TensorShape x_shape({1, 4, 6, 1});
    Tensor x_data = MakeData<X_T>(x_shape);
    Output x, y;
    MakeOp<X_T>(op_type, x_data, {2, 3}, align_corners, half_pixel_centers, &x,
                &y);
    JAC_T max_error;
    TF_ASSERT_OK((ComputeGradientError<X_T, Y_T, JAC_T>(
        scope_, x, x_data, y, {1, 2, 3, 1}, &max_error)));
    EXPECT_LT(max_error, 1.5e-3);
  }

      Tensor y_data = (*y_datas)[y_idx];
      if (y_data.SharesBufferWith((*x_datas)[x_idx])) {
        // Create copies of outputs that share a buffer with any inputs since
        // the underlying buffer of the input Tensors are not copied for some
        // operations (i.e. Identity), which can lead to incorrect results for
        // the centered difference calculation.
        (*y_datas)[y_idx] = tensor::DeepCopy(y_data);
      }

    TF_ASSERT_OK(scope_.status());
    DataType x_type = DataTypeToEnum<X_T>::v();
    TensorShape shape({2, 3, 2});
    auto x = Placeholder(scope_, x_type, Placeholder::Shape(shape));
    Tensor x_data(x_type, shape);
    auto x_data_flat = x_data.flat<X_T>();
    for (int i = 0; i < x_data_flat.size(); ++i) {
      x_data_flat(i) = x_fn(i);
    }

    Output y;
    switch (op_type) {

			{"__eh_frame", "__TEXT", 0x100000fb8, 0x48, 0xfb8, 0x3, 0x0, 0x0, 0x6000000b},
			{"__data", "__DATA", 0x100001000, 0x1c, 0x1000, 0x3, 0x0, 0x0, 0x0},
			{"__dyld", "__DATA", 0x100001020, 0x38, 0x1020, 0x3, 0x0, 0x0, 0x0},
			{"__la_symbol_ptr", "__DATA", 0x100001058, 0x10, 0x1058, 0x2, 0x0, 0x0, 0x7},
		},
		nil,
	},
	{
		"testdata/gcc-amd64-darwin-exec-debug.base64",

	return sa
}

func makeSecret(name, caData, token string) *v1.Secret {
	out := &v1.Secret{
		ObjectMeta: metav1.ObjectMeta{
			Name:        name,
			Namespace:   testNamespace,
			Annotations: map[string]string{v1.ServiceAccountNameKey: testServiceAccountName},
		},
		Data: map[string][]byte{},
		Type: v1.SecretTypeServiceAccountToken,
	}
	if len(caData) > 0 {
		out.Data[v1.ServiceAccountRootCAKey] = []byte(caData)
	}

		if ldr.SymType(mi) != tp.expKind {
			t.Errorf("testing Loader.%s: expected kind %s got %s",
				tp.which, tp.expKind, ldr.SymType(mi))
		}
		if !bytes.Equal(ldr.Data(mi), tp.expData) {
			t.Errorf("testing Loader.%s: expected data %v got %v",
				tp.which, tp.expData, ldr.Data(mi))
		}
		relocs := ldr.Relocs(mi)
		if !sameRelocSlice(&relocs, tp.expRel) {
			t.Fatalf("testing Loader.%s: got relocslice %+v wanted %+v",

      set_static_data_result_index_table(data, ResultIndexToBufferIndex());
      set_static_data_num_results(data, kNumResults);
      set_static_data_arg_index_table(data, ArgIndexToBufferIndex());
      set_static_data_num_args(data, kNumArgs);
      set_static_data_num_variables(data, kNumVariables);
      set_static_data_result_index(data, kResultIndex);
      set_static_data_arg_shape_infos(data, ArgShapeInfos());

				multicluster.MultiClusterSecretLabel: "true",
			},
		},
		Data: map[string][]byte{
			key: data.Bytes(),
		},
	}
	return out, nil
}

func createBaseKubeconfig(caData []byte, clusterName, server string) *api.Config {
	return &api.Config{
		Clusters: map[string]*api.Cluster{
			clusterName: {
				CertificateAuthorityData: caData,
				Server:                   server,
			},
		},

			}
			state.sectdata[sect] = data
			bld.SetData(data)
		}
		bld.SetSize(int64(sect.Size))
		state.sectsyms[sect] = s
		if sect.Name == ".rsrc" || strings.HasPrefix(sect.Name, ".rsrc$") {
			ls.Resources = append(ls.Resources, s)
		} else if bld.Type() == sym.SSEHSECT {
			if sect.Name == ".pdata" {
				ls.PData = s
			} else if sect.Name == ".xdata" {
				ls.XData = s
			}
		}
	}

		}
		if g.freq != 0 {
			return fmt.Errorf("found multiple frequency events")
		}
		g.freq = freq
	case b.exp != event.NoExperiment:
		if g.expData == nil {
			g.expData = make(map[event.Experiment]*ExperimentalData)
		}
		if err := addExperimentalData(g.expData, b); err != nil {
			return err
		}
	default:
		g.batches[b.m] = append(g.batches[b.m], b)
	}
	return nil
}