}
    if (num_dims_i < 0) {
      proto[i].set_unknown_rank(true);
    } else {
      const int64_t* dims_i = dims[i];
      auto proto_i = &proto[i];
      for (int d = 0; d < num_dims_i; ++d) {
        proto_i->add_dim()->set_size(dims_i[d]);
      }
    }
  }
  forward_op_->attrs.Set(
      attr_name, gtl::ArraySlice<TensorShapeProto>(proto.get(), num_values));

                                                      size_t proto_len,
                                                      TF_Status* status);

// This API is for experimental usage and may be subject to change.
TF_CAPI_EXPORT extern void TFE_ContextUpdateServerDefWithTimeout(
    TFE_Context* ctx, int keep_alive_secs, const void* proto, size_t proto_len,

                             const void* proto, size_t proto_len,
                             TF_Status* status) {
  tensorflow::AttrValue attr_value;
  if (!attr_value.ParseFromArray(proto, proto_len)) {
    status->status =
        tensorflow::errors::InvalidArgument("Unparseable AttrValue proto");
    return;
  }
  if (op == nullptr) {

// On success, returns a set of TF_Function instances from `text_proto` of
// GraphDef type. These functions must be deleted by calling TF_DeleteFunction.
//
// If `mutate_proto_func` is non-NULL, run it over each FunctionDef proto,
// before creating a TF_Function out of the possibly mutated proto.
static std::vector<UniqueFuncPtr> CreateFunctionsFromTextProto(
    const char* text_proto,

                                  const void* proto, size_t proto_len,
                                  TF_Status* status) {
  tensorflow::AttrValue attr_value;
  if (!attr_value.ParseFromArray(proto, proto_len)) {
    status->status = InvalidArgument(
        "Unparseable AttrValue proto passed to "
        "TF_FunctionSetAttrValueProto");
    return;
  }

}

void TFE_InitializeLocalOnlyContext(TFE_Context* ctx, int keep_alive_secs,
                                    const void* proto, size_t proto_len,
                                    TF_Status* status) {
  tensorflow::ServerDef server_def;
  if (!server_def.ParseFromArray(proto, proto_len)) {
    status->status = tensorflow::errors::InvalidArgument(
        "Invalid tensorflow.ServerDef protocol buffer");
    return;
  }

//tensorflow/core:image_testdata
//tensorflow/core/kernels/cloud:bigquery_reader_ops
//tensorflow/python:extra_py_tests_deps
//tensorflow/python:mixed_precision
//tensorflow/python:tf_optimizer
//tensorflow/python:compare_test_proto_py
//tensorflow/python/framework:test_file_system.so
//tensorflow/python/debug:grpc_tensorflow_server.par
//tensorflow/python/feature_column:vocabulary_testdata
//tensorflow/python/util:nest_test_main_lib

  tensorflow::Status Run(const std::string& function_name,
                         const tensorflow::DeviceSet& device_set,
                         const tensorflow::ConfigProto& config_proto,
                         const FunctionOptions& function_options,
                         std::unique_ptr<tensorflow::Graph>* graph,
                         tensorflow::FunctionLibraryDefinition* flib_def,

        ":tf_tensor_hdrs",
        # TODO: Only include tf_tstring_hdrs. Don't expose the implementation of TF_TString to API
        # users.
        ":tf_tstring",
        "//tensorflow/core:protos_all_cc",
    ],
)

tf_cuda_library(
    name = "c_api_internal",
    hdrs = [
        "c_api.h",
        "c_api_internal.h",
        "c_api_macros.h",
        "tf_buffer.h",

        "//tensorflow/core:lib",
        "//tensorflow/core:protos_all_cc",
    ],
)

cc_library(
    name = "abstract_op_attrs",
    hdrs = ["abstract_op_attrs.h"],
    visibility = [
        "//tensorflow:internal",
    ],
    deps = [
        "//tensorflow/core:lib",
        "//tensorflow/core:protos_all_cc",
        "@com_google_absl//absl/container:inlined_vector",
    ],
)