std::vector<int32_t>* out_vec);

// Gets boolean from composite attrs if it exists.
std::optional<bool> GetBoolFromCompositeAttr(
    const DictionaryAttr& composite_attrs, llvm::StringRef attr_name);

// Given a DictionaryAttr, checks if it has a DenseIntElementsAttr attribute
// with the name attr_name. If so, extracts its values and stores as a vector
// of int32_t elements.

#include "tensorflow/compiler/mlir/tensorflow/utils/dump_graph.h"

#include <cstdint>
#include <cstring>
#include <string>
#include <utility>

#include "llvm/ADT/StringMap.h"
#include "llvm/ADT/StringRef.h"
#include "llvm/ADT/Twine.h"
#include "llvm/Support/FormatVariadic.h"
#include "llvm/Support/raw_ostream.h"
#include "mlir/IR/Operation.h"  // from @llvm-project
#include "mlir/IR/Verifier.h"  // from @llvm-project

#include <cstddef>
#include <memory>
#include <optional>
#include <stdexcept>
#include <string>
#include <type_traits>

#include "llvm/ADT/STLExtras.h"
#include "llvm/ADT/StringRef.h"
#include "llvm/Support/Casting.h"
#include "mlir/IR/BuiltinAttributes.h"  // from @llvm-project
#include "mlir/Pass/Pass.h"  // from @llvm-project
#include "mlir/Support/LLVM.h"  // from @llvm-project

  absl::Status status = absl::OkStatus();
  module_op.walk([&py_function_library, &calibration_options, &status,
                  &statistics_map](mlir::TF::CustomAggregatorOp aggregator_op) {
    mlir::StringRef id = aggregator_op.getId();
    auto iter = statistics_map.find(id);
    if (iter == statistics_map.end()) {
      status = absl::InternalError(
          absl::StrFormat("Calibrated data does not exist. Cannot find "

    p << '}';
  }
}

void GetExecuteOpAttrsCommon(
    mlir::MLIRContext *context, llvm::ArrayRef<mlir::Attribute> op_attr_array,
    llvm::SmallVectorImpl<std::pair<llvm::StringRef, mlir::Attribute>>
        *op_attrs);

struct ParseExecuteOpOptions {
  bool has_chain = false;
  bool has_key = false;
  bool has_device = false;
  bool has_func_attr = false;
  bool has_cost = false;

    mlir::ModuleOp module, bool export_to_mlir, toco::TocoFlags& toco_flags,
    const mlir::TFL::PassConfig& pass_config,
    const std::unordered_set<std::string>& saved_model_tags,
    llvm::StringRef saved_model_dir, SavedModelBundle* saved_model_bundle,
    std::string* result, bool serialize_stablehlo_ops = false,
    const quantization::PyFunctionLibrary* quantization_py_function_lib =
        nullptr);

  if (failed(GetOp(region, &send_op))) return failure();

  // No TPU embedding ops.
  if (!recv_op && !send_op) return success();

  Location loc = recv_op ? recv_op.getLoc() : send_op.getLoc();
  StringRef config = recv_op ? recv_op.getConfig() : send_op.getConfig();

  // Create XlaRecvTPUEmbeddingDeduplicationData op.
  OpBuilder builder(region);
  auto output_ty =

                                    .setPassPipelineParser(passPipeline))
                  .succeeded());
}

TEST(DumpRawStringToFileTest, Valid) {
  llvm::StringRef example = "module {\n}";
  setenv("TF_DUMP_GRAPH_PREFIX", testing::TmpDir().c_str(), 1);

  std::string filepath = DumpRawStringToFile("example", example);
  ASSERT_NE(filepath, "(TF_DUMP_GRAPH_PREFIX not specified)");

#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h"

namespace mlir::quant::stablehlo {

absl::StatusOr<std::string> ConvertSerializedStableHloModuleToBfloat16(
    const StringRef serialized_stablehlo_module) {
  // StableHLO module is empty often because the XlaCallModuleOp is already
  // deserialized, e.g. after invoking XlaCallModuleDeserializationPass. We
  // don't handle this situation.

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

#include "tensorflow/compiler/mlir/quantization/common/ir/QuantOps.h"

#include <numeric>

#include "llvm/ADT/StringRef.h"
#include "llvm/ADT/Twine.h"
#include "llvm/Support/MathExtras.h"
#include "mlir/Dialect/Quant/QuantTypes.h"  // from @llvm-project
#include "mlir/IR/BuiltinTypes.h"  // from @llvm-project