pass over the examined Iterable yields at least one item that is equal to the specified item. Whilst matching, the traversal of the examined Iterable will stop as soon as a matching item is found. For example: assertThat(Arrays.asList("foo", "bar"), hasItem("bar")) Parameters: item - the item to compare against the items provided by the examined Iterable hasItem public static <T> Matcher<java.lang.Iterable<? super T>> hasItem(Matcher<? super T> itemMatcher) Creates a matcher for Iterables that only...

        module.getArtifactFile(classifier: "bar").text = "5678"

        given:
        buildFile << """
            repositories {
                maven { url "${mavenRepo.uri}" }
            }
            dependencies {
                compile 'test:test:1.3:foo'
                compile 'test:test:1.3:bar'
            }

            /*

			plugins: []framework.PreEnqueuePlugin{
				&preEnqueuePlugin{allowlists: []string{"foo", "bar"}},
				&preEnqueuePlugin{allowlists: []string{"bar"}},
			},
			pod:                   st.MakePod().Name("bar").Label("bar", "").Obj(),
			wantUnschedulablePods: 0,
			wantSuccess:           true,
		},
	}

	for _, tt := range tests {
		t.Run(tt.name, func(t *testing.T) {

    %cst = arith.constant dense<1> : tensor<1xi8>
    %0 = "tf.VarHandleOp"() {container = "", shared_name = "bar"} : () -> tensor<!tf_type.resource<tensor<*xi8>>>
    // CHECK: "tf.VarHandleOp"() <{container = "", shared_name = "bar"}> : () -> tensor<!tf_type.resource<tensor<1xi8>>>
    "tf.AssignVariableOp"(%0, %cst) : (tensor<!tf_type.resource<tensor<*xi8>>>, tensor<1xi8>) -> ()

transition:width .6s ease}@media (prefers-reduced-motion:reduce){.progress-bar{transition:none}}.progress-bar-striped{background-image:linear-gradient(45deg,rgba(255,255,255,.15) 25%,transparent 25%,transparent 50%,rgba(255,255,255,.15) 50%,rgba(255,255,255,.15) 75%,transparent 75%,transparent);background-size:1rem 1rem}.progress-bar-animated{-webkit-animation:progress-bar-stripes 1s linear infinite;animation:progress-bar-stripes 1s linear infinite}@media (prefers-reduced-motion:reduce){.progres...

transition:width .6s ease}@media (prefers-reduced-motion:reduce){.progress-bar{transition:none}}.progress-bar-striped{background-image:linear-gradient(45deg,rgba(255,255,255,.15) 25%,transparent 25%,transparent 50%,rgba(255,255,255,.15) 50%,rgba(255,255,255,.15) 75%,transparent 75%,transparent);background-size:1rem 1rem}.progress-bar-animated{-webkit-animation:progress-bar-stripes 1s linear infinite;animation:progress-bar-stripes 1s linear infinite}@media (prefers-reduced-motion:reduce){.progres...

							},
							{
								Port:  &networking.Port{Name: "http", Number: 80, Protocol: "HTTP"},
								Hosts: []string{"bar.example.com"},
							},
						},
					},
				},
			},
			[]config.Config{
				{
					Meta: config.Meta{Name: uuid.NewString(), Namespace: uuid.NewString(), GroupVersionKind: gvk.VirtualService},

 * </code></td></tr>
 * 
 * <tr><td width="20%"><code>
 *  smb1://host/share/foo/bar/
 * </code></td><td width="20%"><code>
 *  /share2/zig/zag
 * </code></td><td><code>
 *  smb1://host/share2/zig/zag
 * </code></td></tr>
 * 
 * <tr><td width="20%"><code>
 *  smb1://host/share/foo/bar/
 * </code></td><td width="20%"><code>
 *  ../zip/
 * </code></td><td><code>

color:#fff;text-align:center;background-color:#007bff;transition:width .6s ease}.progress-bar-striped{background-image:linear-gradient(45deg,rgba(255,255,255,.15) 25%,transparent 25%,transparent 50%,rgba(255,255,255,.15) 50%,rgba(255,255,255,.15) 75%,transparent 75%,transparent);background-size:1rem 1rem}.progress-bar-animated{-webkit-animation:progress-bar-stripes 1s linear infinite;animation:progress-bar-stripes 1s linear infinite}.media{display:-webkit-box;display:-ms-flexbox;display:flex;-we...

^bb0:
// CHECK: "tf.TensorProtoIntTensor"() {bar = #tf_type<tensor_proto : "0x68656C6C6F"> : tensor<2x1x4xi32>} : () -> ()
  "tf.TensorProtoIntTensor"(){bar = #tf_type<tensor_proto : "0x68656C6C6F"> : tensor<2x1x4xi32>} : () -> ()
// CHECK: "tf.TensorProtoFloatTensor"() {bar = #tf_type<tensor_proto : "0x68656C6C6F"> : tensor<2x1x4xf32>} : () -> ()