}

  companion object {
    const val OKHTTP_CLIENT_WINDOW_SIZE = 16 * 1024 * 1024

    val DEFAULT_SETTINGS =
      Settings().apply {
        set(Settings.INITIAL_WINDOW_SIZE, DEFAULT_INITIAL_WINDOW_SIZE)
        set(Settings.MAX_FRAME_SIZE, Http2.INITIAL_MAX_FRAME_SIZE)
      }

    const val INTERVAL_PING = 1
    const val DEGRADED_PING = 2
    const val AWAIT_PING = 3

  // For LLVM style RTTI.
  static bool classof(const AbstractContext* ptr) {
    return ptr->getKind() == kGraph || ptr->getKind() == kMlir;
  }
};

typedef TracingContext* (*FactoryFunction)(const char* fn_name, TF_Status*);
absl::Status SetDefaultTracingEngine(const char* name);
void RegisterTracingEngineFactory(const ::tensorflow::string& name,
                                  FactoryFunction factory);

  }

  // Checks the expected result of shape inference for the given `op`.
  void CheckOutputShapes(
      TFE_Op* op,
      const std::vector<absl::optional<std::vector<int64_t>>>& input_shapes_vec,
      const std::vector<TF_Tensor*>& input_tensors,
      const absl::optional<std::vector<int64_t>>& expected_shape) {
    // Create input_shapes.
    TF_ShapeAndTypeList* input_shapes =

// placed on the parallel device.
class NamedParallelDevice {
 public:
  NamedParallelDevice(const std::string& name,
                      std::unique_ptr<ParallelDevice> parallel_device)
      : device_name_(name), parallel_device_(std::move(parallel_device)) {}
  const std::string& name() const { return device_name_; }
  const ParallelDevice& device() const { return *parallel_device_; }

 private:
  std::string device_name_;

                      device_name, "\")");
}

absl::Status ImmediateExecutionTensorHandle::SummarizeValue(
    std::string& summary) const {
  absl::Status status;
  AbstractTensorPtr resolved(
      // TODO(allenl): Resolve should be const, and the caches that get updated
      // marked mutable.
      const_cast<ImmediateExecutionTensorHandle*>(this)->Resolve(&status));
  if (!status.ok()) {
    return status;

import okio.utf8Size

/**
 * Trivial Dns Encoder/Decoder, basically ripped from Netty full implementation.
 */
internal object DnsRecordCodec {
  private const val SERVFAIL = 2
  private const val NXDOMAIN = 3
  const val TYPE_A = 0x0001
  const val TYPE_AAAA = 0x001c
  private const val TYPE_PTR = 0x000c
  private val ASCII = Charsets.US_ASCII

  fun encodeQuery(
    host: String,
    type: Int,
  ): ByteString =

/** `100 Continue` (HTTP/1.1 - RFC 7231)  */
const val HTTP_CONTINUE = 100

/** `102 Processing` (WebDAV - RFC 2518)  */
const val HTTP_PROCESSING = 102

/** `103 Early Hints (Early Hints - RFC 8297)` */
const val HTTP_EARLY_HINTS = 103

/** `307 Temporary Redirect` (HTTP/1.1 - RFC 7231)  */
const val HTTP_TEMP_REDIRECT = 307

/** `308 Permanent Redirect` (HTTP/1.1 - RFC 7538)  */
const val HTTP_PERM_REDIRECT = 308

internal const val USERNAME_ENCODE_SET = " \"':;<=>@[]^`{}|/\\?#"
internal const val PASSWORD_ENCODE_SET = " \"':;<=>@[]^`{}|/\\?#"
internal const val PATH_SEGMENT_ENCODE_SET = " \"<>^`{}|/\\?#"
internal const val PATH_SEGMENT_ENCODE_SET_URI = "[]"
internal const val QUERY_ENCODE_SET = " \"'<>#"
internal const val QUERY_COMPONENT_REENCODE_SET = " \"'<>#&="

  handle_->Ref();
}
TapeTensor::TapeTensor(const TapeTensor& other) {
  handle_ = other.handle_;
  handle_->Ref();
}
TapeTensor::~TapeTensor() { handle_->Unref(); }

int64_t TapeTensor::GetID() const { return ToId(handle_); }

tensorflow::DataType TapeTensor::GetDType() const {
  return handle_->DataType();
}
AbstractTensorHandle* TapeTensor::GetHandle() const { return handle_; }

import jetbrains.buildServer.configs.kotlin.Project
import model.CIBuildModel
import model.FunctionalTestBucketProvider
import model.Stage
import model.TestCoverage

const val DEFAULT_FUNCTIONAL_TEST_BUCKET_SIZE = 50
const val DEFAULT_LINUX_FUNCTIONAL_TEST_BUCKET_SIZE = 20
const val DEFAULT_MACOS_FUNCTIONAL_TEST_BUCKET_SIZE = 20

class FunctionalTestProject(
    val model: CIBuildModel,