return absl::OkStatus();
  }

  // We conservatively assume that functions will both read and write resource
  // variables.  In the future we may consider doing some form of
  // inter-procedural analysis.
  if (MayCallFunction(n, flib_def)) {
    *out_resource_op_kind = XlaResourceOpKind::kReadWrite;
  } else {
    *out_resource_op_kind = std::nullopt;
  }

  return absl::OkStatus();
}

			}
			if got := calculateRangeOffset(cidr); got != tt.want {
				t.Errorf("DynamicRangeOffset() = %v, want %v", got, tt.want)
			}
		})
	}
}

// cpu: Intel(R) Xeon(R) CPU E5-2678 v3 @ 2.50GHz
// BenchmarkAllocateNextIPv4
// BenchmarkAllocateNextIPv4-24    	 1175304	       870.9 ns/op	    1337 B/op	      11 allocs/op
func BenchmarkAllocateNextIPv4Size1048574(b *testing.B) {

  // Check for presence of unknown side-effecting ops within the while loop
  // body. These ops act as barriers and the optimization would not yield much
  // inter iteration parallelism for this while loop body. So return with
  // warning.
  if (chain_resource_to_ops_map.count(kUnknownResourceAndDevice) > 0) {
    std::set<std::string> blocking_ops;

    // arguments must correspond to different resources and we can assign unique
    // IDs.
    assign_unique_id_to_all(func_op.getArguments());
  }

  // Since this analysis is neither inter-procedural nor inter-regional,
  // each region attached to Op's within a function is analyzed independently.
  // Seed this analysis for each such region by mapping all resource arguments

		"drop_negative":        "dropneg",
		"call_tree":            "calltree",
		"relative_percentages": "rel",
		"unit":                 "unit",
		"compact_labels":       "compact",
		"intel_syntax":         "intel",
		"nodecount":            "n",
		"nodefraction":         "nf",
		"edgefraction":         "ef",
		"trim":                 "trim",
		"focus":                "f",
		"ignore":               "i",

		"--line-numbers", fmt.Sprintf("--start-address=%#x", start),
		fmt.Sprintf("--stop-address=%#x", end)}

	if intelSyntax {
		if b.isLLVMObjdump {
			args = append(args, "--x86-asm-syntax=intel")
		} else {
			args = append(args, "-M", "intel")
		}
	}

	args = append(args, file)
	cmd := exec.Command(b.objdump, args...)
	out, err := cmd.Output()
	if err != nil {
		return nil, fmt.Errorf("%v: %v", cmd.Args, err)

    sdkmanager 'extras;google;simulators'; \
    sdkmanager 'extras;google;usb_driver'; \
    sdkmanager 'extras;google;webdriver'; \
    sdkmanager 'extras;android;m2repository'; \
    sdkmanager 'extras;intel;Hardware_Accelerated_Execution_Manager'; \
    sdkmanager 'extras;m2repository;com;android;support;constraint;constraint-layout;1.0.0'; \

				}
			}
			assert.Equal(t, testCase.expectedConvertedObject, outObject)
		})
	}
}

func TestUnstructuredToUnstructuredConversion(t *testing.T) {
	// eventually, we don't want any inter-unstructured conversion happen, but for now, the conversion
	// just copy/pastes
	scheme, _ := test.TestScheme()
	inUnstructured := &unstructured.Unstructured{
		Object: map[string]interface{}{
			"apiVersion": "v1",

Artifacts are typically designed to be used or consumed by users or other projects, or deployed to hosting systems.
In such cases, the artifact is a single file.
Directories are common in the case of inter-project dependencies to avoid the cost of producing the publishable artifact.

[[sub:terminology_capability]]
== Capability

A capability identifies a feature offered by one or multiple components.

namespace TF {

namespace {

// Note: This implements the fusions performed in the old Remapper Grappler
// pass. That pass has specific cases for GPU and based on different
// target configurations on both CPU and GPU (Intel MKL, ROCm, etc.). This MLIR
// pass covers (some of) the general CPU case and at the moment does not account
// for any target-specific configurations.

// This pass is being ported over from the Grappler Remapper pass based on