limitations under the License.
==============================================================================*/

#include "tensorflow/c/eager/dlpack.h"

#include <vector>

#include "absl/strings/str_join.h"
#include "include/dlpack/dlpack.h"  // from @dlpack
#include "tensorflow/c/eager/c_api.h"
#include "tensorflow/core/platform/test.h"

namespace tensorflow {
namespace {

  job_def->set_name(job_name);
  for (int i = 0; i < num_tasks; i++) {
    int port = tensorflow::testing::PickUnusedPortOrDie();
    job_def->mutable_tasks()->insert(
        {i, tensorflow::strings::StrCat("localhost", ":", port)});
    LOG(INFO) << "Picked test port: " << port << " for job: " << job_name
              << ", task: " << i;
  }
  return server_def;
}

namespace tensorflow {

==============================================================================*/

#include "tensorflow/c/eager/c_api_unified_experimental.h"

#include <vector>

#include "absl/container/flat_hash_map.h"
#include "absl/strings/str_cat.h"
#include "tensorflow/c/eager/c_api_unified_experimental_internal.h"
#include "tensorflow/c/tf_datatype.h"
#include "tensorflow/c/tf_status.h"
#include "tensorflow/c/tf_status_helper.h"

                    const char* mutation_type) {
  // If any session has already run this node_id, mark this session as
  // unrunnable.
  for (auto it : graph->sessions) {
    mutex_lock session_lock(it.first->mu);
    if (it.first->last_num_graph_nodes > op.node.id()) {
      it.second = strings::StrCat(
          "Operation '", op.node.DebugString(), "' was changed by ",
          mutation_type,

        // just copy-off but includes a sum) and consideration of performance.
        //
        // TODO(allenl): There may be smarter ways to do this copy in some
        // cases, i.e. with a collective broadcast. We'll need to be careful
        // about things that are taken as inputs on the host or on their
        // existing device (for multi-device functions).
        std::unique_ptr<ParallelTensor> parallel_tensor(

using tensorflow::dyn_cast;
using tensorflow::ImmediateExecutionContext;
using tensorflow::ImmediateExecutionTensorHandle;
using tensorflow::string;
using tensorflow::unwrap;
using tensorflow::wrap;
using tensorflow::strings::StrCat;

TF_ExecutionContext* TF_NewEagerExecutionContext(TFE_ContextOptions* options,
                                                 TF_Status* s) {
  TFE_Context* c_ctx = TFE_NewContext(options, s);

      session->graph,
      tensorflow::strings::StrCat("fifo_queue_enqueue_", tensor_id).c_str());
  if (enqueue_op == nullptr) {
    status->status = tensorflow::errors::Internal(
        "Unable to find the enqueue node in the TF graph.");
    return;
  }

  TF_Operation* placeholder_op = TF_GraphOperationByName(
      session->graph,
      tensorflow::strings::StrCat("arg_tensor_enqueue_", tensor_id).c_str());

See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/

#include "absl/strings/str_cat.h"
#include "tensorflow/c/eager/c_api.h"
#include "tensorflow/c/eager/c_api_experimental.h"
#include "tensorflow/c/eager/c_api_internal.h"
#include "tensorflow/c/eager/c_api_remote_test_util.h"

  // Adding a non-existent remote worker to cluster def. This should cause the
  // UpdateServerDef call to fail.
  tensorflow::ClusterDef* cluster_def = server_def.mutable_cluster();
  tensorflow::JobDef* job_def = cluster_def->mutable_job(0);
  int port = tensorflow::testing::PickUnusedPortOrDie();
  job_def->mutable_tasks()->insert(
      {2, tensorflow::strings::StrCat("localhost:", port)});
  server_def.set_task_index(0);

#include <cstdlib>
#include <memory>
#include <string>
#include <string_view>
#include <utility>
#include <vector>

#include "absl/status/status.h"
#include "absl/status/statusor.h"
#include "absl/strings/str_cat.h"
#include "absl/time/time.h"
#include "absl/types/span.h"
#include "tensorflow/c/experimental/next_pluggable_device/tensor_pjrt_buffer_util.h"
#include "tensorflow/c/kernels.h"