// Adds a copy of function `func` and optionally its gradient function `grad`
// to `g`. Once `func`/`grad` is added to `g`, it can be called by creating
// an operation using the function's name.
// Any changes to `func`/`grad` (including deleting it) done after this method
// returns, won't affect the copy of `func`/`grad` in `g`.
// If `func` or `grad` are already in `g`, TF_GraphCopyFunction has no

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  // Define the function and its grad
  DefineFunction(func_name_, &func_);
  TF_Function* grad_func;
  DefineFunction("MyGrad", &grad_func);

  // Add func and its gradient to host graph
  TF_GraphCopyFunction(host_graph_, func_, grad_func, s_);
  ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);

  // Verify that function and its grad are in host graph's GraphDef
  GraphDef gdef;

    while (taskFaker.isIdle()) {
      set("a", "a", "a")
      set("b", "b", "b")
    }
    val commitEditor = cache.edit("c")!!
    val abortEditor = cache.edit("d")!!
    cache.edit("e") // Grab an editor, but don't do anything with it.

    // Cause the rebuild action to fail.
    filesystem.setFaultyRename(cacheDir / DiskLruCache.JOURNAL_FILE_BACKUP, true)
    taskFaker.runNextTask()

  TF_DeleteBuffer(t_buffer);
}

REGISTER_OP("TestOpWithNoGradient")
    .Input("x: T")
    .Output("y: T")
    .Attr("T: {float, double}")
    .Doc(R"doc(
Test op with no grad registered.

x: input
y: output
)doc")
    .SetShapeFn(tensorflow::shape_inference::UnknownShape);

class CApiGradientsTest : public ::testing::Test {
 protected:
  CApiGradientsTest()

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