==============================================================================*/

#include "tensorflow/compiler/mlir/lite/experimental/tac/transforms/device_transform.h"

#include <string>
#include <utility>

#include "llvm/ADT/SmallVector.h"
#include "llvm/Support/Casting.h"
#include "mlir/Dialect/Func/IR/FuncOps.h"  // from @llvm-project
#include "mlir/Dialect/Quant/QuantTypes.h"  // from @llvm-project
#include "mlir/IR/BuiltinTypes.h"  // from @llvm-project

  auto fn = getOperation();
  OpBuilder builder(fn.getContext());

  absl::flat_hash_set<std::string> target_op_names(target_ops_.begin(),
                                                   target_ops_.end());

  llvm::SmallVector<Operation *, 4> custom_ops;
  fn.walk([&](Operation *op) {
    // Skips already imported ops that are imported as CustomTfOp.
    if (op->getParentOfType<CustomTfOp>()) return;

limitations under the License.
==============================================================================*/

#include <vector>

#include "llvm/ADT/STLExtras.h"
#include "llvm/ADT/SmallVector.h"
#include "llvm/ADT/StringRef.h"
#include "llvm/Support/Casting.h"
#include "llvm/Support/CommandLine.h"
#include "llvm/Support/InitLLVM.h"
#include "llvm/Support/PrettyStackTrace.h"
#include "llvm/Support/Regex.h"

#ifndef TENSORFLOW_COMPILER_MLIR_TENSORFLOW_TRANSFORMS_CONSTANT_FOLD_H_
#define TENSORFLOW_COMPILER_MLIR_TENSORFLOW_TRANSFORMS_CONSTANT_FOLD_H_

#include "llvm/ADT/ArrayRef.h"
#include "llvm/ADT/SmallVector.h"
#include "mlir/IR/Attributes.h"  // from @llvm-project
#include "mlir/IR/Operation.h"  // from @llvm-project
#include "mlir/Support/LogicalResult.h"  // from @llvm-project

namespace mlir {
namespace TF {

#include "absl/status/status.h"
#include "absl/status/statusor.h"
#include "absl/strings/str_cat.h"
#include "absl/strings/string_view.h"
#include "llvm/ADT/ArrayRef.h"
#include "llvm/ADT/SmallVector.h"
#include "llvm/Support/SourceMgr.h"
#include "mlir/IR/BuiltinOps.h"  // from @llvm-project
#include "mlir/IR/Diagnostics.h"  // from @llvm-project
#include "mlir/IR/MLIRContext.h"  // from @llvm-project

                                       llvm::SmallVector<Value>& outputs);

  // Given a translated function with a single return value, unpack the tuple
  // results.
  mlir::LogicalResult UnpackTupleResults(mhlo::TupleOp tuple_result,
                                         llvm::SmallVector<Value>& outputs);

  // Tries to legalize the specified TensorFlow op, if supported.
  //

limitations under the License.
==============================================================================*/

#include <algorithm>
#include <cstdint>
#include <memory>
#include <utility>

#include "llvm/ADT/SmallVector.h"
#include "llvm/Support/Casting.h"
#include "mlir/Dialect/Arith/IR/Arith.h"  // from @llvm-project
#include "mlir/Dialect/Func/IR/FuncOps.h"  // from @llvm-project
#include "mlir/IR/Attributes.h"  // from @llvm-project

  // Indices of additional arguments that will be forwarded to the fused
  // operation (e.g. forward bias vector if fusing BiasAdd operation).
  SmallVector<int, 4> additional_arguments;

  // Add additional attributes to the fused node.
  SmallVector<NamedAttribute, 4> additional_attributes;
};

//===----------------------------------------------------------------------===//
// TensorFlow Resource Handles.

  llvm::SmallVector<mlir::tf_device::ClusterFuncOp, 4> cluster_func_ops;
  module->walk([&](mlir::tf_device::ClusterFuncOp cluster_func) {
    cluster_func_ops.push_back(cluster_func);
  });
  EXPECT_EQ(cluster_func_ops.size(), 1);

  EXPECT_TRUE(mlir::succeeded(tensorflow::EraseClusterFuncs(cluster_func_ops)));

  llvm::SmallVector<mlir::tf_device::ClusterFuncOp, 4> new_cluster_func_ops;

    return;
  }

  OpBuilder builder(func);
  FunctionType func_type = func.getFunctionType();
  llvm::SmallVector<Type, 4> new_input_types(func_type.getInputs().begin(),
                                             func_type.getInputs().end());
  llvm::SmallVector<Type, 4> new_output_types(func_type.getResults().begin(),
                                              func_type.getResults().end());