116 lines
3.0 KiB
TOML
116 lines
3.0 KiB
TOML
[package]
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name = "rtx-inference"
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version = "1.0.0"
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edition.workspace = true
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rust-version = "1.92"
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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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[dependencies]
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# Workspace dependencies
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rtx-runtime = { path = "../../core/rtx-runtime" }
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rtx-tensor = { path = "../../core/rtx-tensor", features = ["cpu"] }
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rtx-synthesis = { path = "../../specialized/rtx-synthesis" }
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# ONNX Runtime integration (optional)
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rtx-onnx = { path = "../rtx-onnx", optional = true }
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# Burn ML framework integration (optional)
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rtx-burn = { path = "../../integration/rtx-burn", optional = true }
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# Candle ML framework integration (optional)
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rtx-candle = { path = "../../integration/rtx-candle", optional = true }
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# Error handling
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anyhow.workspace = true
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thiserror.workspace = true
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# Async runtime for request handling
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tokio = { workspace = true, features = ["full", "time", "rt-multi-thread"] }
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async-trait.workspace = true
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# Serialization for request/response
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serde = { workspace = true, features = ["derive"] }
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serde_json.workspace = true
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# Concurrent data structures for request queues and KV cache
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parking_lot.workspace = true
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crossbeam.workspace = true
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dashmap.workspace = true
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# UUID for request tracking
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uuid = { version = "1.0", features = ["v4", "serde"] }
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# For build-time metadata
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once_cell = "1.19"
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# Configuration management
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config.workspace = true
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# Logging and telemetry
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tracing.workspace = true
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tracing-subscriber.workspace = true
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# Performance monitoring
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criterion.workspace = true
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# Quantization support (commented out for testing)
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# cudarc.workspace = true
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# Mathematical operations for cache statistics (commented out for testing)
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# nalgebra.workspace = true
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# Threading for batch processing
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rayon.workspace = true
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# Temporary files for model caching (commented out for testing)
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# tempfile.workspace = true
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# Hashing for cache keys (commented out for testing)
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# sha2 = "0.10"
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# Pattern matching for kernel selection (commented out for testing)
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# regex = "1.0"
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# Random number generation for testing
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fastrand = "2.0"
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# Streaming support
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tokio-stream = "0.1"
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futures = "0.3"
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# Zip archive support for PyTorch file parsing
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zip = "2.2"
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# Byte order handling for binary formats
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byteorder = "1.5"
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[dev-dependencies]
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proptest.workspace = true
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tokio-test = "0.4"
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[build-dependencies]
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chrono = { version = "0.4", features = ["serde"] }
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[features]
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default = []
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metrics = ["tracing-subscriber/env-filter"]
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# ONNX Runtime support for high-performance inference
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onnx-runtime = ["rtx-onnx"]
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# ONNX Runtime with CUDA support
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onnx-cuda = ["onnx-runtime", "rtx-onnx/cuda"]
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# ONNX Runtime with CoreML support (macOS)
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onnx-coreml = ["onnx-runtime", "rtx-onnx/coreml"]
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# ONNX Runtime with TensorRT support
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onnx-tensorrt = ["onnx-runtime", "rtx-onnx/tensorrt"]
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# Burn ML framework support
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burn = ["rtx-burn"]
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burn-wgpu = ["burn", "rtx-burn/wgpu"]
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# Candle ML framework support
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candle = ["rtx-candle"]
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candle-cuda = ["candle", "rtx-candle/cuda"]
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candle-metal = ["candle", "rtx-candle/metal"]
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[lints]
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workspace = true
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