feat: DQN data loader checks .fxcache before DBN streaming

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

crates/ml/src/trainers/dqn/data_loading.rs

@@ -596,6 +596,57 @@ impl DQNTrainer {
         Vec<(FeatureVector, Vec<f64>)>,
         Vec<(FeatureVector, Vec<f64>)>,
     )> {
+        // ── .fxcache (flat binary feature cache) — fastest path ──────────────
+        if let Some(ref cache_dir) = self.feature_cache_dir {
+            let data_dir_path = Path::new(dbn_data_dir);
+            let mbp10_dir = self.hyperparams.mbp10_data_dir.as_ref().map(|s| Path::new(s.as_str()));
+            let trades_dir = self.hyperparams.trades_data_dir.as_ref().map(|s| Path::new(s.as_str()));
+
+            if let Ok(cache_key_hex) = crate::feature_cache::calculate_dbn_cache_key_full(
+                data_dir_path,
+                mbp10_dir,
+                trades_dir,
+            ) {
+                if let Ok(key_bytes) = hex::decode(&cache_key_hex) {
+                    if let Ok(key) = <[u8; 32]>::try_from(key_bytes) {
+                        if let Some(fxcache_path) = crate::fxcache::find_fxcache(cache_dir, &key) {
+                            match crate::fxcache::load_fxcache(&fxcache_path) {
+                                Ok(cached) => {
+                                    info!(
+                                        "fxcache hit: {} bars from {:?}",
+                                        cached.bar_count, fxcache_path
+                                    );
+
+                                    // Set OFI features from cache
+                                    let has_ofi = cached.ofi.iter().any(|o| o.iter().any(|&v| v != 0.0));
+                                    if has_ofi {
+                                        self.ofi_features = Some(Arc::from(cached.ofi));
+                                    }
+
+                                    // Combine features + targets
+                                    let all_data: Vec<([f64; 42], Vec<f64>)> = cached
+                                        .features
+                                        .into_iter()
+                                        .zip(cached.targets.into_iter())
+                                        .map(|(f, t)| (f, t.to_vec()))
+                                        .collect();
+
+                                    // 80/20 split (same as other cache paths)
+                                    let split = (all_data.len() * 80) / 100;
+                                    let train = all_data[..split].to_vec();
+                                    let val = all_data[split..].to_vec();
+                                    return Ok((train, val));
+                                }
+                                Err(e) => {
+                                    debug!("fxcache load failed: {e}, falling through");
+                                }
+                            }
+                        }
+                    }
+                }
+            }
+        }
+
         // ── DBN feature cache (dev/test speedup) ──────────────────────────────
         // Check for a previously computed and serialised training dataset.
         // The cache is keyed on all .dbn/.dbn.zst filenames + sizes + mtimes so