TF_NewGraph(), TF_DeleteGraph);
  std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> s(TF_NewStatus(),
                                                           TF_DeleteStatus);

  TF_Operation* feed = Placeholder(func_graph.get(), s.get());
  TF_Operation* neg = Neg(feed, func_graph.get(), s.get());

  TF_Output inputs[] = {{feed, 0}};
  TF_Output outputs[] = {{neg, 0}};

				if i > 0 {
					buf.WriteString(", ")
				}
				w.writeType(buf, targs.At(i))
			}
			buf.WriteByte(']')
		}

	case *types.TypeParam:
		// Type parameter names may change, so use a placeholder instead.
		fmt.Fprintf(buf, "$%d", typ.Index())

	default:
		panic(fmt.Sprintf("unknown type %T", typ))
	}
}

func (w *Walker) writeSignature(buf *bytes.Buffer, sig *types.Signature) {

// `tensor_id`, associated with `session`. There must be a graph node named
// "fifo_queue_enqueue_<tensor_id>", to be executed by this API call. It reads
// from a placeholder node "arg_tensor_enqueue_<tensor_id>".
//
// `tensor` is still owned by the caller. This call will be blocked if the queue
// has reached its capacity, and will be unblocked when the queued tensors again

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

  VLOG(1) << "Running the enqueue op";
  TF_Output input{placeholder_op, 0};
  TF_SessionRun(session, /*run_options*/ nullptr,

 * obtaining a token and logging in using the provided credentials.
 *
 * <p>This class supports both GET and POST methods for token and login
 * requests. It also allows for the replacement of placeholders in URLs and
 * parameters with actual credentials.
 *
 * <p>Usage example:
 * <pre>
 * {@code
 * Map<String, String> params = new HashMap<>();
 * params.put("token_url", "http://example.com/token");