// TODO - b/296503614: [Converter Component][TF-Quantizer] Reflect custom traits
// from TF-Quantizer to stableHLO quantization
bool IsOpWithDataMovementTrait(Operation* op) {
  // Supported data movement ops. These ops do not perform any computations and
  // has one result operand.
  return isa<TF::IdentityOp, TF::CastOp, TF::ReshapeOp, TF::XlaShardingOp,
             TF::GatherOp, TF::GatherV2Op, TF::XlaGatherOp, TF::ExpandDimsOp,

    signalPassFailure();
    return;
  }

  // Copy all functions used by this signature to the final MLIR module.
  for (func::FuncOp func : module_ref->getOps<func::FuncOp>()) {
    // Do nothing if the function already exists.
    if (symbol_table.lookup(func.getSymName()) != nullptr) continue;

    // Set the function to private and insert to the module.
    func::FuncOp new_func = func.clone();

      : ConversionTarget(ctx), converter_(converter) {
    markUnknownOpDynamicallyLegal([this](Operation* op) {
      // The FuncOp type can contain types that the op's operand and result
      // types do not contain.
      if (auto func = dyn_cast<func::FuncOp>(op)) {
        if (!converter_.isSignatureLegal(func.getFunctionType())) return false;
      } else if (auto bitcast_convert_op =

//    *different* variables
//  - they make the blanket assumption that any functions called cause or depend
//    on side effects (i.e., access resource variables.)
//
// By moving the logic to compile time, we will be able to do a finer-grained
// data flow analysis in the future, which will enable more optimizations.
// This could happen in two steps:
// (1) build multiple dependency chains (one per variable), still treating

    absl::Span<tensorflow::AbstractTensorHandle* const> inputs,
    absl::Span<tensorflow::AbstractTensorHandle*> outputs) {
  // TODO(srbs): Provide a function execution API on ctx so that we do not
  // expose the internals of how functions are to be executed here.
  std::string fname;
  {
    const tensorflow::FunctionDef* fdef = nullptr;
    TF_RETURN_IF_ERROR(trace->GetFunctionDef(&fdef));

  Graph* graph_;
  int unique_name_counter_;
};

string CloneConstantsForBetterClusteringPassImpl::GenerateUniqueName(
    const absl::flat_hash_set<string>& name_set, absl::string_view prefix) {
  string candidate;
  do {
    candidate = absl::StrCat(prefix, "/clone_", unique_name_counter_++);
  } while (name_set.contains(candidate));
  return candidate;
}

absl::StatusOr<Node*> CloneConstantsForBetterClusteringPassImpl::CloneNode(

See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/

// Generated by the tf_library build rule.  DO NOT EDIT!
//
// This file contains a test and benchmark for the function generated by
// tfcompile.  All tokens of the form `{{TFCOMPILE_*}}` must be rewritten to
// real values before this file can be compiled.
//

  // The result (a shape after a reduction with keep_dims=True)
  // [2, 1, 1, 7]
  //
  // We can treat each entry in axes as an index into input_shape that
  // should be replaced by 1.
  // We use DynamicStitch to do this.

  // input_rank = 4
  auto input_rank = Size(scope, input_shape);

  // Normalize any negative indices in the reduction_axes to positive
  // values.

#include "tensorflow/core/framework/cpp_shape_inference.pb.h"
#include "tensorflow/core/framework/full_type.pb.h"

namespace tensorflow {

// Hack to export the tensorflow::RecordMutation symbol for windows.
// Do not delete. Do not use.
void ExportRecordMutation(  // NOLINT: Intentionally unused function.
    TF_Graph* graph, const TF_Operation& op, const char* mutation_type) {
  mutex_lock l(graph->mu);
  RecordMutation(graph, op, mutation_type);

  if (!(indices_size == shared_name_size &&
        shared_name_size == container_size)) {
    return get_resource_op->emitError()
           << "length of attribute arrays do not match. indices = "
           << indices_size << ", shared_name = " << shared_name_size
           << ", container = " << container_size;
  }

  return success();
}