feat(compression): implement model_editor for TFLite model manipulation #3439
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Implement unified module for creating, reading, and modifying TFLite models with a clean API. The module eliminates manual index tracking and buffer management through automatic bookkeeping, supporting both declarative and imperative construction styles. Wrapper classes (Tensor, Operator, Subgraph, Model) hold the underlying flatbuffer T objects as backing storage rather than copying fields into dataclasses. This ensures all schema fields are preserved during read-modify-write cycles, even fields not explicitly handled by model_editor. Future schema additions will be preserved automatically. Add comprehensive test coverage including field preservation tests that verify unhandled schema fields survive read-modify-write. BUG=implements tensorflow#3256
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This is the first in a series of commits being submitted individually from #3400. See that PR for the full context of the change. |
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Implement unified module for creating, reading, and modifying TFLite
models with a clean API. The module eliminates manual index tracking
and buffer management through automatic bookkeeping, supporting both
declarative and imperative construction styles.
Wrapper classes (Tensor, Operator, Subgraph, Model) hold the underlying
flatbuffer T objects as backing storage rather than copying fields into
dataclasses. This ensures all schema fields are preserved during
read-modify-write cycles, even fields not explicitly handled by
model_editor. Future schema additions will be preserved automatically.
Add comprehensive test coverage including field preservation tests that
verify unhandled schema fields survive read-modify-write.
BUG=implements #3256