TF_Graph* g1 = TF_NewGraph();
  TF_Graph* g2 = TF_NewGraph();

  TF_Operation* feed = Placeholder(g1, s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);

  // Attempt to create node in g2 with input from g1
  Neg(feed, g2, s);
  EXPECT_EQ(TF_INVALID_ARGUMENT, TF_GetCode(s));
  EXPECT_STREQ("foo", TF_Message(s));

  TF_DeleteGraph(g1);
  TF_DeleteGraph(g2);
  TF_DeleteStatus(s);
}
*/

        TFE_TensorHandleCopyToDevice(hcpu, ctx, name.c_str(), status.get());
    if (TF_GetCode(status.get()) != TF_OK) {
      ADD_FAILURE() << tag << " -- " << TF_Message(status.get());
      continue;
    }
    // Copy from device to the same device.
    TFE_TensorHandle* hdevice2 =
        TFE_TensorHandleCopyToDevice(hdevice, ctx, name.c_str(), status.get());
    if (TF_GetCode(status.get()) != TF_OK) {

// Loads a shared object implementing filesystem functionality.
static bool LoadDSO(const std::string& dso) {
  tensorflow::Status status = RegisterFilesystemPlugin(dso);
  if (!status.ok())
    VLOG(0) << "Filesystems from '" << dso
            << "' could not be registered: " << status;
  return status.ok();
}

// Tests whether a URI scheme results in a filesystem that is supported.
//

"""configure script to get build parameters from user."""

import argparse
import errno
import glob
import json
import os
import platform
import re
import subprocess
import sys

# pylint: disable=g-import-not-at-top
try:
  from shutil import which
except ImportError:
  from distutils.spawn import find_executable as which
# pylint: enable=g-import-not-at-top

build --define tsl_protobuf_header_only=true

build --define=use_fast_cpp_protos=true
build --define=allow_oversize_protos=true

build --spawn_strategy=standalone
build -c opt

# Make Bazel print out all options from rc files.
build --announce_rc

# TODO(mihaimaruseac): Document this option or remove if no longer needed
build --define=grpc_no_ares=true

# See https://github.com/bazelbuild/bazel/issues/7362 for information on what

      const std::vector<EdgeSpec>& c_edges,  // expected ctrl edges
      bool is_exact_edges = true) {
    // Build a set of edges from fdef
    std::set<EdgeSpec> a_edges;  // actual edges
    // Get edges from inputs to body nodes and between body nodes
    for (const NodeDef& node_def : fdef.node_def()) {
      for (int i = 0; i < node_def.input_size(); ++i) {

/// implements. Each of them is in a 1-to-1 correspondence with the wrapper
/// structures from the first section: these tables only contain function
/// pointers that operate on the corresponding data. Thus, the first argument of
/// each of these functions is a pointer to the paired struct and this argument
/// can be used to track state in between calls (from an object oriented point
/// of view, this can be viewed as a "vtable" for a "class" -- that is the

# shared object directly.
#
# For example, from Python tf.load_op_library loads a custom op library (via
# dlopen() on Linux), the library finds libtensorflow_framework.so (no
# filesystem search takes place, since libtensorflow_framework.so has already
# been loaded by pywrap_tensorflow) and registers its ops and kernels via
# REGISTER_OP and REGISTER_KERNEL_BUILDER (which use symbols from

//   control inputs). In other words, for every node in the body, each input
//   must be either listed in `inputs` or must come from another node in
//   the body. In particular, it is an error to have a control edge going from
//   a node outside of the body into a node in the body. This applies to control
//   edges going from nodes referenced in `inputs` to nodes in the body when
//   the former nodes are not in the body (automatically skipped or not