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[High impact] Refactors ggml backend linking and runtime loading. Fix the remaining direct CPU call in the TTS test before merging. Findings
SummaryThis PR adds ggml runtime CPU dispatch and plugin installation support.
Previous Windows installation finding: danhansen correctly disputed it, and Greptile conceded it. The configured library destination already applies to MODULE DLLs. Diagram%%{init: {'theme': 'neutral'}}%%
flowchart LR
A[Start backend manager] --> B[Set Vulkan cache workaround]
B --> C[Load ggml plugins once]
C --> D[List devices]
D --> E[Create selected backends]
E --> F[Get CPU buffer and functions through registry]
Reviews (4) · Last reviewed commit: "fix: handle null backends and relative p..." · Reviewed by Greptile |
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Review comments at @src/common/ggml_backend_utils.h:
- Around line 9-13: Update is_cpu_backend to return false when the backend is
null, then check the result of ggml_backend_get_device before calling
ggml_backend_dev_type; preserve the CPU-type comparison for non-null devices.
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📒 Files selected for processing (11)
CMakeLists.txtdocs/build.mdsrc/common/ggml_backend_utils.hsrc/runtime/ggml/CMakeLists.txtsrc/runtime/ggml/backend.cppsrc/tts/magpietts/lt.cppsrc/tts/magpietts/model.cppsrc/tts/magpietts/model.hsrc/tts/nanocodec/model.cpptests/cpp/common/test_shared_utilities.cpptests/install/sdk_consumer_test.py
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- src/tts/magpietts/model.h
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Support GGML_BACKEND_DL and GGML_CPU_ALL_VARIANTS using ggml's existing runtime dispatch. Link through ggml, discover CPU devices and functions through its registry, and load plugins before device enumeration. Follow the pinned ggml installation rules: install plugins beside executables or in GGML_BACKEND_DIR. Preserve the Vulkan cache workaround and refresh the backend list when build options change. Add portable CPU build documentation and installation/relocation coverage. Validation on Linux x86_64: - CPU TTS linked and plugin builds: 7/7 CTest tests each. - Custom install directory, variant-option toggling, and CPU variant graph execution pass; license-header and whitespace checks pass. - Earlier CPU ASR validation: 11/11 tests in linked and all-variant builds. GPU backends, Windows, and macOS remain untested. CUDA TTS still requires GGML_BACKEND_DL=OFF for its backend-specific optimized paths. AI assistance: Codex assisted with implementation, review, documentation, and automated validation. Signed-off-by: Dan Hansen <dhansen@byu.net>
for more information, see https://pre-commit.ci
Preserve null-safe CPU detection and run the installed backend test from the relocated prefix so relative GGML_BACKEND_DIR values resolve correctly. Validation: CPU plugin TTS build and 3 targeted CTest tests pass with GGML_BACKEND_DIR:PATH=plugins. Null-backend, null-device, and loaded-CPU checks pass, as do license-header and whitespace checks. AI assistance: Codex implemented and validated these review fixes. Signed-off-by: Dan Hansen <dhansen@byu.net>
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| target_link_libraries(nemo_speech_runtime_ggml PUBLIC ${GGML_DEPENDENCIES}) | ||
| # ggml propagates linked backends and builds plugins when GGML_BACKEND_DL is enabled. | ||
| target_link_libraries(nemo_speech_runtime_ggml PUBLIC ggml) |
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With GGML_BACKEND_DL=ON and TTS tests enabled, test_nanocodec_decode_guard still calls ggml_backend_cpu_init() directly. Linking through ggml no longer links the CPU plugin into that executable, so the build fails at the link step.
Update the test to load the plugins and create its CPU backend through ggml_backend_init_by_type(), as the runtime now does.
Support GGML_BACKEND_DL and GGML_CPU_ALL_VARIANTS using ggml's existing runtime dispatch. Link through ggml, discover CPU devices and functions through its registry, and load plugins before device enumeration.
Follow the pinned ggml installation rules: install plugins beside executables or in GGML_BACKEND_DIR. Preserve the Vulkan cache workaround and refresh the backend list when build options change. Add portable CPU build documentation and installation/relocation coverage.
Validation on Linux x86_64:
GPU backends, Windows, and macOS remain untested. CUDA TTS still requires GGML_BACKEND_DL=OFF for its backend-specific optimized paths.
AI assistance: Codex assisted with implementation, review, documentation, and automated validation.