// partitioned tensor are combined into a single entry.
  const TensorSliceReader::VarToDataTypeMap& GetVariableToDataTypeMap() const;

  // Attempts to look up the tensor named "name" and stores the found result in
  // "out_tensor".
  void GetTensor(const string& name,
                 std::unique_ptr<tensorflow::Tensor>* out_tensor,
                 TF_Status* out_status) const;

 private:

fi

# Repair wheels with auditwheel and delete the old one.
if [[ "$TFCI_WHL_AUDIT_ENABLE" == "1" ]]; then
  python3 -m auditwheel repair --plat "$TFCI_WHL_AUDIT_PLAT" --wheel-dir . *.whl
  # if the wheel is already named correctly, auditwheel won't rename it. so we
  # list all .whl files by their modification time (ls -t) and delete anything
  # other than the most recently-modified one (the new one).
  ls -t *.whl | tail -n +2 | xargs rm
fi

  EXPECT_EQ(-1, TF_OperationOutputListLength(feed, "bogus", s));
  EXPECT_EQ(TF_INVALID_ARGUMENT, TF_GetCode(s));

  ASSERT_FALSE(GetAttrValue(feed, "missing", &attr_value, s));
  EXPECT_EQ(string("Operation 'feed' has no attr named 'missing'."),
            string(TF_Message(s)));

  // Make a constant oper with the scalar "3".
  TF_Operation* three = ScalarConst(3, graph, s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);

    } else {
      typed_inputs.emplace_back(input);
    }
  }

  absl::optional<std::vector<MaybeParallelTensorOwned>> maybe_typed_outputs(
      ExecuteWithSpecialOps(named_device->device(), named_device->name(),
                            context, std::move(typed_inputs), operation_name,
                            attributes, *num_outputs, status));
  if (TF_GetCode(status) != TF_OK) return;

                                                   size_t* len);

// On success, dequeues a tensor from a TF-managed FifoQueue given by
// `tensor_id`, associated with `session`. There must be a graph node named
// "fifo_queue_dequeue_<tensor_id>", to be executed by this API call.

// Caller must call TF_DeleteTensor() over the returned tensor. If the queue is
// empty, this call is blocked.
//

#include "tensorflow/c/c_api.h"
#include "tensorflow/c/eager/c_api.h"
#include "tensorflow/c/eager/c_api_experimental.h"

namespace tensorflow {
namespace parallel_device {

// Allocate a parallel device named `device_name` which forwards operations to
// `underlying_devices`, maintaining "parallel tensors" with components placed
// on each underlying device.
//
// For example if `device_name` is

// already-finalized operation.
//
// Note that TFE_OpGetFlatInputCount and TFE_OpGetFlatInput operate on a flat
// sequence of inputs, unlike TFE_OpGetInputLength (for getting the length of a
// particular named input list, which may only be part of the op's inputs).
TF_CAPI_EXPORT extern int TFE_OpGetFlatInputCount(const TFE_Op* op,
                                                  TF_Status* status);

TF_Tensor* TF_DequeueNamedTensor(TF_Session* session, int tensor_id,
                                 TF_Status* status) {
  assert(session);
  {
    tensorflow::mutex_lock c(session->graph->mu);
    VLOG(1) << "Dequeuing named tensor with id " << tensor_id
            << ", with input graph: "
            << session->graph->graph.ToGraphDefDebug().DebugString();
  }

  TF_Operation* dequeue_op = TF_GraphOperationByName(

// "/job:localhost/replica:0/task:0/device:CUSTOM:0".
//
// The custom device defines copy operations for moving TensorHandles on and
// off, and an execution operation for named operations. Often execution will
// simply wrap op execution on one or more physical devices.
//
// device_info is an opaque caller-defined type stored with the custom device

  EXPECT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

  // Create a new tensor_handle.
  TFE_TensorHandle* h0_task0_new = TestMatrixTensorHandle(ctx);

  // Check that copying it to the old remote device (named localhost) fails.
  TFE_TensorHandleCopyToDevice(h0_task0_new, ctx, remote_device_name, status);
  EXPECT_NE(TF_OK, TF_GetCode(status)) << TF_Message(status);

  // Copying and executing on the new remote device works.