9c3d741a08
Move 17 library crates into crates/, CLI binary into bin/fxt, consolidate 10 test crates into testing/, split config crate from deployment config files. Root directory reduced from 38+ to ~17 directories. All Cargo.toml paths and build.rs proto refs updated. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
67 lines
2.2 KiB
Rust
67 lines
2.2 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 candle error to CommonError
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///
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/// Cannot implement `From<candle_core::Error>` for CommonError due to orphan rule.
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/// Use this function to convert candle errors when needed.
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pub fn candle_error_to_common_error(err: candle_core::Error) -> CommonError {
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CommonError::ml(
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"candle_computation",
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format!("Candle 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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