ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
    TF_OutputListPushBack(func_outputs, add_output2, s);
    ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
    TF_OutputListPushBack(func_outputs, mm_output, s);
    ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
    func = TF_FinalizeFunction(graph_ctx, func_outputs, s);
    ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);

  ASSERT_TRUE(TF_GetCode(status) == TF_OK) << TF_Message(status);
  TF_DeleteGraph(function_graph);
  TFE_ContextOptions* opts = TFE_NewContextOptions();
  TFE_Context* ctx = TFE_NewContext(opts, status);
  ASSERT_TRUE(TF_GetCode(status) == TF_OK) << TF_Message(status);
  TFE_DeleteContextOptions(opts);
  TFE_ContextAddFunction(ctx, fn, status);
  ASSERT_TRUE(TF_GetCode(status) == TF_OK) << TF_Message(status);

  std::string translated_name = TranslateName(fname);
  ops_->new_random_access_file(filesystem_.get(), translated_name.c_str(),
                               file.get(), plugin_status.get());

  if (TF_GetCode(plugin_status.get()) == TF_OK)
    *result = std::make_unique<ModularRandomAccessFile>(
        translated_name, std::move(file), random_access_file_ops_.get());

  return StatusFromTF_Status(plugin_status.get());
}

    if (!block) {
      std::cerr << "No block for key " << key.first << "@" << key.second;
      abort();
    }
    MaybeFetch(key, block, status);
    if (TF_GetCode(status) != TF_OK) return -1;
    UpdateLRU(key, block, status);
    if (TF_GetCode(status) != TF_OK) return -1;
    // Copy the relevant portion of the block into the result buffer.
    const auto& data = block->data;
    if (offset >= pos + data.size()) {

EOF
  cat $BATS_TEST_TMPDIR/out
  [[ ! -s $BATS_TEST_TMPDIR/out ]]
}

@test "All tensorflow.org/code links point to real files" {
    for i in $(grep -onI 'https://www.tensorflow.org/code/[a-zA-Z0-9/._-]\+' -r tensorflow); do
        target=$(echo $i | sed 's!.*https://www.tensorflow.org/code/!!g')

        if [[ ! -f $target ]] && [[ ! -d $target ]]; then
            echo "$i" >> errors.txt
        fi

  TFE_DeleteContextOptions(opts);
  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());
  bool arrived = false;
  bool executed = false;
  const char* name = "/job:localhost/replica:0/task:0/device:CUSTOM:0";
  RegisterLoggingDevice(context, name, /*strict_scope_placement=*/true,
                        &arrived, &executed, status.get());
  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());

  TF_OperationDescription* desc = TF_NewOperation(graph, "Const", name);
  TF_SetAttrTensor(desc, "value", t, s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  TF_SetAttrType(desc, "dtype", TF_TensorType(t));
  *op = TF_FinishOperation(desc, s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  ASSERT_NE(*op, nullptr);
}

TF_Operation* Const(TF_Tensor* t, TF_Graph* graph, TF_Status* s,

-   Once the tests pass, we now bring all the code into the internal code base,
    using a job called "copybara".

**5. Copy to Google Internal codebase and run internal CI**

-   Once the PR is in the Google codebase, we make sure it integrates well with
    its dependencies and the rest of the system.
-   Rarely, If the tests fail at this stage, we cannot merge the code.

// in 'op' should not be mutated till the kernel execution actually finishes.
//
// For sync execution, if any of the inputs to `op` are not ready, this call
// will block till they become ready and then return when the kernel execution
// is done.
// TODO(agarwal): change num_retvals to int from int*.
TF_CAPI_EXPORT extern void TFE_Execute(TFE_Op* op, TFE_TensorHandle** retvals,

                                                    TF_Status* status);

// Report error (specified by error_code and error_message) to other tasks in
// the cluster.
TF_CAPI_EXPORT extern void TFE_ReportErrorToCluster(TFE_Context* ctx,
                                                    int error_code,
                                                    const char* error_message,