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>
44 lines
1.1 KiB
TOML
44 lines
1.1 KiB
TOML
[package]
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name = "ml-hyperopt"
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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 hyperparameter optimization — PSO, TPE, campaigns, sensitivity analysis"
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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 = { path = "../ml-core", default-features = false }
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common.workspace = true
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candle-core = { git = "https://github.com/huggingface/candle", rev = "671de1db" }
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serde = { workspace = true, features = ["derive"] }
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serde_json.workspace = true
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chrono.workspace = true
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tracing.workspace = true
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anyhow.workspace = true
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rand.workspace = true
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rand_distr.workspace = true
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ndarray = { workspace = true, features = ["rayon"] }
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rayon.workspace = true
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statrs.workspace = true
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argmin = { version = "0.8", features = ["rayon"] }
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argmin-math = "0.3"
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[dev-dependencies]
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tokio = { workspace = true, features = ["test-util", "macros"] }
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rand_chacha = "0.3"
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approx = "0.5"
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[lints]
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workspace = true
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