TF_Operation* feed2 = Placeholder(func_graph_, s_, "feed2");

  // Outputs of the while loop corresponding to the two inputs above
  // The first one will the function's output
  std::vector<TF_Output> outputs;

  // Add while loop to func_graph_
  {
    // The inputs to the while loop
    std::vector<TF_Output> inputs = {{feed1, 0}, {feed2, 0}};
    std::unique_ptr<TF_WhileParams> params(new TF_WhileParams(

// restricted by using `--schemes` to specify a set of schemes to test.
//
// Example invocation:
//  bazel test //tensorflow/c/experimental/filesystem:modular_filesystem_test \\
//  --test_arg=--dso=/path/to/one.so --test_arg=--dso=/path/to/another.so \\
//  --test_arg=--scheme= --test_arg=--scheme=file
//
// Note that to test the local filesystem we use an empty value.

namespace tensorflow {

  EXPECT_EQ(2, num_dims);
  EXPECT_EQ(2, returned_dims[0]);
  EXPECT_EQ(3, returned_dims[1]);

  // Try to fetch a shape with the wrong num_dims
  TF_GraphGetTensorShape(graph, feed_out_0, returned_dims, 5, s);
  EXPECT_EQ(TF_INVALID_ARGUMENT, TF_GetCode(s)) << TF_Message(s);

  // Try to set an invalid shape (cannot change 2x3 to a 2x5).
  dims[1] = 5;
  TF_GraphSetTensorShape(graph, feed_out_0, dims, 2, s);

  if (async) {
    if (forward_input) {
      // Since the input was forwarded, we released the input handle right away
      // and hence expect the input to be forwarded to the return tensor.
      EXPECT_EQ(orig_ptr, TF_TensorData(t));
    } else {
      // In async mode we expect forwarding to work without releasing the input
      // handle since by the time the kernel is executed we have released the
      // handle in the client code.