}
      Gradient* in_grad = in_grads[grad_index];
      if (in_grad != nullptr) {
        // ComputeGradient steals a reference
        vspace_.MarkAsResult(in_grad);
      }
      used_in_grads.push_back(in_grad);
    }
  }

  return tape->ComputeGradient(vspace_, targets, sources,
                               sources_that_are_targets, used_in_grads,
                               out_grads);

    const tensorflow::GraphDef& graph_def) {
  std::vector<std::pair<string, string>> grads;
  for (const tensorflow::GradientDef& grad : graph_def.library().gradient()) {
    grads.emplace_back(grad.function_name(), grad.gradient_func());
  }
  std::sort(grads.begin(), grads.end());
  return grads;
}

std::vector<string> GetFuncNames(const tensorflow::GraphDef& graph_def) {
  std::vector<string> names;

    }
  }

  TF_RETURN_IF_ERROR(GradientTape::ComputeGradient(
      vspace, target_tensor_ids, source_tensor_ids, sources_that_are_targets,
      output_gradients, result, /*build_default_zeros_grads*/ false));
  return absl::OkStatus();
}

// Helper functions which delegate to `AbstractOperation`, update
// the state of the ForwardOperation and call the tape as appropriate.

                 absl::Span<AbstractTensorHandle* const> grad_outputs,
                 absl::Span<AbstractTensorHandle*> grad_inputs) override {
    // TODO(b/161805092): Support broadcasting.

    DCHECK(grad_outputs[0]);
    grad_inputs[0] = grad_outputs[0];
    grad_inputs[1] = grad_outputs[0];

    grad_inputs[0]->Ref();
    grad_inputs[1]->Ref();
    return absl::OkStatus();
  }

==============================================================================*/
#include "tensorflow/c/experimental/gradients/math_grad.h"

#include "tensorflow/c/eager/c_api_test_util.h"
#include "tensorflow/c/eager/c_api_unified_experimental_internal.h"
#include "tensorflow/c/eager/unified_api_testutil.h"
#include "tensorflow/c/experimental/gradients/grad_test_helper.h"
#include "tensorflow/c/experimental/gradients/tape/tape_context.h"

  if (TF_GetCode(status) != TF_OK) return;
  if (!grad) return;

  status->status = g->graph.AddFunctionDef(grad->record->fdef(),
                                           grad->record->stack_traces());
  if (TF_GetCode(status) != TF_OK) return;

  tensorflow::GradientDef gdef;
  gdef.set_function_name(func->record->fdef().signature().name());
  gdef.set_gradient_func(grad->record->fdef().signature().name());

the project's [log viewer](https://cloud.google.com/logging/docs/view/overview) and/or the `gcloud logging read`
capability.

The following example grabs the last 10 `kubelet` logs containing the string "cmdAdd" in the log message.

```console

    service.addListener(new RecordingListener(service), directExecutor());
    Thread thread =
        new Thread() {
          @Override
          public void run() {
            // Internally stopAsync() grabs a lock, this could be any such method on
            // AbstractService.
            service.stopAsync();
          }
        };
    thread.start();
    thread.join(LONG_TIMEOUT_MILLIS);

	if err != nil {
		err = multierror.Append(err, fmt.Errorf("istioctl version %s cannot parse mesh config.  Install istioctl from the latest Istio release",
			version.Info.Version))
	}
	return cfg, err
}

// grabs the raw values from the ConfigMap. These are encoded as JSON.
func GetValuesFromConfigMap(ctx cli.Context, revision string) (string, error) {
	client, err := ctx.CLIClient()
	if err != nil {
		return "", err
	}

    service.addListener(new RecordingListener(service), directExecutor());
    Thread thread =
        new Thread() {
          @Override
          public void run() {
            // Internally stopAsync() grabs a lock, this could be any such method on
            // AbstractService.
            service.stopAsync();
          }
        };
    thread.start();
    thread.join(LONG_TIMEOUT_MILLIS);