[TORCH][MLIR] Added _sdpa_flash_attention op

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

@@ -15193,6 +15193,43 @@ def Torch_AtenScaledDotProductAttentionOp : Torch_Op<"aten.scaled_dot_product_at
   }];
 }
 
+def Torch_AtenScaledDotProductFlashAttentionOp : Torch_Op<"aten._scaled_dot_product_flash_attention", [
+    AllowsTypeRefinement,
+    HasValueSemantics,
+    ReadOnly
+  ]> {
+  let summary = "Generated op for `aten::_scaled_dot_product_flash_attention(Tensor, Tensor, Tensor, float, bool, bool, float?) -> (Tensor, Tensor, Tensor, Tensor, SymInt, SymInt, Tensor, Tensor, Tensor)`";
+  let arguments = (ins
+    AnyTorchTensorType:$query,
+    AnyTorchTensorType:$key,
+    AnyTorchTensorType:$value,
+    Torch_FloatType:$dropout_p,
+    Torch_BoolType:$is_causal,
+    Torch_BoolType:$return_debug_mask,
+    AnyTorchOptionalFloatType:$scale
+  );
+  let results = (outs
+    AnyTorchOptionalTensorType:$output,
+    AnyTorchOptionalTensorType:$logsumexp,
+    AnyTorchOptionalTensorType:$cum_seq_q,
+    AnyTorchOptionalTensorType:$cum_seq_k,
+    Torch_IntType:$max_q,
+    Torch_IntType:$max_k,
+    AnyTorchOptionalTensorType:$rng_state,
+    AnyTorchOptionalTensorType:$unused,
+    AnyTorchOptionalTensorType:$debug_attn_mask
+  );
+  let hasCustomAssemblyFormat = 1;
+  let extraClassDefinition = [{
+    ParseResult AtenScaledDotProductFlashAttentionOp::parse(OpAsmParser &parser, OperationState &result) {
+      return parseDefaultTorchOp(parser, result, 7, 9);
+    }
+    void AtenScaledDotProductFlashAttentionOp::print(OpAsmPrinter &printer) {
+      printDefaultTorchOp(printer, *this, 7, 9);
+    }
+  }];
+}
+
 def Torch_AtenGridSamplerOp : Torch_Op<"aten.grid_sampler", [
     AllowsTypeRefinement,
     HasValueSemantics,

projects/pt1/python/torch_mlir/jit_ir_importer/build_tools/torch_ods_gen.py

@@ -29,6 +29,7 @@
     "int[]": "AnyTorchListOfTorchIntType",
     "int?": "AnyTorchOptionalIntType",
     "int[]?": "AnyTorchOptionalListOfTorchIntType",
+    "SymInt": "Torch_IntType",
     "bool": "Torch_BoolType",
     "bool[]": "AnyTorchListOfTorchBoolType",
     "bool?": "AnyTorchOptionalBoolType",
@@ -1087,9 +1088,14 @@ def emit_with_mutating_variants(key, **kwargs):
         "aten::upsample_bilinear2d : (Tensor, int[], bool, float?, float?) -> (Tensor)"
     )
     emit("aten::upsample_bilinear2d.vec : (Tensor, int[]?, bool, float[]?) -> (Tensor)")
+
+    # Attention ops.
     emit(
         "aten::scaled_dot_product_attention : (Tensor, Tensor, Tensor, Tensor?, float, bool, float?, bool) -> (Tensor)"
     )
+    emit(
+        "aten::_scaled_dot_product_flash_attention(Tensor, Tensor, Tensor, float, bool, bool, float?) -> (Tensor, Tensor, Tensor, Tensor, SymInt, SymInt, Tensor, Tensor, Tensor)"
+    )
     emit("aten::grid_sampler : (Tensor, Tensor, int, int, bool) -> (Tensor)")
     emit(
         "aten::_trilinear : (Tensor, Tensor, Tensor, int[], int[], int[], int[], int) -> (Tensor)"