protocol: HTTP
---`
	mkCall := func(port int, tls simulation.TLSMode) simulation.Call {
		r := simulation.Call{Protocol: simulation.HTTP, Port: port, CallMode: simulation.CallModeInbound, TLS: tls}
		if tls == simulation.MTLS {
			r.Alpn = "istio"
		}
		return r
	}
	cases := []struct {
		name   string
		config string
		calls  []simulation.Expect
	}{
		{
			name:   "global disable",

			kubeConfig: "",
			calls: []simulation.Expect{{
				// Expect listener, but no routing
				Name: "defined port",
				Call: simulation.Call{
					Port:       9999,
					HostHeader: "blah.somedomain",
					Address:    "1234:1f1:1:1:1:1:1:1",
					Protocol:   simulation.HTTP,
				},
				Result: simulation.Result{
					ListenerMatched: "0.0.0.0_9999",

---
`
	cases := []struct {
		Name       string
		Call       simulation.Call
		Disabled   simulation.Result
		Permissive simulation.Result
		Strict     simulation.Result
	}{
		{
			Name: "tcp",
			Call: simulation.Call{
				Port:     70,
				Protocol: simulation.TCP,
				CallMode: simulation.CallModeInbound,
			},
			Disabled: simulation.Result{
				ClusterMatched: "inbound|70||",
			},

						Protocol:   simulation.HTTP,
					},
					Result: simulation.Result{ClusterMatched: "outbound|80||b.default"},
				},
				{
					Name: "undefined hostname",
					Call: simulation.Call{
						Port:       80,
						HostHeader: "c.example.com",
						Protocol:   simulation.HTTP,
					},
					Result: simulation.Result{Error: simulation.ErrNoVirtualHost},
				},
			},
		},
		simulationTest{

func NewSimulation(t *testing.T, s *xds.FakeDiscoveryServer, proxy *model.Proxy) *Simulation {
	return NewSimulationFromConfigGen(t, s.ConfigGenTest, proxy)
}

// withT swaps out the testing struct. This allows executing sub tests.
func (sim *Simulation) withT(t *testing.T) *Simulation {
	cpy := *sim
	cpy.t = t
	return &cpy
}

func (sim *Simulation) RunExpectations(es []Expect) {
	for _, e := range es {

//
// which carries the following notice:

/* Copyright (C) 1996, MPEG Software Simulation Group. All Rights Reserved. */

/*
 * Disclaimer of Warranty
 *
 * These software programs are available to the user without any license fee or
 * royalty on an "as is" basis.  The MPEG Software Simulation Group disclaims
 * any and all warranties, whether express, implied, or statuary, including any

#include "mlir/Pass/Pass.h"  // from @llvm-project

namespace mlir {
namespace func {
class FuncOp;
}  // namespace func

namespace quantfork {

/// Creates a pass that converts quantization simulation operations (i.e.
/// FakeQuant and those like it) to casts into/out of supported QuantizedTypes.
std::unique_ptr<OperationPass<func::FuncOp>> createConvertSimulatedQuantPass();

    Simulates the effect of uniform quantization with const range.
  }];

  let description = [{
    Given a const min, max, num_bits and narrow_range attribute, applies the
    same uniform quantization simulation as is done by the TensorFlow
    fake_quant_with_min_max_args op. See the fakeQuantAttrsToType() utility
    method and the quant-convert-simulated-quantization pass for further details.
  }];

  let arguments = (ins

    Simulates the effect of uniform quantization with const range.
  }];

  let description = [{
    Given a const min, max, num_bits and narrow_range attribute, applies the
    same uniform quantization simulation as is done by the TensorFlow
    fake_quant_with_min_max_args op. See the fakeQuantAttrsToType() utility
    method and the quant-convert-simulated-quantization pass for further details.
  }];

  let arguments = (ins

// nodes. This may cause incorrectness in graph analyses, but is useful for
// simulation or scheduling.
// If aggressive_shape_inference is true, nodes are executed on the host to
// identify output values when possible and does other aggressive strategies.
// This may cause incorrectness in graph analyses, but is useful for simulation
// or scheduling.
// If include_input_tensor_values is true, the values of constant