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

package org.gradle.kotlin.dsl.execution

import org.jetbrains.kotlin.lexer.KtTokens.ANDAND
import org.jetbrains.kotlin.lexer.KtTokens.ARROW
import org.jetbrains.kotlin.lexer.KtTokens.AT
import org.jetbrains.kotlin.lexer.KtTokens.CLASS_KEYWORD
import org.jetbrains.kotlin.lexer.KtTokens.COLON

const (
	_ Operator = iota

	// Def is the : in :=
	Def   // :
	Not   // !
	Recv  // <-
	Tilde // ~

	// precOrOr
	OrOr // ||

	// precAndAnd
	AndAnd // &&

	// precCmp
	Eql // ==
	Neq // !=
	Lss // <
	Leq // <=
	Gtr // >
	Geq // >=

	// precAdd
	Add // +
	Sub // -
	Or  // |
	Xor // ^

	// precMul

    %2:2 = tf_executor.island wraps "tf.Identity"(%arg1) {device = "", dtype = "tfdtype$DT_INT32"} : (tensor<10xi32>) -> tensor<10xi32> loc ("bar")
    // The following node would be renamed to bar2
    %3:2 = tf_executor.island wraps "tf.Identity"(%2) {device = "", dtype = "tfdtype$DT_INT32"} : (tensor<10xi32>) -> tensor<10xi32> loc ("bar")

  func.func @main() {
    tf_executor.graph {
      %control = tf_executor.island {
        tf_executor.yield
      }
      tf_executor.fetch %control : !tf_executor.control
    }
    tf_executor.graph {
      %control = tf_executor.island {
        tf_executor.yield
      }
      tf_executor.fetch %control : !tf_executor.control
    }
    return
  }

  %graph:2 = tf_executor.graph {
    %0:2 = tf_executor.island wraps "tf.Const"() {device = "", dtype = "tfdtype$DT_FLOAT", value = dense<0.000000e+00> : tensor<f32>} : () -> tensor<f32> loc("const")
    %1:2 = tf_executor.island wraps "tf.Identity"(%0#0) {T = "tfdtype$DT_FLOAT", device = ""} : (tensor<f32>) -> tensor<f32> loc("identity")

    tf_executor.graph {
      %control = tf_executor.island {
        "tf.StatefulPartitionedCall"(%arg0) <{config = "", config_proto = "", executor_type = "", f = @partitioned}> : (tensor<*x!tf_type.resource>) -> ()
        tf_executor.yield
      }

          this->join(getLatticeElement(result), *getLatticeElement(arg.get()));
        }
      }
    } else if (auto island = dyn_cast<tf_executor::IslandOp>(op)) {
      for (auto &arg : island.GetYield()->getOpOperands()) {
        auto result = island.getResult(arg.getOperandNumber());
        this->join(getLatticeElement(result), *getLatticeElement(arg.get()));
      }
    } else {
      return false;

    // the function body or if they are nested in individual
    // `tf_executor.island`.
    for (Block& block : func.getBody()) BuildClusters(block, builder, info);
    func.walk([&](tf_executor::IslandOp island) {
      BuildClusters(island.GetBody(), builder, info);
    });
  }
}

}  // namespace

)

// GenerateDeltas computes Workload resources. This is design to be highly optimized to delta updates,
// and supports *on-demand* client usage. A client can subscribe with a wildcard subscription and get all
// resources (with delta updates), or on-demand and only get responses for specifically subscribed resources.
//

    }

    /**
     * The base directory for all reports
     * <p>
     * This value can be changed, so any files derived from this should be calculated on demand.
     *
     * @return The base directory for all reports
     */
    public File getBaseDir() {
        return baseDirectory.getAsFile().get();
    }

    /**