// aix, darwin, js/wasm, openbsd, solaris and wasip1/wasm don't implement
// waitid/wait6.

//go:build aix || darwin || (js && wasm) || openbsd || solaris || wasip1

package os

// blockUntilWaitable attempts to block until a call to p.Wait will
// succeed immediately, and reports whether it has done so.
// It does not actually call p.Wait.
// This version is used on systems that do not implement waitid,

		Run: func(data RunData) error {
			// transform data into a typed data struct
			d, ok := data.(myPhaseData)
			if !ok {
				return errors.New("invalid RunData type")
			}

			// implement your phase logic...
			fmt.Printf("%v\n", d.Data())
			return nil
		},
	}

	// Create another phase
	var myPhase2 = Phase{
		Name:  "myPhase2",
		Short: "Another phase of a kubeadm composable workflow...",

	if !ok {
		log.Fatal("first does not implement encoding.BinaryMarshaler")
	}
	state, err := marshaler.MarshalBinary()
	if err != nil {
		log.Fatal("unable to marshal hash:", err)
	}

	second := sha256.New()

	unmarshaler, ok := second.(encoding.BinaryUnmarshaler)
	if !ok {
		log.Fatal("second does not implement encoding.BinaryUnmarshaler")
	}

    *type = builder.getType<mlir::tf_type::tftype##Type>(); \
    return OkStatus();
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_types.def"

    default:
      return errors::Unimplemented(absl::StrCat(
          "Converting DataType '", DataTypeString(dtype), "' to MLIR Type"));
  }
}

Status ConvertScalarTypeToDataType(Type type, DataType* dtype) {
  if (type.isF16()) {
    *dtype = DT_HALF;

import java.io.FilterReader
import kotlin.reflect.KClass


/**
 * Adds a content filter to be used during the copy.
 * Multiple calls add additional filters to the filter chain.
 * Each filter should implement [FilterReader].
 * Import `org.apache.tools.ant.filters.*` for access to all the standard Ant filters.
 *
 * Examples:
 *
 * ```
 * filter<StripJavaComments>()
 * filter<com.mycompany.project.CustomFilter>()

			if !ok {
				t.Fatalf("Hash does not implement MarshalBinary")
			}
			enc, err := h2m.MarshalBinary()
			if err != nil {
				t.Fatalf("MarshalBinary: %v", err)
			}
			if !bytes.Equal(enc, tt.golden) {
				t.Errorf("MarshalBinary = %x, want %x", enc, tt.golden)
			}
			h3u, ok := h3.(encoding.BinaryUnmarshaler)
			if !ok {
				t.Fatalf("Hash does not implement UnmarshalBinary")
			}

import com.tngtech.archunit.lang.ArchRule;
import org.gradle.api.internal.provider.AbstractProperty;
import org.gradle.api.provider.Property;

import static com.tngtech.archunit.core.domain.JavaClass.Predicates.implement;
import static com.tngtech.archunit.lang.conditions.ArchConditions.beAssignableTo;
import static com.tngtech.archunit.lang.syntax.ArchRuleDefinition.classes;

@AnalyzeClasses(packages = "org.gradle")

                                      const AbstractOperation* value) {
  return tensorflow::errors::Unimplemented(
      "SetAttrFunction has not been implemented yet.");
}
Status TapeOperation::SetAttrFunctionName(const char* attr_name,
                                          const char* value, size_t length) {
  return tensorflow::errors::Unimplemented(
      "SetAttrFunctionName has not been implemented "
      "yet.");
}

	// px.private()

	// this assignment is correctly illegal:
	//	*Implementation does not implement p.Exported (missing p.private method)
	// px = new(Implementation)

	// this assignment is correctly illegal:
	//	p.Exported does not implement Exported (missing private method)
	// x = px

	// this assignment unexpectedly compiles and then executes
	defer func() {
		recover()
	}()

    for (const auto& t : signature.tuple()) {
      if (t.type() != TaggedValue::Type::TENSOR_SPEC) {
        break;
      }
    }
    return ::tensorflow::OkStatus();
  }
  return tensorflow::errors::Unimplemented(
      "Only functions with inputs/outputs containing a single tensor or a tuple"
      " of tensors are supported right now.");
}

Status VerifySupportedArgs(TaggedValue args) {