rob thijssen
96d8755245
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Two follow-up cuda-only fixes surfaced by `cargo build --features cuda`
inside the cuda-13.0 runner container:
1. `half::{bf16, f16}` was an undeclared dep. Added `half = "2.5"`
(matching candle-core's pinned major) under the cuda feature flag.
2. `dev.alloc::<T>(n)` already returns `candle_core::Result` (it calls
`.w()` internally on the cudarc error). Calling `.w()?` on top of
that needs `From<candle_core::Error> for CudaError`, which doesn't
exist — collapse to `?`. Removed the now-unused
`cuda_backend::WrapErr` import.
Verified by `cargo build -p neuron --features cuda` and
`cargo clippy -p neuron --all-targets --features cuda -- -D warnings`
inside `git.lair.cafe/gongfoo/runner-cuda-13.0` with the local
glibc/CUDA-13.0 math_functions.h noexcept patch. CPU clippy/tests stay
green.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
82 lines
2.4 KiB
TOML
82 lines
2.4 KiB
TOML
[package]
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name = "neuron"
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version.workspace = true
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edition.workspace = true
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license.workspace = true
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[lib]
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name = "neuron"
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path = "src/lib.rs"
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[[bin]]
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name = "neuron"
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path = "src/main.rs"
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[features]
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default = []
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# Enables CUDA acceleration in candle and the cudarc/nccl bindings the
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# TP worker pool uses. Without this feature, candle compiles for CPU
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# only, Device::new_cuda calls fall back to CPU, and TP Init/sanity
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# requests return Error{kind="cuda_feature_not_enabled"}.
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cuda = [
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"candle-core/cuda",
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"candle-core/nccl",
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"candle-nn/cuda",
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"candle-transformers/cuda",
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"dep:cudarc",
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"dep:half",
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]
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# Use cuDNN for convolution / attention kernels. Requires CUDA.
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cudnn = [
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"cuda",
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"candle-core/cudnn",
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"candle-nn/cudnn",
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"candle-transformers/cudnn",
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]
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# FlashAttention kernels. Requires CUDA.
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flash-attn = [
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"cuda",
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"candle-transformers/flash-attn",
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]
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# Reserved for GPU-only integration tests in later stages.
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cuda-integration = ["cuda"]
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[dependencies]
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cortex-core.workspace = true
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tokio.workspace = true
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axum.workspace = true
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serde.workspace = true
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serde_json.workspace = true
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reqwest.workspace = true
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tracing.workspace = true
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tracing-subscriber.workspace = true
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anyhow.workspace = true
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async-trait.workspace = true
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clap.workspace = true
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thiserror.workspace = true
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futures.workspace = true
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tokio-stream.workspace = true
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figment.workspace = true
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toml.workspace = true
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# candle for in-process inference. CUDA support is gated behind the
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# crate's `cuda` feature (default off) so the workspace builds on
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# non-CUDA hosts and CI runners.
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candle-core = "0.10.2"
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candle-nn = "0.10.2"
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candle-transformers = "0.10.2"
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# Direct dep on cudarc (matching candle's transitive version) so the
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# TP worker pool can call cudarc::nccl::{Comm, Id} directly. Gated on
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# the `cuda` feature; same toolchain requirement as candle's CUDA path.
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cudarc = { version = "0.19", optional = true, default-features = false, features = ["nccl", "cuda-version-from-build-system"] }
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# Used by the AllReduce CustomOp1 to type-dispatch on bf16/f16 candle
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# storages. Matches candle-core's pinned major version to avoid double-
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# compiling the `half` crate at conflicting versions.
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half = { version = "2.5", optional = true }
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tokenizers = { version = "0.22", default-features = false, features = ["onig"] }
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hf-hub = { version = "0.4", features = ["tokio"] }
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[dev-dependencies]
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tokio = { workspace = true, features = ["test-util"] }
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reqwest.workspace = true
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