@specs-feup/onnx-flow

A high-performance tool for decomposing and optimizing ONNX models into hardware-aware data-flow representations.

onnx-flow transforms high-level neural network operations (like AveragePool, Conv, or Softmax) into lower-level operations (suitable for offloading). It enables decompositions, explicit loop-lowering, optimizations (such as loop fusion), and graph partitioning for distributed workloads. Outputs can be generated in ONNX, JSON and DOT formats with multiple visualization options.

Key Features

• Operation Decomposition: Transforms high-level neural network operations (like AveragePool, Conv, or Softmax) into lower-level primitives suitable for offloading.
• Optimizations: Applies advanced optimizations, such as loop fusion, to streamline execution.
• Graph Partitioning: Supports splitting graphs into partitions to facilitate distributed workloads, automatically managing boundary tensors.
• Multi-Format Output: Generates processed graphs in ONNX, JSON, and DOT formats to suit various integration needs.
• Visualization: Provides multiple visualization options, including static SVG rendering and interactive Graphviz Online links.

Installation

To install the package via npm:

npm install @specs-feup/onnx-flow

CLI Usage

The CLI is the primary way to transform models. It supports both .onnx binaries and .json flow-graph exports.

onnx-flow <input_file> [options]

1. Partitioning Options

Overrides transformation options to ensure split-point stability.

• --partition, --pt <nodeId | OpType Instance>: Partition the graph into head/tail at a specific node (e.g., --pt 12 or --pt MatMul 2).

2. Transformation & Optimization

• -f, --fuse: Fuse supported operators into a single Loop (Default: true).
• -c, --coalesce: Use coalesced scalar MAC for MatMul inside Loop bodies (Default: true).
• -r, --recurse: Recursively decompose generated loop bodies (Default: false).
• --ll, --loopLowering: Enable explicit Loop node generation (Default: true).
• --dgc, --decomposeForCgra: Apply CGRA-specific decomposition logic.

3. Output & Visualization

• -o, --output <path>: Save the resulting graph to a specific file.
• --fm, --format <json|dot>: Choose output format, besides reconverted ONNX (Default: json).
• --vz, --visualization <0|1|2>: 0 = None, 1 = Graphviz Online link, 2 = Local server.
• --fmtr, --formatter <default|cgra>: Choose the DOT styling engine.

4. Other

• --version: Show version number.
• --help: Show detailed usage.

License

Licensed under the Apache 2.0 License.