<PyArrayObject*>(np_array));
 }
 
-int InterpreterWrapper::NumTensors() const {
+int MicroInterpreterWrapper::NumTensors() const {
   if (!interpreter_) {
     return 0;
   }
   return interpreter_->tensors_size();
 }
 
-std::string InterpreterWrapper::TensorName(int i) const {
+std::string MicroInterpreterWrapper::TensorName(int i) const {
   if (!interpreter_ || i >= this->NumTensors() || i < 0) {
     return "";
   }
@@ -207,7 +207,7 @@ std::string InterpreterWrapper::TensorName(int i) const {
   return tensor->name ? tensor->name : "";
 }
 
-PyObject* InterpreterWrapper::TensorType(int i) const {
+PyObject* MicroInterpreterWrapper::TensorType(int i) const {
   TFLITE_PY_ENSURE_VALID_INTERPRETER();
   TFLITE_PY_TENSOR_BOUNDS_CHECK(i);
 
@@ -225,7 +225,7 @@ PyObject* InterpreterWrapper::TensorType(int i) const {
   return PyArray_TypeObjectFromType(code);
 }
 
-PyObject* InterpreterWrapper::TensorSize(int i) const {
+PyObject* MicroInterpreterWrapper::TensorSize(int i) const {
   TFLITE_PY_ENSURE_VALID_INTERPRETER();
   TFLITE_PY_TENSOR_BOUNDS_CHECK(i);
 
@@ -240,14 +240,14 @@ PyObject* InterpreterWrapper::TensorSize(int i) const {
   return PyArray_Return(reinterpret_cast<PyArrayObject*>(np_array));
 }
 
-PyObject* InterpreterWrapper::TensorQuantization(int i) const {
+PyObject* MicroInterpreterWrapper::TensorQuantization(int i) const {
   TFLITE_PY_ENSURE_VALID_INTERPRETER();
   TFLITE_PY_TENSOR_BOUNDS_CHECK(i);
   const TfLiteTensor* tensor = interpreter_->tensor(i);
   return PyTupleFromQuantizationParam(tensor->params);
 }
 
-PyObject* InterpreterWrapper::TensorQuantizationParameters(int i) const {
+PyObject* MicroInterpreterWrapper::TensorQuantizationParameters(int i) const {
   TFLITE_PY_ENSURE_VALID_INTERPRETER();
   TFLITE_PY_TENSOR_BOUNDS_CHECK(i);
   const TfLiteTensor* tensor = interpreter_->tensor(i);
@@ -281,7 +281,7 @@ PyObject* InterpreterWrapper::TensorQuantizationParameters(int i) const {
   return result;
 }
 
-PyObject* InterpreterWrapper::SetTensor(int i, PyObject* value) {
+PyObject* MicroInterpreterWrapper::SetTensor(int i, PyObject* value) {
   TFLITE_PY_ENSURE_VALID_INTERPRETER();
   TFLITE_PY_TENSOR_BOUNDS_CHECK(i);
 
@@ -384,7 +384,7 @@ PyObject* CheckGetTensorArgs(MicroInterpreter* interpreter_, int tensor_index,
 
 }  // namespace
 
-PyObject* InterpreterWrapper::GetTensor(int i) const {
+PyObject* MicroInterpreterWrapper::GetTensor(int i) const {
   // Sanity check accessor
   TfLiteTensor* tensor = nullptr;
   int type_num = 0;
@@ -432,7 +432,7 @@ PyObject* InterpreterWrapper::GetTensor(int i) const {
   }
 }
 
-PyObject* InterpreterWrapper::tensor(PyObject* base_object, int i) {
+PyObject* MicroInterpreterWrapper::tensor(PyObject* base_object, int i) {
   // Sanity check accessor
   TfLiteTensor* tensor = nullptr;
   int type_num = 0;
@@ -452,10 +452,10 @@ PyObject* InterpreterWrapper::tensor(PyObject* base_object, int i) {
   return PyArray_Return(np_array);
 }
 
-InterpreterWrapper* InterpreterWrapper::CreateWrapperCPPFromFile(
+MicroInterpreterWrapper* MicroInterpreterWrapper::CreateWrapperCPPFromFile(
     const char* model_path, size_t tensor_arena_size, std::string* error_msg) {
   std::unique_ptr<PythonErrorReporter> error_reporter(new PythonErrorReporter);
-  std::unique_ptr<InterpreterWrapper::Model> model =
+  std::unique_ptr<MicroInterpreterWrapper::Model> model =
       Model::BuildFromFile(model_path, error_reporter.get());
   if(tensor_arena_size == 0 || tensor_arena_size > 64*1024*1024) {
     *error_msg = "Invalid tensor_arena_size";
@@ -479,15 +479,15 @@ InterpreterWrapper* InterpreterWrapper::CreateWrapperCPPFromFile(
     error_reporter.get()
   );
 
-  auto wrapper = new InterpreterWrapper(
+  auto wrapper = new MicroInterpreterWrapper(
     std::move(model), std::move(error_reporter),
     interpreter, resolver, tensor_arena);
 
   return wrapper;
 }
 
 
-PyObject* InterpreterWrapper::ResetVariableTensors() {
+PyObject* MicroInterpreterWrapper::ResetVariableTensors() {
   TFLITE_PY_ENSURE_VALID_INTERPRETER();
   TFLITE_PY_CHECK(interpreter_->ResetVariableTensors());
   Py_RETURN_NONE;

tensorflow/lite/micro/python/interpreter_wrapper/interpreter_wrapper.h

@@ -41,15 +41,15 @@ namespace interpreter_wrapper {
 
 class PythonErrorReporter;
 
-class InterpreterWrapper {
+class MicroInterpreterWrapper {
  public:
   using Model = FlatBufferModel;
 
   // SWIG caller takes ownership of pointer.
-  static InterpreterWrapper* CreateWrapperCPPFromFile(
+  static MicroInterpreterWrapper* CreateWrapperCPPFromFile(
       const char* model_path, size_t tensor_arena_size, std::string* error_msg);
 
-  ~InterpreterWrapper();
+  ~MicroInterpreterWrapper();
   PyObject* AllocateTensors();
   PyObject* Invoke();
 
@@ -80,18 +80,18 @@ class InterpreterWrapper {
 
  private:
 
-  InterpreterWrapper(std::unique_ptr<Model> model,
+  MicroInterpreterWrapper(std::unique_ptr<Model> model,
                      std::unique_ptr<PythonErrorReporter> error_reporter,
                      MicroInterpreter *interpreter, 
                      AllOpsResolver* resolver,
                      uint8_t* tensor_arena);
 
-  // InterpreterWrapper is not copyable or assignable. 
-  InterpreterWrapper() = delete;
-  InterpreterWrapper(const InterpreterWrapper& rhs) = delete;
+  // MicroInterpreterWrapper is not copyable or assignable. 
+  MicroInterpreterWrapper() = delete;
+  MicroInterpreterWrapper(const MicroInterpreterWrapper& rhs) = delete;
 
 
-  // The public functions which creates `InterpreterWrapper` should ensure all
+  // The public functions which creates `MicroInterpreterWrapper` should ensure all
   // these member variables are initialized successfully. Otherwise it should
   // report the error and return `nullptr`.
   MicroInterpreter* interpreter_;