mirror of
https://github.com/ruvnet/RuView
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ruv
5cacb5fe0a
- onnx.rs ORT input: arr.as_slice() single-memcpy fast path with iterator fallback for strided views. MEASURED [1,256,64,64]: 1.972ms -> 1.336ms (~1.48x). Repro: cargo bench -p wifi-densepose-nn --no-default-features --features onnx --bench onnx_bench -- onnx_input_copy - onnx.rs checked_output_dims: reject ONNX dim <= 0 (incl. unresolved -1) before allocation (config-OOM class) + test. - onnx_concurrency bench: empirically proves the per-inference write lock serializes (throughput drops with more threads). The intended read-lock win is NOT landable on ort 2.0.0-rc.11 (safe Session::run is &mut self, verified) and is deferred to the backlog with the upgrade path documented in-code. New committed fixture tests/fixtures/tiny_conv.onnx (666 B, not gitignored). Co-Authored-By: claude-flow <ruv@ruv.net>
66 lines
1.5 KiB
TOML
66 lines
1.5 KiB
TOML
[package]
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name = "wifi-densepose-nn"
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version.workspace = true
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edition.workspace = true
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authors.workspace = true
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license.workspace = true
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repository.workspace = true
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documentation.workspace = true
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keywords = ["neural-network", "onnx", "inference", "densepose", "deep-learning"]
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categories = ["science", "computer-vision"]
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description = "Neural network inference for WiFi-DensePose pose estimation"
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readme = "README.md"
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[features]
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default = ["onnx"]
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onnx = ["ort"]
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tch-backend = ["tch"]
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candle-backend = ["candle-core", "candle-nn"]
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cuda = ["onnx"]
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tensorrt = ["onnx"]
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all-backends = ["onnx", "tch-backend", "candle-backend"]
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[dependencies]
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# Core utilities
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thiserror.workspace = true
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anyhow.workspace = true
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serde.workspace = true
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serde_json.workspace = true
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tracing.workspace = true
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# Tensor operations
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ndarray.workspace = true
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num-traits.workspace = true
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# ONNX Runtime (default)
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ort = { workspace = true, optional = true }
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# PyTorch backend (optional)
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tch = { workspace = true, optional = true }
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# Candle backend (optional)
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candle-core = { workspace = true, optional = true }
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candle-nn = { workspace = true, optional = true }
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# Async runtime
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tokio = { workspace = true, features = ["sync", "rt"] }
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# Additional utilities
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parking_lot = "0.12"
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memmap2 = "0.9"
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[dev-dependencies]
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criterion.workspace = true
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proptest.workspace = true
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tokio = { workspace = true, features = ["rt-multi-thread", "macros"] }
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tempfile = "3.10"
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[[bench]]
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name = "inference_bench"
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harness = false
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[[bench]]
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name = "onnx_bench"
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harness = false
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required-features = ["onnx"]
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