2.1 KiB
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);