}

  absl::Status RegisterFunction(AbstractFunction* func) override {
    return errors::Unimplemented(
        "Registering graph functions has not been implemented yet.");
  }

  absl::Status RemoveFunction(const string& func) override {
    return errors::Unimplemented(
        "GraphContext::RemoveFunction has not been implemented yet.");
  }
  // For LLVM style RTTI.
  static bool classof(const AbstractContext* ptr) {

void TFE_DeleteContextOptions(TFE_ContextOptions* options) { delete options; }

TFE_Context* TFE_NewContext(const TFE_ContextOptions* opts, TF_Status* status) {
  if (opts->use_tfrt) {
    status->status = tensorflow::errors::Unimplemented("TFRT is not supported");
    return nullptr;
  }
  std::vector<std::unique_ptr<tensorflow::Device>> devices;
  status->status = tensorflow::DeviceFactory::AddDevices(

            break;
        case Smb2Constants.SMB2_DIALECT_0300:
        case Smb2Constants.SMB2_DIALECT_0302:
            this.signingKey = Smb3KeyDerivation.deriveSigningKey(dialect, sessionKey, new byte[0] /* unimplemented */);
            this.algorithmName = "AESCMAC";
            this.provider = Crypto.getProvider();
            break;
        case Smb2Constants.SMB2_DIALECT_0311:
            if (preauthIntegrityHash == null) {

TF_Library* TF_LoadPluggableDeviceLibrary(const char* library_filename,
                                          TF_Status* status) {
#if defined(IS_MOBILE_PLATFORM) || defined(IS_SLIM_BUILD)
  status->status = tensorflow::errors::Unimplemented(
      "PluggableDevice plugin functionality is not supported on mobile");
  return nullptr;
#else
  TF_Library* lib_handle = new TF_Library;
  static tensorflow::mutex mu(tensorflow::LINKER_INITIALIZED);

   * getAnnotatedBounds()} method, then its return type means it won't compile on Android, while if
   * we don't include the method, then the compiler will complain that an abstract method is
   * unimplemented. So instead we use a dynamic proxy to get an implementation. If the method being
   * called on the {@code TypeVariable} instance has the same name as one of the public methods of

   * @return the converted instance; <b>must not</b> be null
   * @throws UnsupportedOperationException if backward conversion is not implemented; this should be
   *     very rare. Note that if backward conversion is not only unimplemented but
   *     unimplement<i>able</i> (for example, consider a {@code Converter<Chicken, ChickenNugget>}),

   * @return the converted instance; <b>must not</b> be null
   * @throws UnsupportedOperationException if backward conversion is not implemented; this should be
   *     very rare. Note that if backward conversion is not only unimplemented but
   *     unimplement<i>able</i> (for example, consider a {@code Converter<Chicken, ChickenNugget>}),

  void (*delete_device)(void* device_info);

  // Implements TFE_CreatePackedTensorHandle when one of `handles` is on this
  // custom device.
  //
  // Many devices will want to simply return an "unimplemented" status
  // here. This is the default behavior if `pack` is null when passed to
  // TFE_RegisterCustomDevice.
  TFE_TensorHandle* (*pack)(TFE_Context* context, TFE_TensorHandle** handles,

		} else {
			r1, r2, scale, ok = p.register(tok.String(), 0)
			if !ok {
				p.errorf("indirect through non-register %s", tok)
			}
			if r2 != 0 {
				p.errorf("unimplemented two-register form")
			}
			a.Index = r1
			if scale != 0 && scale != 1 && (p.arch.Family == sys.ARM64 ||
				p.arch.Family == sys.PPC64) {
				// Support (R1)(R2) (no scaling) and (R1)(R2*1).

            return compressLZ77Huffman(data, offset, length);

        case COMPRESSION_LZNT1:
            throw new CIFSException("LZNT1 compression not yet implemented");

        case COMPRESSION_PATTERN_V1:
            throw new CIFSException("Pattern_V1 compression not yet implemented");

        default:
            throw new CIFSException("Unknown compression algorithm: " + algorithm);
        }
    }

    @Override