chore: import upstream snapshot with attribution

tensorflow/lite/tools/pip_package/README.md

@@ -0,0 +1,153 @@
+# Building TensorFlow Lite Standalone Pip
+
+Many users would like to deploy TensorFlow lite interpreter and use it from
+Python without requiring the rest of TensorFlow.
+
+## Steps
+
+To build a binary wheel run this script:
+
+```sh
+sudo apt install swig libjpeg-dev zlib1g-dev python3-dev python3-numpy
+pip install numpy pybind11
+sh tensorflow/lite/tools/pip_package/build_pip_package_with_cmake.sh
+```
+
+That will print out some output and a .whl file. You can then install that
+
+```sh
+pip install --upgrade <wheel>
+```
+
+You can also build a wheel inside docker container using make tool. For example
+the following command will cross-compile tflite-runtime package for python2.7
+and python3.7 (from Debian Buster) on Raspberry Pi:
+
+```sh
+make BASE_IMAGE=debian:buster PYTHON_VERSION=2.7 TENSORFLOW_TARGET=rpi docker-build
+make BASE_IMAGE=debian:buster PYTHON_VERSION=3.7 TENSORFLOW_TARGET=rpi docker-build
+```
+
+Another option is to cross-compile for python3.5 (from Debian Stretch) on ARM64
+board:
+
+```sh
+make BASE_IMAGE=debian:stretch PYTHON_VERSION=3.5 TENSORFLOW_TARGET=aarch64 docker-build
+```
+
+To build for python3.6 (from Ubuntu 18.04) on x86_64 (native to the docker
+image) run:
+
+```sh
+make BASE_IMAGE=ubuntu:18.04 PYTHON_VERSION=3.6 TENSORFLOW_TARGET=native docker-build
+```
+
+In addition to the wheel there is a way to build Debian package by adding
+`BUILD_DEB=y` to the make command (only for python3):
+
+```sh
+make BASE_IMAGE=debian:buster PYTHON_VERSION=3.6 TENSORFLOW_TARGET=rpi BUILD_DEB=y docker-build
+```
+
+## Alternative build with Bazel (experimental)
+
+There is another build steps to build a binary wheel which uses Bazel instead of
+Makefile. You don't need to install additional dependencies.
+This approach can leverage TF's `ci_build.sh` for ARM cross builds.
+
+### Normal build for your workstation
+
+```sh
+tensorflow/lite/tools/pip_package/build_pip_package_with_bazel.sh
+```
+
+### Optimized build for your workstation
+The output may have a compatibility issue with other machines but it gives the
+best performance for your workstation.
+
+```sh
+tensorflow/lite/tools/pip_package/build_pip_package_with_bazel.sh native
+```
+
+### Cross build for armhf Python 3.5
+
+```sh
+tensorflow/tools/ci_build/ci_build.sh PI-PYTHON3 \
+  tensorflow/lite/tools/pip_package/build_pip_package_with_bazel.sh armhf
+```
+
+### Cross build for armhf Python 3.7
+
+```sh
+tensorflow/tools/ci_build/ci_build.sh PI-PYTHON37 \
+  tensorflow/lite/tools/pip_package/build_pip_package_with_bazel.sh armhf
+```
+
+### Cross build for aarch64 Python 3.5
+
+```sh
+tensorflow/tools/ci_build/ci_build.sh PI-PYTHON3 \
+  tensorflow/lite/tools/pip_package/build_pip_package_with_bazel.sh aarch64
+```
+
+### Cross build for aarch64 Python 3.8
+
+```sh
+tensorflow/tools/ci_build/ci_build.sh PI-PYTHON38 \
+  tensorflow/lite/tools/pip_package/build_pip_package_with_bazel.sh aarch64
+```
+
+### Cross build for aarch64 Python 3.9
+
+```sh
+tensorflow/tools/ci_build/ci_build.sh PI-PYTHON39 \
+  tensorflow/lite/tools/pip_package/build_pip_package_with_bazel.sh aarch64
+```
+
+### Native build for Windows
+
+```sh
+bash tensorflow/lite/tools/pip_package/build_pip_package_with_bazel.sh windows
+```
+
+## Enable TF OP support (Flex delegate)
+
+If you want to use TF ops with Python API, you need to enable flex support.
+You can build TFLite interpreter with flex ops support by providing
+`--define=tflite_pip_with_flex=true` to Bazel.
+
+Here are some examples.
+
+### Normal build with Flex for your workstation
+
+```sh
+CUSTOM_BAZEL_FLAGS=--define=tflite_pip_with_flex=true \
+  tensorflow/lite/tools/pip_package/build_pip_package_with_bazel.sh
+```
+
+### Cross build with Flex for armhf Python 3.7
+
+```sh
+CI_DOCKER_EXTRA_PARAMS="-e CUSTOM_BAZEL_FLAGS=--define=tflite_pip_with_flex=true" \
+  tensorflow/tools/ci_build/ci_build.sh PI-PYTHON37 \
+  tensorflow/lite/tools/pip_package/build_pip_package_with_bazel.sh armhf
+```
+
+## Usage
+
+Note, unlike tensorflow this will be installed to a `tflite_runtime` namespace.
+You can then use the Tensorflow Lite interpreter as.
+
+```python
+from tflite_runtime.interpreter import Interpreter
+interpreter = Interpreter(model_path="foo.tflite")
+```
+
+This currently works to build on Linux machines including Raspberry Pi. In
+the future, cross compilation to smaller SOCs like Raspberry Pi from
+bigger host will be supported.
+
+## Caveats
+
+* You cannot use TensorFlow Select ops, only TensorFlow Lite builtins.
+* Currently custom ops and delegates cannot be registered.