22004a7368
Hard refactor — no shims, no compat layers. Candle removed from Cargo.toml and all source files in 6 crates: - ml-core: MlDevice enum, checkpoint.rs (safetensors direct), cudarc imports fixed from candle re-export to direct, AdamWConfig lr_decay, cuda_compat gutted. Net -7,341 lines. - ml-ppo: All 16 files rewritten. LSTM→CudaLSTM, VarMap→GpuVarStore, PPOAgent 2306→700 lines, checkpoint→binary format. - ml-ensemble: GPU-resident sigmoid via custom CUDA kernel. - ml-explainability: Integrated gradients via GPU finite-difference kernels. - ml-labeling: Device→MlDevice. - ml-hyperopt: Cargo.toml only. Remaining: ml-dqn (24 files), ml-supervised (4 files), ml crate (104 files). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
68 lines
2.1 KiB
Rust
68 lines
2.1 KiB
Rust
//! Error types for ML models crate - unified with CommonError
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use common::error::CommonError;
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/// `Result` type alias for ML models operations - updated to use CommonError
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pub type MLResult<T> = Result<T, CommonError>;
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/// `Result` type alias for model operations
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pub type ModelResult<T> = Result<T, CommonError>;
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/// Convert a framework computation error to CommonError
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///
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/// Accepts any `Display` error type (cudarc, etc.) and wraps it
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/// as an ML computation error.
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pub fn computation_error_to_common_error<E: std::fmt::Display>(err: E) -> CommonError {
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CommonError::ml(
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"computation",
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format!("ML computation error: {}", err),
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)
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}
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/// Create an ML training error
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pub fn ml_training_error(message: &str, model: Option<String>) -> CommonError {
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CommonError::ml(
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"training",
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format!("ML training error: {} (model: {:?})", message, model),
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)
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}
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/// Create an ML inference error
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pub fn ml_inference_error(message: &str, model: Option<String>) -> CommonError {
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CommonError::ml(
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"inference",
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format!("ML inference error: {} (model: {:?})", message, model),
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)
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}
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/// Create an ML validation error
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pub fn ml_validation_error(field: &str, message: &str) -> CommonError {
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CommonError::validation(format!(
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"ML validation error in field '{}': {}",
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field, message
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))
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}
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#[cfg(test)]
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mod tests {
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use super::*;
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#[test]
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fn test_ml_error_creation() {
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let inference_error =
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ml_inference_error("Test inference error", Some("test_model".to_owned()));
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let error_str = inference_error.to_string();
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assert!(error_str.contains("Test inference error"));
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assert!(error_str.contains("test_model"));
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let training_error = ml_training_error("Test training error", None);
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let error_str = training_error.to_string();
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assert!(error_str.contains("Test training error"));
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let validation_error = ml_validation_error("input", "Invalid input shape");
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let error_str = validation_error.to_string();
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assert!(error_str.contains("input"));
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assert!(error_str.contains("Invalid input shape"));
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}
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}
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