{"Name":"LD1 (multiple structures)","Bits":"0|Q|0|0|1|1|0|0|1|1|0|11111:5|1010:4|size:2|Rn:5|Rt:5","Arch":"Post-index Two registers, immediate offset variant","Syntax":"LD1 { <Vt>.<T>, <Vt2>.<T> }, [<Xn|SP>], <imm>","Code":"","Alias":""},
{"Name":"LD1 (multiple structures)","Bits":"0|Q|0|0|1|1|0|0|1|1|0|Rm:5|1010:4|size:2|Rn:5|Rt:5","Arch":"Post-index Two registers, register offset variant","Syntax":"LD1 { <Vt>.<T>, <Vt2>.<T> }, [<Xn|SP>], <Xm>","Code":"","Alias":""},

        run "resolve"

        then:
        executed(":lib:jar1", ":app:resolve")

        and:
        output.count("Transforming") == 0
    }

    def "transforms can be applied to multiple files with the same name"() {
        given:
        buildFile << """
            def f = file("lib.jar")
            f.text = "1234"

            dependencies {
                compile files(f)

	op_LM      uint32 = 0x9800 // FORMAT_RS1        LOAD MULTIPLE (32)
	op_LMD     uint32 = 0xEF00 // FORMAT_SS5        LOAD MULTIPLE DISJOINT
	op_LMG     uint32 = 0xEB04 // FORMAT_RSY1       LOAD MULTIPLE (64)
	op_LMH     uint32 = 0xEB96 // FORMAT_RSY1       LOAD MULTIPLE HIGH
	op_LMY     uint32 = 0xEB98 // FORMAT_RSY1       LOAD MULTIPLE (32)
	op_LNDBR   uint32 = 0xB311 // FORMAT_RRE        LOAD NEGATIVE (long BFP)

  let summary =
    "Replicate TensorList init ops for correct shape assignments in shape inference";

  let description = [{
    If we pass same TensorList to a while op as multiple arguments or just use
    the same TensorList at multiple places and assign different
    TensorListSetItem to elements of TensorList, the shape inference is then
    unable to identify the Shape of these args and thus the input TensorList

      "tf.C"() : () -> ()
      tf_device.return
    }) {num_cores_per_replica = 1, topology =  "", device_assignment =  []} : () -> ()
    func.return
  }

  // Tests extraction of a single outside compiled cluster with multiple ops and no input or output dependecies.

  // CHECK-LABEL: func @nodep_single_cluster_multiple_ops_outside_compilation
  func.func @nodep_single_cluster_multiple_ops_outside_compilation() -> () {

			}`, valid.Unix()),
			wantErr: `oidc: verify token: oidc: expected audience "my-client" got ["not-my-client"]`,
		},
		{
			// ID tokens may contain multiple audiences:
			// https://openid.net/specs/openid-connect-core-1_0.html#IDToken
			name: "multiple-audiences",
			options: Options{
				JWTAuthenticator: apiserver.JWTAuthenticator{
					Issuer: apiserver.Issuer{
						URL:       "https://auth.example.com",

		expectedNewlyActiveUDPServices: map[proxy.ServicePortName]bool{},
		expectedLocalEndpoints:         map[types.NamespacedName]int{},
	}, {
		// Case[3]: no change, multiple subsets, multiple ports, local
		name:              "no change, multiple subsets, multiple ports, local",
		previousEndpoints: multipleSubsetsMultiplePortsLocal,
		currentEndpoints:  multipleSubsetsMultiplePortsLocal,

nput-group-sm>.input-group-append>select.btn:not([size]):not([multiple]),.input-group-sm>.input-group-append>select.input-group-text:not([size]):not([multiple]),.input-group-sm>.input-group-prepend>select.btn:not([size]):not([multiple]),.input-group-sm>.input-group-prepend>select.input-group-text:not([size]):not([multiple]),.input-group-sm>select.form-control:not([size]):not([multiple]),select.form-control-sm:not([size]):not([multiple]){height:calc(1.8125rem + 2px)}.form-control-lg,.input-group-...

            is then described by additional elements.
            Projects should only list the license(s) that applies to the project
            and not the licenses that apply to dependencies.
            If multiple licenses are listed, it is assumed that the user can select
            any of them, not that they must accept all.
            ]]>
          </description>
          <association>
            <type>License</type>

org:leaf:1.0
\\--- org:foo:1.0
     \\--- substituted

org:leaf:2.0 -> 1.0
\\--- org:bar:1.0
     \\--- substituted
"""
    }

    def "shows multiple outgoing dependencies"() {
        given:
        ivyRepo.module("org", "leaf", "1.0").publish()
        ivyRepo.module("org", "middle", "1.0")
            .dependsOn("org", "leaf", "1.0")