#include "tensorflow/core/lib/core/status_test_util.h"
#include "tensorflow/core/platform/test.h"

namespace tensorflow {
namespace {

Status PickDeviceHelper(bool allow_mixing_unknown_and_cpu,
                        absl::Span<const absl::string_view> device_names,
                        string* result) {
  jit::DeviceInfoCache cache;
  jit::DeviceSet device_set;
  for (absl::string_view name : device_names) {

  // XlaCompilationResult pointed to by `result` by calling
  // XlaCompiler::CompileFunction.
  Status Compile(const XlaCompiler::CompileOptions& options,
                 const NameAttrList& function,
                 absl::Span<const XlaArgument> args,
                 XlaCompilationResult* result) override;

  // Compiles a Tensorflow single op into an HloModuleProto stored in the
  // XlaCompilationResult pointed to by `result` by calling

	arch string
	name string
}

var (
	bases   = map[baseKey]v1.Image{}
	basesMu sync.RWMutex
)

func WarmBase(ctx context.Context, architectures []string, baseImages ...string) {
	_, span := tracing.Start(ctx, "RunCrane")
	defer span.End()
	basesMu.Lock()
	wg := sync.WaitGroup{}
	wg.Add(len(baseImages) * len(architectures))
	resolvedBaseImages := make([]v1.Image, len(baseImages)*len(architectures))
	keys := []baseKey{}

#include <string>
#include <utility>

#include "absl/container/flat_hash_map.h"
#include "absl/status/status.h"
#include "absl/status/statusor.h"
#include "absl/strings/str_cat.h"
#include "absl/types/span.h"
#include "tensorflow/compiler/mlir/quantization/stablehlo/quantization_config.pb.h"
#include "tensorflow/compiler/mlir/quantization/tensorflow/quantization_options.pb.h"

namespace stablehlo::quantization {

#include "tensorflow/compiler/mlir/quantization/tensorflow/calibrator/calibration_statistics_collector_min_max.h"

#include <algorithm>
#include <cstdint>
#include <limits>
#include <optional>

#include "absl/types/span.h"
#include "tensorflow/compiler/mlir/quantization/tensorflow/calibrator/calibration_statistics.pb.h"

namespace tensorflow {
namespace calibrator {

void CalibrationStatisticsCollectorMinMax::ClearData() {

namespace tensorflow {
namespace gradients {
namespace {
class IdentityNGradientFunction : public GradientFunction {
 public:
  Status Compute(AbstractContext* ctx,
                 absl::Span<AbstractTensorHandle* const> grad_outputs,
                 absl::Span<AbstractTensorHandle*> grad_inputs) override {
    for (int i = 0; i < grad_outputs.size(); i++) {
      auto grad_input = grad_outputs[i];

#define TENSORFLOW_COMPILER_MLIR_QUANTIZATION_STABLEHLO_CC_CALIBRATION_REPRESENTATIVE_DATASET_H_

#include <string>

#include "absl/container/flat_hash_map.h"
#include "absl/status/statusor.h"
#include "absl/types/span.h"
#include "tensorflow/compiler/mlir/quantization/stablehlo/quantization_config.pb.h"
#include "tensorflow/compiler/mlir/quantization/tensorflow/quantization_options.pb.h"

namespace stablehlo::quantization {

#define TENSORFLOW_COMPILER_MLIR_QUANTIZATION_TENSORFLOW_CALIBRATOR_CALIBRATION_STATISTICS_COLLECTOR_MIN_MAX_H_

#include <cstdint>
#include <optional>

#include "absl/types/span.h"
#include "tensorflow/compiler/mlir/quantization/stablehlo/quantization_config.pb.h"
#include "tensorflow/compiler/mlir/quantization/tensorflow/calibrator/calibration_statistics.pb.h"

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

#include "absl/base/macros.h"
#include "absl/strings/string_view.h"
#include "absl/types/span.h"
#include "mlir/Dialect/Func/IR/FuncOps.h"  // from @llvm-project
#include "mlir/IR/BuiltinOps.h"  // from @llvm-project
#include "mlir/IR/MLIRContext.h"  // from @llvm-project
#include "tensorflow/cc/saved_model/loader.h"

  bool UseFunction() const { return std::get<2>(GetParam()); }
};

// Checks that inputs[0] is a scalar.
Status TestScalarShape(AbstractContext* ctx,
                       absl::Span<AbstractTensorHandle* const> inputs,
                       absl::Span<AbstractTensorHandle*> outputs) {
  PartialTensorShape shape;
  TF_RETURN_IF_ERROR(inputs[0]->Shape(&shape));
  if (shape.dims() != 0) {
    return errors::InvalidArgument(