TFE_Op* op = TFE_NewOp(ctx, "ReadVariableOp", status);
  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  TFE_OpSetAttrType(op, "dtype", TF_FLOAT);
  TFE_OpAddInput(op, var, status);
  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  int num_retvals = 1;
  TFE_Execute(op, out_value, &num_retvals, status);
  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  TFE_DeleteOp(op);

  (*module_ref)->setAttr("tf.devices", device_dict);

  mlir::TF::RuntimeDevices devices;
  EXPECT_TRUE(mlir::succeeded(GetDevicesFromOp(*module_ref, &devices)));

  ASSERT_EQ(devices.NumDevices(), 1);
  ASSERT_EQ(devices.device_names().size(), 1);
  ASSERT_EQ(DeviceNameUtils::ParsedNameToString(devices.device_names()[0]),
            "/job:worker/replica:0/task:0/device:CPU:0");
}

TEST(DeviceUtilTest, GetGpuDeviceMetadata) {

      }));

  ASSERT_EQ(inputs.size(), 1);
  EXPECT_EQ(inputs[0], "x");
  ASSERT_EQ(outputs.size(), 1);
  EXPECT_EQ(outputs[0], "r");

  ASSERT_EQ(in_specs.size(), 1);
  ASSERT_EQ(in_specs[0].first, tensorflow::DT_INT32);
  ASSERT_TRUE(in_specs[0].second.IsIdenticalTo(PartialTensorShape({1, 3})));

  ASSERT_EQ(out_specs.size(), 1);
  ASSERT_EQ(out_specs[0].first, tensorflow::DT_INT32);

  root.graph()->AddControlEdge(write, read);

  std::vector<std::pair<int, int>> incompatible_pairs;
  TF_ASSERT_OK(ComputeIncompatiblePairs(root.graph(), &incompatible_pairs));

  ASSERT_EQ(incompatible_pairs.size(), 1);
  std::pair<int, int> write_read_pair = {write->id(), read->id()};
  EXPECT_EQ(incompatible_pairs[0], write_read_pair);
}

TEST(ResourceOperationSafetyAnalysisTest, ReadWrite) {

  auto* h0_task1 =
      TFE_TensorHandleCopyToDevice(h0_task0, ctx, remote_device_name, status);
  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  auto* h1_task1 =
      TFE_TensorHandleCopyToDevice(h1_task0, ctx, remote_device_name, status);
  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

  TFE_Op* matmul = MatMulOp(ctx, h0_task1, h1_task1);

    return "else";
  }
};

TEST(VisitTest, Test1) {
  TaggedValue a(Int64(1)), b(Float32(1.1f));
  TaggedValue c = TaggedValue::None();

  ASSERT_EQ(a.visit<const char*>(Visitor()), "int64");
  ASSERT_EQ(b.visit<const char*>(Visitor()), "float32");
  ASSERT_EQ(c.visit<const char*>(Visitor()), "else");
}

}  // namespace impl
}  // namespace libtf

  };

  TF_ASSERT_OK(InitGraphPlugin(plugin_init));
  ASSERT_EQ(PluginGraphOptimizerRegistry::CreateOptimizers(
                std::set<string>{"Success"})
                .size(),
            1);
  ConfigList config = PluginGraphOptimizerRegistry::GetPluginConfigs(
      true, std::set<string>{"Success"});
  ASSERT_EQ(config.toggle_config["remapping"], RewriterConfig::OFF);
}

 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package org.gradle.test.fixtures.server

interface ServerExpectation {
    void assertMet()

 */

package org.gradle.test.fixtures.server

import groovy.transform.CompileStatic

@CompileStatic
abstract class ForbidOne extends OneRequestServerExpectation {

    void assertMet() {
        if (run) {
            throw new AssertionError(notMetMessage as Object)
        }
    }

    abstract String getNotMetMessage()

      TFE_NewOp(context.get(), "AssertAndCollective", status.get()),
      TFE_DeleteOp);
  ASSERT_EQ(TF_GetCode(status.get()), TF_OK) << TF_Message(status.get());
  std::unique_ptr<ParallelTensor> reduced_values =
      parallel_device.ScalarsFromSequence<float>({1.0, 2.0}, context.get(),
                                                 status.get());
  ASSERT_EQ(TF_GetCode(status.get()), TF_OK) << TF_Message(status.get());