}
                }
                MethodVisitorScope bridge = new MethodVisitorScopeImpl(
                    clazz.visitor.visitMethod(methodData.access, methodData.name, methodData.descriptor, methodData.signature, methodData.exceptions)
                );
                bridge.visitCode();
                bridge.visitEnd();
            }
            return original;
        }),

}

// Adds the list of ops that are only supported in the old bridge.
// TODO(b/168036682): Remove bounded dynamism ops now that MLIR bridge supports
// bounded dynamism.
// TODO(b/257574556): Remove the need for this manual list by making use of old
// bridge phase 2 op list.
void AddOldBridgeOnlyOps(MLIRContext* context,

#include "tensorflow/compiler/mlir/lite/stablehlo/transforms/tf_stablehlo_pass.h"
#include "tensorflow/compiler/mlir/quantization/stablehlo/cc/pass_pipeline.h"
#include "tensorflow/compiler/mlir/quantization/stablehlo/passes/bridge/passes.h"
#include "tensorflow/compiler/mlir/quantization/stablehlo/passes/passes.h"
#include "tensorflow/compiler/mlir/quantization/tensorflow/cc/run_passes.h"

  if (lower_to_xla_hlo) {
    // Legalize any StableHLO ops to MHLO. Bridge still doesn't use StableHLO
    // but such ops might be present in the input from upstream like TFRT
    // compilation. Later on, this could be merged in the legalization pass when
    // we migrate bridge to StableHLO.

    // TODO(b/259459405): Avoid this peculiar use through some refactoring in
    // the caller.

        "@llvm-project//mlir:Pass",
        "@llvm-project//mlir:Support",
        "@llvm-project//mlir:TransformUtils",
    ],
)

cc_library(
    name = "bridge",
    srcs = ["bridge.cc"],
    hdrs = ["bridge.h"],
    deps = [
        ":tensorflow_passes",
        "//tensorflow/compiler/mlir/tensorflow:dump_mlir_util",
        "//tensorflow/compiler/mlir/tensorflow:error_util",

      return failure();

    // Populate set_is_same_data_across_replicas
    // Note: this information is duplicated and can be removed from the proto
    // and here once MLIR bridge phase 2 doesn't fallback to the old bridge.
    auto attr = op.getFuncOp().getArgAttrOfType<mlir::BoolAttr>(
        index, replication_attr_name);
    arg->set_is_same_data_across_replicas(attr != nullptr && attr.getValue());

    bool use_tuple_args, bool use_resource_updates_for_aliases,
    const XlaShapeLayoutHelpers::ShapeDeterminationFns shape_determination_fns,
    XlaCompilationResult* compilation_result);

// Runs MLIR Bridge on a MLIR module.
//
// If lower_to_xla_hlo is true then compiles down into XLA HLO, generates all
// accompanying metadata and stores them in CompilationResult.
//

      TypeID::get<TF::ModOp>(),

      // MatrixDiagPartV3 should use the MLIR implementation due to performance.
      TypeID::get<TF::MatrixDiagPartV3Op>(),

      // Ops that are legalized in the old bridge using MlirXlaOpKernel
      TypeID::get<TF::AbsOp>(),
      TypeID::get<TF::AtanOp>(),
      TypeID::get<TF::AvgPool3DOp>(),
      TypeID::get<TF::BiasAddGradOp>(),
      TypeID::get<TF::CeilOp>(),

	"log/slog/internal"
	"runtime"
	"sync/atomic"
	"time"
)

var defaultLogger atomic.Pointer[Logger]

var logLoggerLevel LevelVar

// SetLogLoggerLevel controls the level for the bridge to the [log] package.
//
// Before [SetDefault] is called, slog top-level logging functions call the default [log.Logger].
// In that mode, SetLogLoggerLevel sets the minimum level for those calls.

}

def XlaValidateInputsPass : Pass<"tf-xla-validate-inputs", "ModuleOp"> {
  let summary = "Validtes inputs to the TF CPU/GPU bridge";
  let description = [{
    This pass checks that the IR has valid input to CPU/GPU TF/XLA bridge.
  }];
  let constructor = "TFDevice::CreateXlaValidateInputsPass()";
  let dependentDialects = ["tf_device::TensorFlowDeviceDialect"];