CMSIS-Executorch/cmsis-executorch-simple.csolution.yml at main · Arm-Examples/CMSIS-Executorch · GitHub

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# Copyright 2026 Arm Limited and/or its affiliates.
# SPDX-License-Identifier: Apache-2.0
#
# A minimal ExecuTorch-on-Ethos-U85 example for the Corstone-320 (SSE-320) FVP.
# The model is exported from PyTorch in a venv (no Docker) and converted to a
# .pte as a build step. The `mlops:` node makes CMSIS-Toolbox emit
# `cmsis-executorch-simple.cbuild-mlops.yml`, which the export script consumes
# to drive Vela -- see model/export_model.py.
solution:
  created-for: CMSIS-Toolbox@2.14.1
  cdefault:
  compiler: AC6

  packs:
    # Pinned exactly: the pack's C++ runtime and the Python exporter pinned in
    # requirements-executorch.txt must be the same ExecuTorch version, or the
    # .pte fails to load. `cbuild --packs` fetches it from the public index.
    - pack: PyTorch::ExecuTorch@1.4.0
    - pack: ARM::CMSIS
    - pack: ARM::CMSIS-NN
    - pack: ARM::CMSIS-Compiler
    - pack: ARM::Cortex_DFP

  target-types:
    # Corstone-320 with an Ethos-U85 NPU, simulated on the Arm FVP.
    - type: SSE-320-U85
      board: SSE-320
      device: SSE-320-FVP
      variables:
        - Board-Layer: $SolutionDir()$/board/Corstone-320/Board-U85.clayer.yml
        - AI-Layer: $SolutionDir()$/ai_layer/ai_layer.clayer.yml
      target-set:
        - set:
          images:
            - project-context: cmsis-executorch-simple.Debug
          debugger:
            name: Arm-FVP
            model: FVP_Corstone_SSE-320
            config-file: board/Corstone-320/fvp_config.txt
            args: "--simlimit 60 "

  build-types:
    - type: Debug
      debug: on
      optimize: debug

  projects:
    - project: ./cmsis-executorch-simple.cproject.yml

  # MLOps information: exported to cmsis-executorch-simple.cbuild-mlops.yml when
  # building with `cbuild ... --active SSE-320-U85`. Retarget the NPU here and
  # the export script (model/export_model.py) picks it up automatically.
  # https://open-cmsis-pack.github.io/cmsis-toolbox/build-overview/#mlops-information
  mlops:
    description: TinyCNN int8 image classifier for Ethos-U85
    npu:
      type: Ethos-U85
    vela:
      system: Ethos_U85_SYS_DRAM_Mid # system-config from the Vela config
      memory: Shared_Sram # memory-mode from the Vela config
    model:
      clayer: $AI-Layer$
      name: TinyCNN
    simulator:
      target: SSE-320-U85