Infrastructure to enable deployment of ML models to low-power resource-constrained embedded targets (including microcontrollers and digital signal processors).
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feat(compression): add module for defining test .tflite models #2798
Add a module that provides tools for constructing .tflite
flatbuffers from a Python dictionary representation of a model.
This is useful for declaratively defining model flatbuffers for
testing, which is faster and clearer than building up model
flatbuffers programmatically.
The implementation should stay low-level and independent from any
helpers in this project which make constructing model and
flatbuffers easier, because this module is used to define tests
for those helpers.
Add a module that provides tools for constructing .tflite flatbuffers from a Python dictionary representation of a model. This is useful for declaratively defining model flatbuffers for testing, which is faster and clearer than building up model flatbuffers programmatically.
The implementation should stay low-level and independent from any helpers in this project which make constructing model and flatbuffers easier, because this module is used to define tests for those helpers.
BUG=#2636