Synaptics Torq Compiler
The torq-compiler Python package enables the compilation of machine learning models for the Synaptics Torq NPU and provides simulation capabilities for corresponding hardware. It bundles the Torq compiler alongside the IREE compiler Python bindings into a single wheel with both namespaces.
Installation
pip install torq-compiler
Optional extras
Install with one or more extras to enable optional features (e.g. pip install "torq-compiler[onnx,tflite]"):
onnx: ONNX model import, self-verification,torq-gen-config, and quantizationtflite: TFLite model conversion viatosa-converter-for-tflitetf: TensorFlow SavedModel import and TFLite dynamic-to-static shape conversion (torq-convert-static)profile: profiling annotation and Perfetto trace renderingall: all of the extras above
Documentation
Comprehensive compiler documentation is available in the Usage Guide.
1 maintainer
Metadata
1 maintainer
Release files for torq-compiler 2.2.1
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Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| torq_compiler-2.2.1-cp312-cp312-manylinux_2_39_x86_64.whl | CPython 3.12 | CPython 3.12 | Linux glibc 2.39+ x86-64 | Details |
Release files / torq_compiler-2.2.1-cp312-cp312-manylinux_2_39_x86_64.whl
| Download URL | torq_compiler-2.2.1-cp312-cp312-manylinux_2_39_x86_64.whl |
|---|---|
| Size | 87.1 MB |
| Tags | CPython 3.12 Linux glibc 2.39+ x86-64 |
|
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Signed by GitHub Actions, verified by PyPI on Sep 23, 2026.
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