chore: import upstream snapshot with attribution

tensorflow/lite/tools/strip_buffers/README.md

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+# TFLite Buffer-Stripping Tool/Library
+
+**NOTE: This is an advanced tool used to reduce bandwidth usage in Neural
+Architecture Search applications. Use with caution.**
+
+The tools in this directory make it easier to distribute TFLite models to
+multiple devices over networks with the sole aim of benchmarking *latency*
+performance. The intended workflow is as follows:
+
+*   The stripping tool empties eligible constants from a TFLite flatbuffer to
+    reduce its size.
+*   This lean model can be easily transported to devices over a network.
+*   The reconstitution tool on the device takes in a flatbuffer in memory, and
+    fills in the appropriate buffers with random data.
+
+As an example, see the before/after sizes for MobileNetV1:
+
+*   Float: 16.9MB -> 12KB
+*   Quantized: 4.3MB -> 17.6 KB
+
+**NOTE: This tool only supports single subgraphs for now.**
+
+There are two tools in this directory:
+
+## 1. Stripping buffers out of TFLite flatbuffers
+
+This tool takes in an input `flatbuffer`, and strips out (or 'empties') the
+buffers (constant data) for tensors that follow the following guidelines:
+
+*   Are either of: Float32, Int32, UInt8, Int8
+*   If Int32, the tensor should have a min of 10 elements
+
+The second rule above protects us from invalidating constant data that cannot be
+randomised (for example, Reshape 'shape' input).
+
+To run the associated script:
+
+```
+bazel run -c opt tensorflow/lite/tools/strip_buffers:strip_buffers_from_fb -- --input_flatbuffer=/input/path.tflite --output_flatbuffer=/output/path.tflite
+```
+
+## 2. Stripping buffers out of TFLite flatbuffers
+
+The idea here is to reconstitute the lean flatbuffer `Model` generared in the
+above step, by filling in random data whereever necessary.
+
+The prototype script can be called as:
+
+```
+bazel run -c opt tensorflow/lite/tools/strip_buffers:reconstitute_buffers_into_fb -- --input_flatbuffer=/input/path.tflite --output_flatbuffer=/output/path.tflite
+```
+
+## C++ Library
+
+Both the above tools are present as `stripping_lib` in this directory, which
+mutate the flatbuffer(s) in-memory. This ensures we can do the above two steps
+without touching the filesystem again.