ONNX Runtime

This is an attempt at a Rust wrapper for Microsoft's ONNX Runtime (version 1.5).

This project consist on two crates:

onnxruntime-sys: Low-level binding to the C API;
onnxruntime: High-level and safe API.

The build.rs script supports downloading pre-built versions of the Microsoft ONNX Runtime, which provides the following targets:

CPU:

Linux x86_64
macOS x86_64
Windows i686
Windows x86_64

GPU:

Linux x86_64
Windows x86_64

WARNING:

This is an experiment and work in progress; it is not complete/working/safe. Help welcome!
Basic inference works, see onnxruntime/examples/sample.rs or onnxruntime/tests/integration_tests.rs
ONNX Runtime has many options to control the inference process but those options are not yet exposed.
This was developed and tested on macOS Catalina. Other platforms should work but have not been tested.

Setup

Three different strategy to obtain the ONNX Runtime are supported by the build.rs script:

Download a pre-built binary from upstream;
Point to a local version already installed;
Compile from source (not yet implemented).

To select which strategy to use, set the ORT_STRATEGY environment variable to:

download: This is the default if ORT_STRATEGY is not set;
system: To use a locally installed version
compile: To compile the library

The download strategy supports downloading a version of ONNX that supports CUDA. To use this, set the environment variable ORT_USE_CUDA=1 (only supports Linux or Windows).

Until the build script allow compilation of the runtime, see the compilation notes for some details on the process.

Example

The C++ example that uses the C API (C_Api_Sample.cpp) was ported to both the low level crate (onnxruntime-sys) and the high level on (onnxruntime).

onnxruntime-sys

To run this example (onnxruntime-sys/examples/c_api_sample.rs):

# Download the model (SqueezeNet 1.0, ONNX version: 1.3, Opset version: 8)
❯ curl -LO "https://github.com/onnx/models/raw/master/vision/classification/squeezenet/model/squeezenet1.0-8.onnx"
❯ cargo run --example c_api_sample
[...]
    Finished dev [unoptimized + debuginfo] target(s) in 1.88s
     Running `target/debug/examples/c_api_sample`
Using Onnxruntime C API
2020-08-09 09:37:41.554922 [I:onnxruntime:, inference_session.cc:174 ConstructorCommon] Creating and using per session threadpools since use_per_session_threads_ is true
2020-08-09 09:37:41.556650 [I:onnxruntime:, inference_session.cc:830 Initialize] Initializing session.
2020-08-09 09:37:41.556665 [I:onnxruntime:, inference_session.cc:848 Initialize] Adding default CPU execution provider.
2020-08-09 09:37:41.556678 [I:onnxruntime:test, bfc_arena.cc:15 BFCArena] Creating BFCArena for Cpu
2020-08-09 09:37:41.556687 [V:onnxruntime:test, bfc_arena.cc:32 BFCArena] Creating 21 bins of max chunk size 256 to 268435456
2020-08-09 09:37:41.558313 [I:onnxruntime:, reshape_fusion.cc:37 ApplyImpl] Total fused reshape node count: 0
2020-08-09 09:37:41.559327 [I:onnxruntime:, reshape_fusion.cc:37 ApplyImpl] Total fused reshape node count: 0
2020-08-09 09:37:41.559476 [I:onnxruntime:, reshape_fusion.cc:37 ApplyImpl] Total fused reshape node count: 0
2020-08-09 09:37:41.559607 [V:onnxruntime:, inference_session.cc:671 TransformGraph] Node placements
2020-08-09 09:37:41.559615 [V:onnxruntime:, inference_session.cc:673 TransformGraph] All nodes have been placed on [CPUExecutionProvider].
2020-08-09 09:37:41.559639 [I:onnxruntime:, session_state.cc:25 SetGraph] SaveMLValueNameIndexMapping
2020-08-09 09:37:41.559787 [I:onnxruntime:, session_state.cc:70 SetGraph] Done saving OrtValue mappings.
2020-08-09 09:37:41.560252 [I:onnxruntime:, session_state_initializer.cc:178 SaveInitializedTensors] Saving initialized tensors.
2020-08-09 09:37:41.563467 [I:onnxruntime:, session_state_initializer.cc:223 SaveInitializedTensors] Done saving initialized tensors
2020-08-09 09:37:41.563979 [I:onnxruntime:, inference_session.cc:919 Initialize] Session successfully initialized.
Number of inputs = 1
Input 0 : name=data_0
Input 0 : type=1
Input 0 : num_dims=4
Input 0 : dim 0=1
Input 0 : dim 1=3
Input 0 : dim 2=224
Input 0 : dim 3=224
2020-08-09 09:37:41.573127 [I:onnxruntime:, sequential_executor.cc:145 Execute] Begin execution
2020-08-09 09:37:41.573183 [I:onnxruntime:test, bfc_arena.cc:259 AllocateRawInternal] Extending BFCArena for Cpu. bin_num:13 rounded_bytes:3154176
2020-08-09 09:37:41.573197 [I:onnxruntime:test, bfc_arena.cc:143 Extend] Extended allocation by 4194304 bytes.
2020-08-09 09:37:41.573203 [I:onnxruntime:test, bfc_arena.cc:147 Extend] Total allocated bytes: 9137152
2020-08-09 09:37:41.573212 [I:onnxruntime:test, bfc_arena.cc:150 Extend] Allocated memory at 0x7fb7d6cb7000 to 0x7fb7d70b7000
2020-08-09 09:37:41.573248 [I:onnxruntime:test, bfc_arena.cc:259 AllocateRawInternal] Extending BFCArena for Cpu. bin_num:8 rounded_bytes:65536
2020-08-09 09:37:41.573256 [I:onnxruntime:test, bfc_arena.cc:143 Extend] Extended allocation by 4194304 bytes.
2020-08-09 09:37:41.573262 [I:onnxruntime:test, bfc_arena.cc:147 Extend] Total allocated bytes: 13331456
2020-08-09 09:37:41.573268 [I:onnxruntime:test, bfc_arena.cc:150 Extend] Allocated memory at 0x7fb7d70b7000 to 0x7fb7d74b7000
Score for class [0] =  0.000045440644
Score for class [1] =  0.0038458651
Score for class [2] =  0.00012494653
Score for class [3] =  0.0011804523
Score for class [4] =  0.0013169361
Done!

onnxruntime

To run this example (onnxruntime/examples/sample.rs):

# Download the model (SqueezeNet 1.0, ONNX version: 1.3, Opset version: 8)
❯ curl -LO "https://github.com/onnx/models/raw/master/vision/classification/squeezenet/model/squeezenet1.0-8.onnx"
❯ cargo run --example sample
[...]
    Finished dev [unoptimized + debuginfo] target(s) in 13.62s
     Running `target/debug/examples/sample`
Uninitialized environment found, initializing it with name "test".
2020-08-09 09:34:37.395577 [I:onnxruntime:, inference_session.cc:174 ConstructorCommon] Creating and using per session threadpools since use_per_session_threads_ is true
2020-08-09 09:34:37.399253 [I:onnxruntime:, inference_session.cc:830 Initialize] Initializing session.
2020-08-09 09:34:37.399284 [I:onnxruntime:, inference_session.cc:848 Initialize] Adding default CPU execution provider.
2020-08-09 09:34:37.399313 [I:onnxruntime:test, bfc_arena.cc:15 BFCArena] Creating BFCArena for Cpu
2020-08-09 09:34:37.399335 [V:onnxruntime:test, bfc_arena.cc:32 BFCArena] Creating 21 bins of max chunk size 256 to 268435456
2020-08-09 09:34:37.410516 [I:onnxruntime:, reshape_fusion.cc:37 ApplyImpl] Total fused reshape node count: 0
2020-08-09 09:34:37.417478 [I:onnxruntime:, reshape_fusion.cc:37 ApplyImpl] Total fused reshape node count: 0
2020-08-09 09:34:37.420131 [I:onnxruntime:, reshape_fusion.cc:37 ApplyImpl] Total fused reshape node count: 0
2020-08-09 09:34:37.422623 [V:onnxruntime:, inference_session.cc:671 TransformGraph] Node placements
2020-08-09 09:34:37.428863 [V:onnxruntime:, inference_session.cc:673 TransformGraph] All nodes have been placed on [CPUExecutionProvider].
2020-08-09 09:34:37.428954 [I:onnxruntime:, session_state.cc:25 SetGraph] SaveMLValueNameIndexMapping
2020-08-09 09:34:37.429079 [I:onnxruntime:, session_state.cc:70 SetGraph] Done saving OrtValue mappings.
2020-08-09 09:34:37.429925 [I:onnxruntime:, session_state_initializer.cc:178 SaveInitializedTensors] Saving initialized tensors.
2020-08-09 09:34:37.436300 [I:onnxruntime:, session_state_initializer.cc:223 SaveInitializedTensors] Done saving initialized tensors
2020-08-09 09:34:37.437255 [I:onnxruntime:, inference_session.cc:919 Initialize] Session successfully initialized.
Dropping the session options.
2020-08-09 09:34:37.448956 [I:onnxruntime:, sequential_executor.cc:145 Execute] Begin execution
2020-08-09 09:34:37.449041 [I:onnxruntime:test, bfc_arena.cc:259 AllocateRawInternal] Extending BFCArena for Cpu. bin_num:13 rounded_bytes:3154176
2020-08-09 09:34:37.449072 [I:onnxruntime:test, bfc_arena.cc:143 Extend] Extended allocation by 4194304 bytes.
2020-08-09 09:34:37.449087 [I:onnxruntime:test, bfc_arena.cc:147 Extend] Total allocated bytes: 9137152
2020-08-09 09:34:37.449104 [I:onnxruntime:test, bfc_arena.cc:150 Extend] Allocated memory at 0x7fb3b9585000 to 0x7fb3b9985000
2020-08-09 09:34:37.449176 [I:onnxruntime:test, bfc_arena.cc:259 AllocateRawInternal] Extending BFCArena for Cpu. bin_num:8 rounded_bytes:65536
2020-08-09 09:34:37.449196 [I:onnxruntime:test, bfc_arena.cc:143 Extend] Extended allocation by 4194304 bytes.
2020-08-09 09:34:37.449209 [I:onnxruntime:test, bfc_arena.cc:147 Extend] Total allocated bytes: 13331456
2020-08-09 09:34:37.449222 [I:onnxruntime:test, bfc_arena.cc:150 Extend] Allocated memory at 0x7fb3b9985000 to 0x7fb3b9d85000
Dropping Tensor.
Score for class [0] =  0.000045440578
Score for class [1] =  0.0038458686
Score for class [2] =  0.0001249467
Score for class [3] =  0.0011804511
Score for class [4] =  0.00131694
Dropping TensorFromOrt.
Dropping the session.
Dropping the memory information.
Dropping the environment.

See also the integration tests (onnxruntime/tests/integration_tests.rs) that performs simple model download and inference, validating the results.

Bindings Generation

Bindings (the basis of onnxruntime-sys) are committed to the git repository. This means bindgen is not a dependency anymore on every build (it was made optional) and thus build times are better.

To generate new bindings (for example if they don't exists for your platform or if a version bump occurred), build the crate with the generate-bindings feature.

NOTE: Make sure to have the rustfmt rustup component present so that bindings are formatted:

rustup component add rustfmt

Then on each platform build with the proper feature flag:

❯ cd onnxruntime-sys
❯ cargo build --features generate-bindings

Generating Bindings for Linux With Docker

Prepare the container:

❯ docker run -it --rm --name rustbuilder -v "$PWD":/usr/src/myapp -w /usr/src/myapp rust:1.47.0 /bin/bash
❯ apt-get update
❯ apt-get install clang
❯ rustup component add rustfmt

Generate the bindings:

❯ docker exec -it --user "$(id -u)":"$(id -g)" rustbuilder /bin/bash
❯ cd onnxruntime-sys
❯ cargo build --features generate-bindings

Generating Bindings for Windows With Vagrant

You can use nbigaouette/windows_vagrant_rust to provision a Windows VM that can build the project and generate the bindings.

Windows can build both x86 and x86_64 bindings:

❯ rustup target add i686-pc-windows-msvc x86_64-pc-windows-msvc
❯ cd onnxruntime-sys
❯ cargo build --features generate-bindings --target i686-pc-windows-msvc
❯ cargo build --features generate-bindings --target x86_64-pc-windows-msvc

Conduct

The Rust Code of Conduct shall be respected. For escalation or moderation issues please contact Nicolas (nbigaouette@gmail.com) instead of the Rust moderation team.

License

This project is licensed under either of

Apache License, Version 2.0, (LICENSE-APACHE or http://www.apache.org/licenses/LICENSE-2.0)
MIT license (LICENSE-MIT or http://opensource.org/licenses/MIT)

at your option.

dllu/onnxruntime-rs