5e50c50336
The ml crate fix alone wasn't enough — ml-core, ml-dqn, ml-ppo, ml-supervised, ml-ensemble, ml-explainability, ml-hyperopt, and ml-labeling all had `default = ["cuda"]`, each independently pulling in cudarc via candle-core/cuda. Now `default = []` on all sub-crates. CUDA activates only when the compile-and-train template passes `--features ml/cuda`, which propagates through ml's cuda feature gate to all sub-crates. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
41 lines
920 B
TOML
41 lines
920 B
TOML
[package]
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name = "ml-labeling"
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version.workspace = true
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edition.workspace = true
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rust-version.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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homepage.workspace = true
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documentation.workspace = true
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publish.workspace = true
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keywords.workspace = true
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categories.workspace = true
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description = "ML labeling algorithms for Foxhunt HFT training data"
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[features]
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default = []
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cuda = ["candle-core/cuda"]
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[dependencies]
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ml-core.workspace = true
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# ML frameworks (gpu_acceleration.rs uses candle tensors)
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candle-core = { git = "https://github.com/huggingface/candle", rev = "671de1db" }
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# Serialization
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serde = { workspace = true, features = ["derive"] }
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# Core utilities
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tracing.workspace = true
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uuid.workspace = true
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# Concurrency
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dashmap = { workspace = true }
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[dev-dependencies]
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tokio = { workspace = true, features = ["test-util", "macros"] }
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[lints]
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workspace = true
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