Formatting

Signed-off-by: Keshav Vinayak Jha <[email protected]>

Author: keshavvinayak01

include/torch-mlir/Dialect/Torch/IR/TorchOps.td

@@ -1450,10 +1450,10 @@ def Torch_AtenFlexAttentionOp : Torch_Op<"aten.flex_attention", [
   let summary = "Generated op for `aten::flex_attention`";
   let description = [{
     FlexAttention operation with flexible block-sparse attention patterns.
-    
+
     Args:
       query: Query tensor [B, H, M, K]
-      key: Key tensor [B, H, N, K]  
+      key: Key tensor [B, H, N, K]
       value: Value tensor [B, H, N, Ev]
       scale: Optional float for scaling attention scores (None means 1/sqrt(head_dim))
       enable_gqa: Boolean for grouped query attention support
@@ -1462,14 +1462,14 @@ def Torch_AtenFlexAttentionOp : Torch_Op<"aten.flex_attention", [
     Attributes:
       score_mod_fn: Optional function symbol reference for score modification
       mask_mod_fn: Optional function symbol reference for mask modification
-      
+
     TODO: kernel_options: Dict attributes for performance tuning (block_size, num_warps, etc.)
 
     Returns:
       output: Result tensor [B, H, M, Ev]
       logsumexp: Optional log-sum-exp tensor [B, H, M] (if return_lse=True)
   }];
-  
+
   let arguments = (ins
     AnyTorchTensorType:$query,
     AnyTorchTensorType:$key,
@@ -1480,12 +1480,12 @@ def Torch_AtenFlexAttentionOp : Torch_Op<"aten.flex_attention", [
     OptionalAttr<FlatSymbolRefAttr>:$score_mod_fn,
     OptionalAttr<FlatSymbolRefAttr>:$mask_mod_fn
   );
-  
+
   let results = (outs
     AnyTorchTensorType:$output,
     AnyTorchOptionalTensorType:$logsumexp
   );
-  
+
   let hasCustomAssemblyFormat = 1;
   let extraClassDefinition = [{
     ParseResult AtenFlexAttentionOp::parse(OpAsmParser &parser, OperationState &result) {