chore: import upstream snapshot with attribution

tensorflow/lite/tools/serialization/README.md

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+# TFLite Serialization Tool
+
+**NOTE:** This tool is intended for advanced users only, and should be used with
+care.
+
+The (C++) serialization library generates and writes a TFLite flatbuffer given
+an `Interpreter` or `Subgraph`. Example use-cases include authoring models with
+the `Interpreter` API, or updating models on-device (by modifying `tensor.data`
+for relevant tensors).
+
+## Serialization
+
+### Writing flatbuffer to file
+
+To write a TFLite model from an `Interpreter` (see `lite/interpreter.h`):
+`std::unique_ptr<tflite::Interpreter> interpreter; // ...build/modify
+interpreter... tflite::ModelWriter writer(interpreter.get()); std::string
+filename = "/tmp/model.tflite"; writer.Write(filename);`
+
+Note that the above API does not support custom I/O tensors or custom ops yet.
+However, it does support model with Control Flow.
+
+To generate/write a flatbuffer for a particular `Subgraph` (see
+`lite/core/subgraph.h`) you can use `SubgraphWriter`.
+
+```
+std::unique_ptr<tflite::Interpreter> interpreter;
+// ...build/modify interpreter...
+// The number of subgraphs can be obtained by:
+// const int num_subgraphs = interpreter_->subgraphs_size();
+// Note that 0 <= subgraph_index < num_subgraphs
+tflite::SubgraphWriter writer(&interpreter->subgraph(subgraph_index));
+std::string filename = "/tmp/model.tflite";
+writer.Write(filename);
+```
+
+`SubgraphWriter` supports custom ops and/or custom I/O tensors.
+
+### Generating flatbuffer in-memory
+
+Both `ModelWriter` and `SubgraphWriter` support a `GetBuffer` method to return
+the generated flatbuffer in-memory:
+
+```
+std::unique_ptr<uint8_t[]> output_buffer;
+size_t output_buffer_size;
+tflite::ModelWriter writer(interpreter.get());
+writer.GetBuffer(&output_buffer, &output_buffer_size);
+```
+
+## De-serialization
+
+The flatbuffers written as above can be de-serialized just like any other TFLite
+model, for eg:
+
+```
+std::unique_ptr<FlatBufferModel> model =
+    FlatBufferModel::BuildFromFile(filename);
+tflite::ops::builtin::BuiltinOpResolver resolver;
+InterpreterBuilder builder(*model, resolver);
+std::unique_ptr<Interpreter> new_interpreter;
+builder(&new_interpreter);
+```