Cortex M

Cortex-M (CMSIS-NN) Backend

Architecture

Not a delegate backend — no partitioner. Custom ops and graph passes replace ATen quantized ops with CMSIS-NN equivalents at the graph level.

Pipeline

Uses standard PT2E quantization (prepare_pt2e / convert_pt2e), then CortexMPassManager rewrites quantized ops to cortex_m:: equivalents.

from executorch.backends.cortex_m.quantizer.quantizer import CortexMQuantizer
from executorch.backends.cortex_m.passes.cortex_m_pass_manager import CortexMPassManager
from torch.export import export
from torchao.quantization.pt2e.quantize_pt2e import convert_pt2e, prepare_pt2e
from executorch.exir import to_edge_transform_and_lower, EdgeCompileConfig

quantizer = CortexMQuantizer()
captured = export(model, example_inputs).module()
prepared = prepare_pt2e(captured, quantizer)
prepared(*example_inputs)  # calibration
quantized = convert_pt2e(prepared)

exported = export(quantized, example_inputs)
edge = to_edge_transform_and_lower(
    exported,
    compile_config=EdgeCompileConfig(_check_ir_validity=False),
)
edge._edge_programs["forward"] = CortexMPassManager(
    edge.exported_program(), CortexMPassManager.pass_list
).transform()
et_program = edge.to_executorch()