if (iter != fdef.ret().end()) {
        const auto& v = a_edges.insert({iter->second, arg.name()});
        ASSERT_TRUE(v.second) << "Duplicate edge " << iter->second << " -> "
                              << arg.name() << ". fdef: " << fdef.DebugString();
      } else {
        const auto& v = a_edges.insert({arg.name(), arg.name()});
        ASSERT_TRUE(v.second) << "Duplicate edge " << arg.name() << " -> "

  // Create an abstract tensor handle from tensorflow::Tensor.
  virtual ImmediateExecutionTensorHandle* CreateLocalHandleFromTFTensor(
      tensorflow::Tensor& t, const char* d_name) = 0;

  // Convert a TFRT TensorHandle to tensorflow::TensorHandle.
  virtual ImmediateExecutionTensorHandle* TFTensorHandleFromInterface(
      ImmediateExecutionTensorHandle* handle) = 0;

        "//learning/pathways/...",
        "//learning/serving/contrib/tfrt/mlir/canonical_ops/...",
        "//learning/serving/experimental/remote_predict/...",
        "//perftools/accelerators/xprof/convert/...",
        "//perftools/accelerators/xprof/integration_tests/...",
        "//smartass/brain/configure/...",
        "//tensorflow/...",
        "//tensorflow_decision_forests/...",

      const auto func_op = GetFunc(ctx, default_value.func(), status);
      if (!status->status.ok()) return;
      // TODO(nareshmodi): TFE_OpSetAttrFunction and TFE_OpSetAttrFunctionList
      // require TFE_Op* and just convert it internally a NameAttrValue, so
      // consider adding an overload to the C API to make this case easier.
      TFE_OpSetAttrFunction(op, attr_name, func_op);
      TFE_DeleteOp(func_op);
    } break;

  if not bazel_config_name:
    write_action_env_to_bazelrc(var_name, var)
  elif var:
    write_to_bazelrc('build --config=%s' % bazel_config_name)
  environ_cp[var_name] = str(var)


def convert_version_to_int(version):
  """Convert a version number to a integer that can be used to compare.

  Version strings of the form X.YZ and X.Y.Z-xxxxx are supported. The
  'xxxxx' part, for instance 'homebrew' on OS/X, is ignored.

    version = "v2"
    failed_packages = []

    logging.info("Try to import packages at runtime...")
    for package_name in self.api_packages_v2:
      # Convert package name to the short version:
      # tensorflow._api.v2.distribute.experimental to
      # tensorflow.distribute.experimental
      short_package_name = package_name.replace(f"_api.{version}.", "")

                           TF_DataType value) {
  auto iter = builder->attr_names.insert(attr_name).first;
  builder->Set(*iter, static_cast<tensorflow::DataType>(value));
}

void TF_AttrBuilderSetTypeList(TF_AttrBuilder* builder, const char* attr_name,
                               const TF_DataType* values, int num_values) {
  auto iter = builder->attr_names.insert(attr_name).first;

        missing_it->second--;
        VLOG(1) << "Op " << op_id << " missing " << missing_it->second
                << " output gradients";
        if (missing_it->second == 0) {
          op_stack.insert(op_stack.begin(), op_id);
        }
      }
    }
  }
  if (!state.op_tape.empty()) {
    return tensorflow::errors::Internal("Invalid tape state.");
  }
  if (result.size() != source_tensor_ids.size()) {

  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);
  string serialized_update = server_def.SerializeAsString();
  TFE_ContextUpdateServerDef(ctx, 0, serialized_update.data(),

 		tzh = tzh0;
-		(void) strncpy(tzh.tzh_magic, TZ_MAGIC, sizeof tzh.tzh_magic);
+		memcpy(tzh.tzh_magic, TZ_MAGIC, sizeof tzh.tzh_magic);
 		tzh.tzh_version[0] = ZIC_VERSION;
 		convert(eitol(thistypecnt), tzh.tzh_ttisgmtcnt);