void AddPostQuantizationStableHloToTfPasses(
    const mlir::TFL::PassConfig& pass_config,
    mlir::OpPassManager& pass_manager);

// This is the early part of the conversion in isolation. This enables a caller
// to inject more information in the middle of the conversion before resuming it
// (like freezing variables for example).
void AddPreVariableFreezingTFToTFLConversionPasses(
    const mlir::TFL::PassConfig& pass_config,

#include <memory>
#include <string>

#include "tensorflow/c/tf_status_helper.h"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/platform/status.h"
#include "tensorflow/core/platform/types.h"
#include "tensorflow/core/util/tensor_bundle/tensor_bundle.h"
#include "tensorflow/core/util/tensor_slice_reader.h"

namespace tensorflow {
namespace checkpoint {

class TensorSliceReader;

                             absl::Span<AbstractTensorHandle* const> inputs,
                             std::vector<AbstractTensorHandle*>* params);

// A callable that takes tensor inputs and returns zero or more tensor outputs.
using Model = std::function<Status(AbstractContext*,
                                   absl::Span<AbstractTensorHandle* const>,
                                   absl::Span<AbstractTensorHandle*>)>;

#include "tensorflow/compiler/mlir/quantization/tensorflow/exported_model.pb.h"
#include "tensorflow/compiler/mlir/quantization/tensorflow/quantization_options.pb.h"
#include "tensorflow/core/framework/graph.pb.h"
#include "tensorflow/core/protobuf/meta_graph.pb.h"
#include "tensorflow/python/lib/core/pybind11_lib.h"
#include "tsl/platform/protobuf.h"  // IWYU pragma: keep

namespace pybind11::detail {
namespace internal {

// `base_loc` is used for error reporting and debug info.
// If ordered_output_arrays is not empty, then the imported mlir function will
// only return nodes in ordered_output_arrays in the same order. Returns nullptr
// on failure, and more specific errors will be emitted via the context.
// If `use_external_constant` is true, it will create `tfl.external_const`
// instead of `tfl.const`.
// If `experimental_prune_unreachable_nodes_unconditionally` is true, nodes that

// converting them to NHWC formats along with extra optimizations such as
// constant folding the transpose->convolution pattern. This is useful when
// downstream pipeline (e.g. XLA) is more optimized when accepting NHWC formats.
void AddProcessNchwTensorPasses(OpPassManager& pm);

// Registers quantization pass pipelines. This is only required when running

#include <memory>
#include <unordered_set>

#include "absl/status/statusor.h"
#include "tensorflow/core/framework/graph_debug_info.pb.h"
#include "tensorflow/core/lib/core/status.h"
#include "tensorflow/core/platform/types.h"
#include "tensorflow/core/protobuf/meta_graph.pb.h"
#include "tensorflow/core/protobuf/saved_model.pb.h"

namespace tensorflow {
Status ReadSavedModel(absl::string_view export_dir,

#include <vector>

#include "tensorflow/core/framework/api_def.pb.h"
#include "tensorflow/core/framework/attr_value.pb.h"
#include "tensorflow/core/framework/attr_value_util.h"
#include "tensorflow/core/framework/op_def_util.h"
#include "tensorflow/core/framework/op_gen_lib.h"
#include "tensorflow/core/framework/tensor.pb.h"
#include "tensorflow/core/framework/tensor_shape.pb.h"
#include "tensorflow/core/platform/types.h"

namespace tensorflow {

#ifndef TENSORFLOW_COMPILER_MLIR_LITE_PYTHON_JAX_TO_TFL_FLATBUFFER_H_
#define TENSORFLOW_COMPILER_MLIR_LITE_PYTHON_JAX_TO_TFL_FLATBUFFER_H_

#include <string>

#include "tensorflow/core/lib/core/errors.h"
#include "tensorflow/core/platform/status.h"
#include "tensorflow/core/platform/types.h"
#include "tensorflow/lite/toco/model_flags.pb.h"
#include "tensorflow/lite/toco/toco_flags.pb.h"

namespace tensorflow {

#include "tensorflow/compiler/mlir/tensorflow/utils/export_utils.h"
#include "tensorflow/core/framework/attr_value.pb.h"
#include "tensorflow/core/framework/node_def.pb.h"
#include "tensorflow/core/framework/node_def_util.h"
#include "tensorflow/core/framework/op_def_builder.h"
#include "tensorflow/core/platform/status.h"

namespace tensorflow {