cleanup(fflag): delete 7 dead transformer flags — [FFLAG-016, FFLAG-017]

HFTTransformerConfig had seven write-only bool flags with zero conditional
readers anywhere in the workspace:
- FFLAG-017: use_market_microstructure, use_order_book_features,
  use_trade_flow_features
- FFLAG-016: use_flash_attention, use_sparse_attention, use_cuda_graphs,
  enable_profiling

Each was declared + defaulted + asserted in tests, but no code branched on
them. Deleted all 7 fields + Default init + production()/benchmark() setters
+ test assertions. Per feedback_no_feature_flags.md these were aspirational
knobs — the features they nominally gated have no implementation.
This commit is contained in:
jgrusewski
2026-04-20 22:45:51 +02:00
parent e2a84c90c4
commit 3f4fa33b9b

View File

@@ -117,13 +117,8 @@ pub struct HFTTransformerConfig {
/// Feature configuration
pub feature_dim: usize,
pub use_market_microstructure: bool,
pub use_order_book_features: bool,
pub use_trade_flow_features: bool,
/// Optimization settings
pub use_flash_attention: bool,
pub use_sparse_attention: bool,
pub attention_sparsity: f32,
/// Memory optimization
@@ -132,8 +127,6 @@ pub struct HFTTransformerConfig {
/// Hardware settings
pub device_type: DeviceType,
pub use_cuda_graphs: bool,
pub enable_profiling: bool,
}
impl Default for HFTTransformerConfig {
@@ -147,17 +140,10 @@ impl Default for HFTTransformerConfig {
ff_dim: 256,
seq_len: 64,
feature_dim: 32,
use_market_microstructure: true,
use_order_book_features: true,
use_trade_flow_features: true,
use_flash_attention: true,
use_sparse_attention: false,
attention_sparsity: 0.1,
pre_allocate_tensors: true,
memory_pool_size: 1024 * 1024 * 64, // 64MB
device_type: DeviceType::Cuda,
use_cuda_graphs: false, // Enable after validation
enable_profiling: false,
}
}
}
@@ -209,19 +195,14 @@ impl HFTTransformerConfig {
/// Enable all optimizations for production deployment
pub fn production() -> Self {
Self {
use_flash_attention: true,
pre_allocate_tensors: true,
use_cuda_graphs: true,
..Self::micro()
}
}
/// Configuration for benchmarking and validation
pub fn benchmark() -> Self {
Self {
enable_profiling: true,
..Self::micro()
}
Self::micro()
}
}
@@ -252,8 +233,6 @@ mod tests {
assert_eq!(nano.hidden_dim, 32);
let production = HFTTransformerConfig::production();
assert!(production.use_flash_attention);
assert!(production.pre_allocate_tensors);
assert!(production.use_cuda_graphs);
}
}