return absl::OkStatus();
  }

  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.

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(

TF_WhileParams TF_NewWhile(TF_Graph* g, TF_Output* inputs, int ninputs,
                           TF_Status* status) {
#if defined(IS_MOBILE_PLATFORM) || defined(IS_SLIM_BUILD)
  status->status = tensorflow::errors::Unimplemented(
      "Creating while loops is not supported on mobile. File a bug at "
      "https://github.com/tensorflow/tensorflow/issues if this feature is "
      "important to you");
  return EmptyWhileParams();
#else

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);

   * @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>}),
   *     then this is not logically a {@code Converter} at all, and should just implement {@link
   *     Function}.

   * @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>}),
   *     then this is not logically a {@code Converter} at all, and should just implement {@link
   *     Function}.

  EXPECT_EQ(TF_OUT_OF_RANGE,
            static_cast<TF_Code>(tensorflow::error::OUT_OF_RANGE));
  EXPECT_EQ(TF_UNIMPLEMENTED,
            static_cast<TF_Code>(tensorflow::error::UNIMPLEMENTED));
  EXPECT_EQ(TF_INTERNAL, static_cast<TF_Code>(tensorflow::error::INTERNAL));
  EXPECT_EQ(TF_UNAVAILABLE,
            static_cast<TF_Code>(tensorflow::error::UNAVAILABLE));

    *   (since v2.7) Run `tf.scatter_nd` and other related scatter functions,
        such as `tf.tensor_scatter_nd_update`, on CPU (with significant
        performance penalty).
    *   Add determinism-unimplemented exception-throwing to the following ops.
        When op-determinism is expected (i.e. after
        `tf.config.experimental.enable_op_determinism` has been called), an

Use of this source code is governed by a BSD-style // license that can be found in the LICENSE file. //go:build (!amd64 && !arm64) || purego package nistec import "errors" func P256OrdInverse(k []byte) ([]byte, error) { return nil, errors.New("unimplemented") } golang.org/fips140@v1.0.0-c2097c7c/fips140/v1.0.0-c2097c7c/nistec/p256_table.go // Copyright 2024 The Go Authors. All rights reserved. // Use of this source code is governed by a BSD-style // license that can be found in the LICENSE file. package...