context_.loadAllAvailableDialects();
  }

  absl::Status CreateMlirModule(std::string mlir_module_filename) {
    std::string mlir_module_path = TestDataPath() + mlir_module_filename;
    mlir_module_ =
        mlir::parseSourceFile<mlir::ModuleOp>(mlir_module_path, &context_);
    if (!mlir_module_) {
      return absl::Status(
          absl::StatusCode::kNotFound,
          absl::StrCat("Could not find MLIR module at ", mlir_module_path));

        "//tensorflow/core:protos_all_cc",
        "//tensorflow/core/util/quantization:uniform_quant_ops_params",
        "@com_google_absl//absl/base:core_headers",
        "@com_google_absl//absl/strings",
        "@com_google_absl//absl/synchronization",
        "@com_google_absl//absl/types:span",
        "@llvm-project//llvm:Support",
        "@llvm-project//mlir:ArithDialect",
        "@llvm-project//mlir:FuncDialect",

      Status s = CheckIfTPUInitialized();
      if (!s.ok()) {
        done(s);
        return absl::OkStatus();
      }
    }
    if (input->shape().num_elements() == 0) {
      // Zero-element tensors have no backing buffers.
      done(absl::OkStatus());
      return absl::OkStatus();
    }

    se::Stream* const src_compute_stream = src_xla_context->stream();

        "//tensorflow/core:lib",
        "//third_party/python_runtime:headers",
        "@com_google_absl//absl/status",
        "@com_google_absl//absl/status:statusor",
        "@com_google_absl//absl/strings",
        "@com_google_absl//absl/strings:string_view",
        "@llvm-project//llvm:Support",
        "@llvm-project//mlir:BytecodeWriter",
        "@llvm-project//mlir:IR",

        "//tensorflow/core/tfrt/runtime",
        "//tensorflow/core/tpu:tpu_defs",
        "@com_google_absl//absl/container:flat_hash_set",
        "@com_google_absl//absl/functional:function_ref",
        "@com_google_absl//absl/log",
        "@com_google_absl//absl/status",
        "@com_google_absl//absl/strings",
        "@llvm-project//mlir:FuncDialect",
        "@llvm-project//mlir:FuncExtensions",

        "//tensorflow/core:protos_all_cc",
        "//tensorflow/lite:framework",
        "//tensorflow/lite/tools/optimize:reduced_precision_support",
        "@com_google_absl//absl/log",
        "@com_google_absl//absl/status",
        "@com_google_absl//absl/strings",
        "@flatbuffers",
        "@llvm-project//llvm:Support",
        "@llvm-project//mlir:FuncDialect",
        "@llvm-project//mlir:IR",

        "//tensorflow/compiler/mlir/tensorflow/transforms:tensorflow_passes",
        "//tensorflow/core:lib",
        "@com_google_absl//absl/status",
        "@com_google_absl//absl/strings",
        "@com_google_absl//absl/strings:str_format",
        "@llvm-project//llvm:Support",
        "@llvm-project//mlir:FuncDialect",
        "@llvm-project//mlir:IR",
        "@llvm-project//mlir:Parser",

#include "tensorflow/compiler/mlir/lite/quantization/lite/quantize_model.h"

#include <optional>
#include <string>
#include <unordered_set>

#include "absl/container/flat_hash_set.h"
#include "absl/log/log.h"
#include "absl/strings/string_view.h"
#include "llvm/ADT/StringRef.h"
#include "llvm/ADT/Twine.h"
#include "llvm/Support/Debug.h"
#include "mlir/IR/BuiltinOps.h"  // from @llvm-project

    context_.loadAllAvailableDialects();
  }

  absl::Status CreateMlirModule(std::string mlir_module_filename) {
    std::string mlir_module_path = TestDataPath() + mlir_module_filename;
    mlir_module_ =
        mlir::parseSourceFile<mlir::ModuleOp>(mlir_module_path, &context_);
    if (!mlir_module_) {
      return absl::Status(
          absl::StatusCode::kNotFound,
          absl::StrCat("Could not find MLIR module at ", mlir_module_path));

        "@com_google_absl//absl/algorithm:container",
        "@com_google_absl//absl/cleanup",
        "@com_google_absl//absl/container:flat_hash_map",
        "@com_google_absl//absl/container:flat_hash_set",
        "@com_google_absl//absl/random",
        "@com_google_absl//absl/status",
        "@com_google_absl//absl/status:statusor",
        "@com_google_absl//absl/strings",