targeted conformance profile:


                  HTTP Profile


                  1. HTTPRoute, Port: 80, Protocol: HTTP
                  2. HTTPRoute, Port: 443, Protocol: HTTPS, TLS Mode: Terminate, TLS keypair provided


                  TLS Profile


                  1. TLSRoute, Port: 443, Protocol: TLS, TLS Mode: Passthrough

	}

	for _, test := range tests {
		err := ValidateAppArmorProfileFormat(test.profile)
		if test.expectValid {
			assert.NoError(t, err, "Profile %s should be valid", test.profile)
		} else {
			assert.Error(t, err, fmt.Sprintf("Profile %s should not be valid", test.profile))
		}
	}
}

func TestValidateDownwardAPIHostIPs(t *testing.T) {
	testCases := []struct {

    analyzing input pipeline performance with TF Profiler.

*   [`tf.distribute.TPUStrategy`](https://www.tensorflow.org/api_docs/python/tf/distribute/TPUStrategy)
    is now a stable API and no longer considered experimental for TensorFlow.
    (earlier `tf.distribute.experimental.TPUStrategy`).

*   [TF Profiler](https://www.tensorflow.org/guide/profiler) introduces two new
    tools: a memory profiler to visualize your model’s memory usage over time

        "properties": {
          "localhostProfile": {

		{"Sample.Value", Field, 16},
		{"Value", Type, 16},
		{"ValueKind", Type, 16},
	},
	"runtime/pprof": {
		{"(*Profile).Add", Method, 0},
		{"(*Profile).Count", Method, 0},
		{"(*Profile).Name", Method, 0},
		{"(*Profile).Remove", Method, 0},
		{"(*Profile).WriteTo", Method, 0},
		{"Do", Func, 9},
		{"ForLabels", Func, 9},
		{"Label", Func, 9},
		{"LabelSet", Type, 9},