TF_DeleteImportGraphDefOptions(opts);
  opts = TF_NewImportGraphDefOptions();
  TF_ImportGraphDefOptionsSetPrefix(opts, "imported2");
  TF_ImportGraphDefOptionsAddInputMapping(opts, "scalar", 0, {scalar, 0});
  TF_ImportGraphDefOptionsAddReturnOutput(opts, "feed", 0);
  TF_ImportGraphDefOptionsAddReturnOutput(opts, "scalar", 0);
  EXPECT_EQ(2, TF_ImportGraphDefOptionsNumReturnOutputs(opts));

func Open(dialector Dialector, opts ...Option) (db *DB, err error) {
	config := &Config{}

	sort.Slice(opts, func(i, j int) bool {
		_, isConfig := opts[i].(*Config)
		_, isConfig2 := opts[j].(*Config)
		return isConfig && !isConfig2
	})

	if len(opts) > 0 {
		if c, ok := opts[0].(*Config); ok {
			config = c
		} else {
			opts = append([]Option{config}, opts...)
		}
	}

// and is re-computed by the runtime.
inline void TF_ImportGraphDefOptionsSetPropagateDeviceSpec(
    TF_ImportGraphDefOptions* opts, unsigned char propagate_device_spec) {
  opts->opts.propagate_device_spec = propagate_device_spec;
}

}  // end namespace tensorflow

		).Row().Scan(&count)
	})

	return count > 0
}

// BuildIndexOptions build index options
func (m Migrator) BuildIndexOptions(opts []schema.IndexOption, stmt *gorm.Statement) (results []interface{}) {
	for _, opt := range opts {
		str := stmt.Quote(opt.DBName)
		if opt.Expression != "" {
			str = opt.Expression
		} else if opt.Length > 0 {
			str += fmt.Sprintf("(%d)", opt.Length)
		}

	LimitPerRecord(num int) PreloadBuilder
}

type op func(*DB) *DB

func G[T any](db *DB, opts ...clause.Expression) Interface[T] {
	v := &g[T]{
		db:  db,
		ops: make([]op, 0, 5),
	}

	if len(opts) > 0 {
		v.ops = append(v.ops, func(db *DB) *DB {
			return db.Clauses(opts...)
		})
	}

	v.createG = &createG[T]{
		chainG: chainG[T]{
			execG: execG[T]{g: v},
		},
	}

                               inputs.size(), inputs.data(), outputs.size(),
                               outputs.data(), output_names_ptr,
                               /*opts=*/nullptr, /*description=*/nullptr, s_);
    delete[] output_names_ptr;
    if (expect_failure) {
      ASSERT_EQ(func_, nullptr);
      return;
    }

    ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);

  *func = TF_GraphToFunction(func_graph.get(), name, append_hash, -1,
                             /*opers=*/nullptr, 1, inputs, 1, outputs,
                             /*output_names=*/nullptr,
                             /*opts=*/nullptr, description, s.get());
  ASSERT_EQ(TF_OK, TF_GetCode(s.get())) << TF_Message(s.get());
  ASSERT_NE(*func, nullptr);
}

class CApiExperimentalFunctionTest : public ::testing::Test {
 protected:

#     define_values = {"PORTABLE_PROTO_TRANSITION_MODE": "third_party"},
#     visibility = ["//visibility:public"],
# )
# copybara:uncomment_end

# 'enable_registration_v2' opts-in to a different implementation of op and
# kernel registration - REGISTER_OP, REGISTER_KERNEL_BUILDER, etc.
#
# This setting is currently experimental. The 'v2' implementation does _not_

common --incompatible_default_to_explicit_init_py

# For projects which use TensorFlow as part of a Bazel build process, putting
# nothing in a bazelrc will default to a monolithic build. The following line
# opts in to modular op registration support by default.
common --define framework_shared_object=true
common --define tsl_protobuf_header_only=true

common --define=allow_oversize_protos=true

common --spawn_strategy=standalone

- kube-apiserver disables the beta WatchList feature by default in 1.33 in favor of the `StreamingCollectionEncodingToJSON` and `StreamingCollectionEncodingToProtobuf` features.kube-controller-manager no longer opts into enabling the WatchListClient feature in 1.33. ([#131359](https://github.com/kubernetes/kubernetes/pull/131359), [@deads2k](https://github.com/deads2k)) [SIG API Machinery]

## Dependencies

### Added