"//tensorflow/core/graph/regularization:util",
        "//tensorflow/core/util/tensor_bundle:naming",
        "@com_google_absl//absl/container:btree",
        "@com_google_absl//absl/log",
        "@com_google_absl//absl/status",
        "@com_google_absl//absl/status:statusor",
        "@com_google_absl//absl/strings",
        "@local_tsl//tsl/platform:protobuf",
        "@local_tsl//tsl/platform:types",
    ] + if_not_mobile([

#define TENSORFLOW_COMPILER_MLIR_QUANTIZATION_STABLEHLO_CC_WEIGHT_ONLY_PTQ_H_

#include <string>
#include <vector>

#include "absl/base/nullability.h"
#include "absl/container/flat_hash_map.h"
#include "absl/status/status.h"
#include "absl/status/statusor.h"
#include "absl/strings/string_view.h"
#include "mlir/IR/BuiltinOps.h"  // from @llvm-project
#include "mlir/Pass/PassManager.h"  // from @llvm-project

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

#include <memory>
#include <set>
#include <string>

#include "absl/status/status.h"
#include "absl/status/statusor.h"
#include "absl/strings/str_cat.h"
#include "llvm/Support/Path.h"
#include "llvm/Support/ToolOutputFile.h"
#include "mlir/Support/FileUtilities.h"  // from @llvm-project

#include "tensorflow/cc/saved_model/fingerprinting.h"

#include <cstdint>
#include <string>

#include "absl/container/btree_map.h"
#include "absl/log/log.h"
#include "absl/status/status.h"
#include "absl/status/statusor.h"
#include "absl/strings/str_cat.h"
#include "absl/strings/string_view.h"
#include "absl/strings/strip.h"
#include "tensorflow/cc/saved_model/constants.h"
#include "tensorflow/core/framework/versions.pb.h"

#include <cstdint>
#include <cstdlib>
#include <memory>
#include <string>
#include <utility>

#include "absl/log/log.h"
#include "absl/memory/memory.h"
#include "absl/status/status.h"
#include "absl/status/statusor.h"
#include "absl/strings/match.h"
#include "absl/strings/string_view.h"
#include "llvm/ADT/DenseMap.h"
#include "llvm/Support/Casting.h"
#include "llvm/Support/FormatVariadic.h"

// `inputs_arg_shape_and_dtype` and `input_handles`.
absl::StatusOr<std::string> GetCompilerIr(
    IrExportStage stage, ProcessFunctionLibraryRuntime* pflr,
    absl::string_view func_name, absl::string_view platform_name,
    EagerContext* context,
    absl::Span<const ArgShapeAndDType> input_arg_shape_and_dtype,
    absl::Span<const TensorHandle* const> input_handles,
    CompilerArgSource compiler_arg_source);

  Status Append(StringPiece data) override {
    absl::StrAppend(&str_, data);
    return absl::OkStatus();
  }

  Status Close() override { return absl::OkStatus(); }

  Status Flush() override { return absl::OkStatus(); }

  Status Name(StringPiece* result) const override {
    *result = "(string)";
    return absl::OkStatus();
  }

  Status Sync() override { return absl::OkStatus(); }

  constexpr absl::string_view kConstOpExpr =
      R"mlir(%cst = "tf.Const"() {value = dense<3.0> : tensor<4xf32>} : () -> tensor<4xf32>)mlir";

  Block block{};
  TF::ConstOp int_tensor_const_op = ParseConstOp(kConstOpExpr, block, ctx_);

  const int64_t num_bytes = GetSizeInBytes(int_tensor_const_op);
  EXPECT_THAT(num_bytes, Eq(16));
}

TEST_F(GetSizeInBytesTest, Float64ConstOpSizeInBytes) {

  template <class T>
  tensorflow::StatusOr<Tensor> CreateHostTensor(absl::Span<const int64_t> shape,
                                                int dtype,
                                                absl::Span<const T> data);
};

template <class T>
tensorflow::StatusOr<Tensor> Runtime::CreateHostTensor(
    absl::Span<const int64_t> shape, int dtype, absl::Span<const T> data) {
  size_t num_elements = 1;

    if (RE2::FullMatch(pass->getName(), *dump_pass_re_)) {
      Dump(absl::StrCat(absl::string_view(pass->getName()), "_before"), op,
           absl::StrCat(absl::Hex(pass_counter_, absl::kZeroPad8)));
    }
  }

  void runAfterPass(mlir::Pass* pass, mlir::Operation* op) override {
    if (RE2::FullMatch(pass->getName(), *dump_pass_re_)) {
      Dump(absl::StrCat(absl::string_view(pass->getName()), "_after"), op,