refactor(ml): use canonical DeviceConfig from gpu module in Liquid CfC

Replace local DeviceConfig enum definition in liquid/candle_cfc.rs with
a re-export from the central crate::gpu::DeviceConfig, eliminating
duplication while preserving all existing API and tests.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

ml/src/liquid/candle_cfc.rs

@@ -11,29 +11,8 @@ use serde::{Deserialize, Serialize};
 use crate::cuda_compat::manual_sigmoid;
 use crate::MLError;
 
-/// Device configuration for CfC training
-#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
-pub enum DeviceConfig {
-    Cpu,
-    Cuda(usize),
-    Auto,
-}
-
-impl DeviceConfig {
-    pub fn resolve(&self) -> Result<Device, MLError> {
-        match self {
-            DeviceConfig::Cpu => Ok(Device::Cpu),
-            DeviceConfig::Cuda(id) => Device::new_cuda(*id).map_err(|e| {
-                MLError::ConfigurationError(format!(
-                    "CUDA device {} required but unavailable: {}",
-                    id, e
-                ))
-            }),
-            DeviceConfig::Auto => Device::cuda_if_available(0)
-                .map_err(|e| MLError::ConfigurationError(format!("Auto device error: {}", e))),
-        }
-    }
-}
+/// Device configuration for CfC training — re-exported from central gpu module.
+pub use crate::gpu::DeviceConfig;
 
 /// CfC v2 training configuration
 ///