#include "tensorflow/compiler/mlir/quantization/common/quantization_lib/quantization_utils.h"
#include "tensorflow/compiler/mlir/quantization/stablehlo/ops/stablehlo_op_quant_spec.h"
#include "tensorflow/core/framework/types.pb.h"

namespace mlir::quant::stablehlo {

// Checks whether an op is connected with a quantized composite function. If
// not, the same-scale op will not be quantized. This decision is based on the

#include "xla/test.h"
#include "tensorflow/core/framework/tensor_testutil.h"
#include "tensorflow/core/framework/tensor_util.h"
#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/lib/core/errors.h"
#include "tensorflow/core/lib/core/status_test_util.h"
#include "tensorflow/core/platform/types.h"
#include "tsl/platform/ml_dtypes.h"

namespace tensorflow {
namespace {

#include "tensorflow/compiler/mlir/tensorflow/utils/mangling_util.h"
#include "tensorflow/core/framework/tensor.h"
#include "tensorflow/core/framework/tensor_shape.pb.h"
#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/platform/types.h"

namespace mlir {

namespace {

namespace cutil = TF::collection_ops_util;

#define GEN_PASS_DEF_STACKOPSDECOMPOSITIONPASS

#include "tensorflow/compiler/mlir/quantization/common/quantization_lib/quantization_utils.h"  // IWYU pragma: keep
#include "tensorflow/compiler/mlir/quantization/tensorflow/quantization_options.pb.h"
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h"
#include "tensorflow/compiler/mlir/tensorflow/utils/xla_call_module_attrs.h"

namespace mlir::quant {

constexpr char kAttrMapAttribute[] = "attr_map";

#include "tensorflow/compiler/tf2xla/xla_op_registry.h"
#include "xla/client/xla_builder.h"
#include "xla/client/xla_computation.h"
#include "xla/mlir_hlo/mhlo/IR/hlo_ops.h"
#include "xla/shape_util.h"
#include "xla/xla_data.pb.h"
#include "tensorflow/core/framework/op_kernel.h"
#include "tsl/lib/core/status_test_util.h"
#include "tsl/platform/errors.h"
#include "tsl/platform/status.h"
#include "tsl/platform/statusor.h"

namespace mlir {

			if err != nil {
				return nil, false, err
			}
			oc.Sampler = dts
		}

		// If any sampler is configured for the OpenTelemetryTracingProvider
		hasCustomSampler = true
	}

	pb, err := anypb.New(oc)
	return pb, hasCustomSampler, err
}

func skywalkingConfig(clusterName, hostname string) (*anypb.Any, error) {
	s := &tracingcfg.SkyWalkingConfig{
		GrpcService: &core.GrpcService{

			prefix += filepath.Base(p.Mapping[0].File) + "."
		}
		for _, s := range p.SampleType {
			prefix += s.Type + "."
		}

		tempFile, err := newTempFile(dir, prefix, ".pb.gz")
		if err == nil {
			if err = p.Write(tempFile); err == nil {
				o.UI.PrintErr("Saved profile in ", tempFile.Name())
			}
		}
		if err != nil {
			o.UI.PrintErr("Could not save profile: ", err)
		}

#include "mlir/Support/LogicalResult.h"  // from @llvm-project
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_device.h"
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_structs.h"
#include "xla/xla_data.pb.h"
#include "tensorflow/core/lib/core/status.h"
#include "tensorflow/core/platform/statusor.h"
#include "tensorflow/core/util/device_name_utils.h"

namespace tensorflow {
using tsl::StatusOr;

#include "tensorflow/compiler/tf2xla/xla_helpers.h"
#include "xla/client/xla_computation.h"
#include "tensorflow/core/common_runtime/device.h"
#include "tensorflow/core/framework/graph_debug_info.pb.h"
#include "tensorflow/core/framework/tensor_shape.h"

namespace tensorflow {

// Lowers MLIR module to XLA HLO inside an XlaComputation. The input module

#include "mlir/Support/LLVM.h"  // from @llvm-project
#include "tensorflow/compiler/mlir/quantization/common/attrs_and_constraints.h"
#include "tensorflow/compiler/mlir/quantization/tensorflow/cc/constant_fold.h"
#include "xla/xla_data.pb.h"
#include "tensorflow/lite/kernels/padding.h"

namespace mlir::quant {
namespace {

Value GetDimValue(OpBuilder &builder, Location loc, Value shape_value,
                  int32_t dim) {