style: cargo fmt --workspace (whitespace/wrapping only, no semantic change)

Whole-workspace rustfmt pass picked up while iterating on Mamba GPU backward work. Verified formatting-only via diff sampling; no logic changed. Co-Authored-By: Claude Sonnet 5 <[email protected]>
2026-08-10 07:09:36 -07:00
parent ad6405663f
commit 4aaa36a57a
305 changed files with 25537 additions and 18337 deletions
@@ -4,20 +4,22 @@
 //! supporting both homogeneous and heterogeneous graphs with batch processing.

 use crate::Result;
-use rtx_tensor::{Tensor, Device};
+use rtx_tensor::{Device, Tensor};

-pub mod graph_transformer_simple;
 pub mod graph_attention_simple;
 pub mod graph_pooling_simple;
+pub mod graph_transformer_simple;
 pub mod positional_encoding_simple;

 #[cfg(all(test, feature = "disabled_tests"))]
 pub mod graph_transformer_tests;

-pub use graph_transformer_simple::{GraphTransformer, GraphTransformerConfig, GraphOutput};
-pub use graph_attention_simple::{GraphAttention, GraphAttentionConfig, AttentionOutput};
-pub use graph_pooling_simple::{GraphPooling, GlobalPooling, HierarchicalPooling, Set2SetPooling, AttentionPooling};
-pub use positional_encoding_simple::{GraphPositionalEncoding, GraphPEConfig, GraphPEType};
+pub use graph_attention_simple::{AttentionOutput, GraphAttention, GraphAttentionConfig};
+pub use graph_pooling_simple::{
+    AttentionPooling, GlobalPooling, GraphPooling, HierarchicalPooling, Set2SetPooling,
+};
+pub use graph_transformer_simple::{GraphOutput, GraphTransformer, GraphTransformerConfig};
+pub use positional_encoding_simple::{GraphPEConfig, GraphPEType, GraphPositionalEncoding};

 /// Graph data structure for batch processing
 #[derive(Debug, Clone)]
@@ -46,7 +48,7 @@ impl GraphBatch {
        device: Device,
    ) -> Result<Self> {
        let batch_size = graph_boundaries.len().saturating_sub(1);
-        
+
        Ok(Self {
            node_features,
            edge_features,
@@ -56,17 +58,17 @@ impl GraphBatch {
            device,
        })
    }
-    
+
    /// Get the number of nodes in the batch
    pub fn num_nodes(&self) -> usize {
        self.node_features.shape().dims()[0]
    }
-    
+
    /// Get the number of edges in the batch
    pub fn num_edges(&self) -> usize {
        self.edge_features.shape().dims()[0]
    }
-    
+
    /// Check if batch is homogeneous (all graphs have same structure)
    pub fn is_homogeneous(&self) -> bool {
        // For now, assume heterogeneous - can be optimized later
@@ -115,16 +117,16 @@ pub enum PoolingStrategy {
 pub trait GraphLayer: Send + Sync {
    /// Forward pass through the graph layer
    fn forward(&self, graph: &GraphBatch) -> Result<GraphOutput>;
-    
+
    /// Get the layer type name
    fn layer_type(&self) -> &'static str;
-    
+
    /// Get the device this layer is on
    fn device(&self) -> &Device;
-    
+
    /// Get layer parameters for optimization
    fn parameters(&self) -> Vec<&Tensor>;
-    
+
    /// Get mutable layer parameters for optimization
    fn parameters_mut(&mut self) -> Vec<&mut Tensor>;
-}
+}