#include "tensorflow/core/platform/strcat.h"
#include "tensorflow/core/platform/stringpiece.h"
#include "tensorflow/core/platform/types.h"
#include "tensorflow/core/public/version.h"

namespace tensorflow {
namespace cc_op {
namespace {

string DefaultValue(OpDef_AttrDef attr) {
  static const auto* attr_default_value_map =
      new absl::flat_hash_map<StringPiece, StringPiece, StringPieceHasher>{
          {"int", "0"},

        "@llvm-project//mlir:IR",
        "@llvm-project//mlir:Parser",
        "//tensorflow/cc:array_ops",
        "//tensorflow/cc:function_ops",
        "//tensorflow/cc:functional_ops",
        "//tensorflow/cc:ops",
        "//tensorflow/cc:scope",
        "//tensorflow/cc:tpu_ops",
        "//tensorflow/compiler/mlir/tensorflow",
        "//tensorflow/compiler/tf2xla:tf2xla_defs",
        "//tensorflow/core:core_cpu_base",

def LegalizeCast : Pat<(TF_CastOp $arg0, BoolAttr:$arg1), (TFL_CastOp $arg0)>;

def LegalizeBatchToSpaceND : Pat<
  (TF_BatchToSpaceNDOp $input, $block_shape, $crops),
  (TFL_BatchToSpaceNdOp $input, (CreateTFCastToInt32Op $block_shape),
     (CreateTFCastToInt32Op $crops))>;

def LegalizeSpaceToBatchND : Pat<
  (TF_SpaceToBatchNDOp $input, $block_shape, $paddings),
  (TFL_SpaceToBatchNdOp $input, (CreateTFCastToInt32Op $block_shape),

#include "tensorflow/compiler/mlir/lite/utils/attribute_utils.h"
#include "tensorflow/compiler/mlir/lite/utils/constant_utils.h"
#include "tensorflow/compiler/mlir/lite/utils/validators.h"
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h"
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops_a_m.h"
#include "tensorflow/compiler/mlir/tensorflow/transforms/lower_tf.h"
#include "tensorflow/compiler/mlir/tensorflow/utils/mangling_util.h"
#include "xla/statusor.h"

      for (OpResult per_replica_result : replicated_output->getResults()) {
        auto [partitioned_output, id_ops] =
            GetSingleUserOfType<mlir::TF::TPUPartitionedOutputV2Op>(
                per_replica_result);
        if (partitioned_output) {
          erase_list.insert(erase_list.end(), id_ops.begin(), id_ops.end());
          partitioned_outputs[cluster_result_id].emplace_back(
              partitioned_output);

include "mlir/Dialect/Arith/IR/ArithOps.td"
include "mlir/Dialect/Func/IR/FuncOps.td"
include "mlir/Dialect/Shape/IR/ShapeOps.td"
include "mlir/IR/OpBase.td"
include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.td"
include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.td"
include "stablehlo/dialect/StablehloOps.td"
include "tensorflow/compiler/mlir/quantization/common/attrs_and_constraints.td"

	// Score each call site.
	var resultNameTab map[*ir.Name]resultPropAndCS
	for _, cs := range csl {
		var cprops *FuncProps
		fihcprops := false
		desercprops := false
		if funcInlHeur, ok := fpmap[cs.Callee]; ok {
			cprops = funcInlHeur.props
			fihcprops = true
		} else if cs.Callee.Inl != nil {
			cprops = DeserializeFromString(cs.Callee.Inl.Properties)
			desercprops = true
		} else {

#include "tensorflow/core/lib/io/path.h"
#include "tensorflow/core/platform/strcat.h"
#include "tensorflow/core/platform/types.h"
#include "tsl/platform/statusor.h"

namespace tensorflow {
namespace cc_op {

absl::StatusOr<ApiDefMap> LoadOpsAndApiDefs(
    OpList& ops, bool include_internal,
    const std::vector<string>& api_def_dirs) {
  OpRegistry::Global()->Export(include_internal, &ops);
  ApiDefMap api_def_map(ops);

#include "mlir/Support/LogicalResult.h"  // from @llvm-project
#include "mlir/Transforms/DialectConversion.h"  // from @llvm-project
#include "tensorflow/compiler/mlir/lite/ir/tfl_ops.h"
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h"
#include "xla/mlir_hlo/mhlo/IR/hlo_ops.h"

namespace mlir {
namespace odml {

bool IsIotaAttr(ArrayRef<int64_t> arr, int64_t size) {
  if (arr.size() != size) return false;
  int64_t iota = 0;

#include "mlir/Transforms/DialectConversion.h"  // from @llvm-project
#include "tensorflow/compiler/mlir/lite/stablehlo/transforms/legalize_hlo_conversions/util.h"
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h"
#include "xla/mlir_hlo/mhlo/IR/hlo_ops.h"

namespace mlir {
namespace odml {

// Convert updates into canonical form as expected by tf.scatter ops.
//