tape.Watch(inputs[0]);  // Watch x.
  AbstractTensorHandle* exp_output;
  TF_RETURN_IF_ERROR(ops::Exp(ctx, inputs[0], &exp_output, "Exp"));
  std::unique_ptr<GradientFunction> gradient_function(
      new PassThroughGradientFunction);
  tape.RecordOperation(inputs, {exp_output}, gradient_function.release());
  TF_RETURN_IF_ERROR(tape.ComputeGradient(ctx,
                                          /*targets*/ {exp_output},

*/

const get_email_domain = async ({github, username}) => {
  const user = await github.rest.users.getByUsername({
    username
  });
  if (user.status >= 400) {
    console.log(user);
    throw `Error Getting user data for ${username}`;
  }
  const email = user.data.email;
  let domain = "";
  if (email && email.lastIndexOf("@") != -1)
    domain = email.substring(email.lastIndexOf("@") +1);
  console.log(domain);

                                           /*abs_error*/ 0));
  ASSERT_NO_FATAL_FAILURE(CheckTensorValue(outputs[1], {0.0f}, /*dims*/ {},
                                           /*abs_error*/ 0));
  outputs[0]->Unref();
  outputs[1]->Unref();
}

#ifdef PLATFORM_GOOGLE
INSTANTIATE_TEST_SUITE_P(
    UnifiedCAPI, CppGradients,
    ::testing::Combine(::testing::Values("graphdef", "mlir"),

}

class FunctionErrorInjectionPass : public tensorflow::FunctionOptimizationPass {
 public:
  FunctionErrorInjectionPass(string error_node, string error_device)
      : error_node_(error_node), error_device_(error_device) {}
  tensorflow::Status Run(const std::string& function_name,
                         const tensorflow::DeviceSet& device_set,
                         const tensorflow::ConfigProto& config_proto,

  # scripts. By setting "expand_aliases", we enable alias expansion in
  # non-interactive shells as well.
  shopt -s expand_aliases
else
  echo '==TFCI==: Error: Cannot find path to grealpath or gstat'
  echo 'TF CI scripts require GNU core utilties to be installed. Please make'
  echo 'sure they are present on your system and try again.'
  exit 1
fi

                      bool use_function) {
  AbstractTensorHandle* model_outputs[1];

  // Run the model.
  TF_RETURN_IF_ERROR(
      RunModel(forward, ctx, inputs, model_outputs, use_function));
  AbstractTensorHandlePtr model_out(model_outputs[0]);

  TF_Tensor* model_out_tensor;
  TF_RETURN_IF_ERROR(GetValue(model_out.get(), &model_out_tensor));
  int num_dims_out = TF_NumDims(model_out_tensor);
  TF_DeleteTensor(model_out_tensor);

    # Change "testsuite > testcase,system-out" to "testsuite > testcase > error"
    for p in testsuite._elem.xpath(".//system-out"):
      for c in p.getparent().xpath(".//error | .//failure"):
        c.text = p.text
      p.getparent().remove(p)
    # Remove duplicate results of the same exact test (e.g. due to retry
    # attempts)
    for p in testsuite._elem.xpath(".//error | .//failure"):
      # Sharded tests have target names like this:

    *   One MUST NOT access `tensorflow::errors::Code` fields. Accessing
        `tensorflow::error::Code` fields is fine.
        *   Use the constructors such as `tensorflow::errors:InvalidArgument` to
            create status using an error code without accessing it.
        *   Use the free functions such as
            `tensorflow::errors::IsInvalidArgument` if needed.

# Register multi toolchains
load("@rules_python//python:repositories.bzl", "python_register_toolchains")  # buildifier: disable=same-origin-load

python_register_toolchains(
    name = "python",
    ignore_root_user_error = True,
    python_version = TF_PYTHON_VERSION,
)

load("@python//:defs.bzl", "interpreter")
load("@rules_python//python:pip.bzl", "pip_parse")

pip_parse(
    name = "pypi",

                                                   TF_Status* status);

// Aborts all ongoing collectives with the specified status. After abortion,
// subsequent collectives will error with this status immediately. To reset the
// collectives, create a new EagerContext.
//
// This is intended to be used when a peer failure is detected.
TF_CAPI_EXPORT extern void TFE_AbortCollectiveOps(TFE_Context* ctx,