ClientSession session(scope_test_);
  std::vector<Tensor> grad_result;
  TF_EXPECT_OK(session.Run({{x, {3.0f}}}, grad_outputs, &grad_result));
  EXPECT_EQ(grad_result.size(), 1);
  EXPECT_EQ(grad_result[0].NumElements(), 1);
  EXPECT_EQ(grad_result[0].flat<float>()(0), 17502.0f);
}

TEST_F(GradientsTest, MultiOutputNodeDependentOutputs) {
  auto x = Placeholder(scope_test_, DT_FLOAT);

  ASSERT_EQ(func_->record->fdef().signature().attr().size(), 2);
  EXPECT_EQ(func_->record->fdef().signature().attr(0).name(), "v1");
  EXPECT_EQ(func_->record->fdef().signature().attr(0).type(), "int");
  EXPECT_EQ(func_->record->fdef().signature().attr(1).name(), "v2");
  EXPECT_EQ(func_->record->fdef().signature().attr(1).type(), "int");
}

				}
				if !strings.Contains(err.Error(), tc.ExpectErr) {
					t.Fatalf("expected error %s, got %v", tc.ExpectErr, err)
				}
				return
			}
			if len(tc.ExpectErr) > 0 {
				t.Fatalf("expected error %s, got none", tc.ExpectErr)
			}
			if !reflect.DeepEqual(tc.Out, tc.ExpectOut) {
				t.Fatalf("unexpected result:\n %s", cmp.Diff(tc.ExpectOut, tc.Out))
			}
		})
	}

  }

  EXPECT_EQ(listener()->jit_compilation_activity().cluster_name(), "cluster_0");
  EXPECT_EQ(listener()->jit_compilation_activity().compile_count(), 2);

  EXPECT_GT(listener()->jit_compilation_activity().compile_time_us(), 0);
  EXPECT_EQ(listener()->jit_compilation_activity().cumulative_compile_time_us(),
            first_compile_time +
                listener()->jit_compilation_activity().compile_time_us());
}

}  // namespace

		},
		{
			name:        "space in the end of the manifest",
			input:       "well-formed-with-space",
			expectCount: 1,
			expectOut:   true,
		},
		{
			name:        "some random comments",
			input:       "well-formed-with-comments",
			expectCount: 1,
			expectOut:   true,
		},
		{
			name:        "invalid k8s object - missing kind",
			input:       "invalid",
			failOnError: true,

  EXPECT_TRUE(add.Run());
  EXPECT_EQ(add.error_msg(), "");
  EXPECT_EQ(add.result0(), 579);
  EXPECT_EQ(add.result0_data()[0], 579);
  EXPECT_EQ(add.result0_data(), add.results()[0]);

  const AddComp& add_const = add;
  EXPECT_EQ(add_const.error_msg(), "");
  EXPECT_EQ(add_const.arg0(), 123);
  EXPECT_EQ(add_const.arg0_data()[0], 123);
  EXPECT_EQ(add_const.arg0_data(), add.arg_data(0));
  EXPECT_EQ(add_const.arg1(), 456);

    TF_ASSERT_OK(scope_.status());
    float max_error;
    TF_ASSERT_OK((ComputeGradientError<float, float, float>(
        scope_, xs, x_shapes, ys, y_shapes, &max_error)));
    EXPECT_LT(max_error, 1e-4);
  }

  Scope scope_;
};

TEST_F(DataFlowGradTest, DynamicPartitionGrad) {
  TensorShape data_shape({2, 3, 2});
  auto data = Placeholder(scope_, DT_FLOAT, Placeholder::Shape(data_shape));

		s.Verify(s.Connect().RequestResponseAck(t, &discovery.DiscoveryRequest{ResourceNames: []string{testResourceName}}), expectCert)
	})
	t.Run("unsubscribe", func(t *testing.T) {
		s := setupSDS(t)
		c := s.Connect()
		res := c.RequestResponseAck(t, &discovery.DiscoveryRequest{ResourceNames: []string{testResourceName}})
		s.Verify(res, expectCert)
		c.Request(t, &discovery.DiscoveryRequest{

                           &shape_info));
  auto iter = shape_info.find("sink");
  EXPECT_NE(iter, shape_info.end());
  EXPECT_EQ(iter->second.size(), 1);
  EXPECT_EQ(iter->second.at(0).handle_type, DT_FLOAT);
  TensorShape resource_shape;
  EXPECT_TRUE(iter->second.at(0).handle_shape.AsTensorShape(&resource_shape));
  EXPECT_EQ(resource_shape, TensorShape({2, 3}));
}

}  // namespace

//   // Only asserts in dbg.
//   EXPECT_DEBUG_DEATH(DieInDebugOr12(&sideeffect), "death");
//
// #ifdef NDEBUG
//   // opt-mode has sideeffect visible.
//   EXPECT_EQ(12, sideeffect);
// #else
//   // dbg-mode no visible sideeffect.
//   EXPECT_EQ(0, sideeffect);
// #endif
// }
//
// This will assert that DieInDebugReturn12InOpt() crashes in debug
// mode, usually due to a DCHECK or LOG(DFATAL), but returns the